Biased galaxy formation in the fields of high-redshift AGN

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Galaxy clustering in the Herschel deep field

a r X i v :a s t r o -p h /0007224v 1 17 J u l 2000Mon.Not.R.Astron.Soc.000,000–000(0000)Printed 1February 2008(MN L A T E X style ﬁle v1.4)Galaxy clustering in the Herschel deep ﬁeldH.J.McCracken 1,3,T.Shanks 1,N.Metcalfe 1,R.Fong 1A.Campos 1,21Departmentof Physics,University of Durham Science Laboratories,South Rd,Durham DH13LE.2Instituto de Matematicas y Fisica Fundamental (CSIC)Serrano 113bis,E-28006Madrid,Spain 3Present address:Laboratoire d’Astrophysique de Marseille,13376Marseille Cedex 12,France1February 2008ABSTRACTWe present a study of the angular correlation function as measured in the William Herschel Deep Field,a high galactic latitude ﬁeld which has been the subject of an ex-tensive observing campaign from optical to infrared wavelengths.It covers 50arcmin 2and with it we are able to investigate the scaling of the angular correlation function to B ∼28,R,I ∼26,K ∼20and H ∼22.5.We compare our measurements to re-sults obtained from the smaller Hubble Deep Field.To interpret our results,we use a model which correctly predicts colours,number counts and redshift distributions for the faint galaxy population.We ﬁnd that at ﬁxed separation the amplitude of ω(θ)measured in BRI bandpasses is lower than the predictions of a model containing with no luminosity evolution and stable clustering growth in proper co-ordinates.However,in the near-infrared bandpasses,our measurements are consistent with the predictions of an essentially non-evolving K −selected galaxy redshift distribution.In the range B ∼27−28we ﬁnd that our correlation amplitudes are independent of magnitude,which is consistent with the observed ﬂattening of the number count slope and cor-respondingly slower increase of the cosmological volume element expected at these magnitudes.If our luminosity evolution models provide a correct description of the underlying redshift distributions (and comparisons to available observations at brighter magni-tudes suggest they do),then our measurements in all bandpasses are consistent with a rapid growth of galaxy clustering (0<ǫ<2in the normal parametrisation)on the sub-Mpc scales which our survey probes.We demonstrate that this rapid growth of clustering is consistent with the predictions of biased models of galaxy formation,which indicate that a rapid rate of clustering growth is expected for the intrinsically faint galaxies which dominate our survey.1INTRODUCTIONThe projected two-point galaxy correlation function ω(θ)has proved to be one of the most enduring statistics in ob-servational cosmology.This is a consequence of the relative ease with which it may be measured;for each galaxy,all one requires is positions and magnitudes.Starting with the early studies of clustering in the local universe using Schmidt plates (Groth &Peebles 1977)to more recent works using CCD-based detectors (Efstathiou et al.1991;Pritchet &In-fante 1992)these studies have probed galaxy clustering to very faint magnitudes.Normally,these surveys measure how the amplitude of the projected angular correlation function at a ﬁxed angular separation,A ω,varies as a function of sam-ple limiting magnitude –the “scaling relation”.Usually,this relation has been parametrised in terms of “epsilon mod-els”in which the three-dimensional correlation length r 0(z )scales monotonically with redshift (Groth &Peebles 1977;Phillipps et al.1978).These models also require a choice ofcosmology and knowledge of the underlying redshift distri-butions for each magnitude-limited sample.In this paper we will investigate the projected angu-lar clustering of the faint ﬁeld galaxy population.We char-acterise galaxy clustering as a function of sample limiting magnitude in BRIKH bandpasses.Our primary dataset is a deep,ground based survey of an area called ’the William Herschel deep ﬁeld’(WHDF).This has been described in several recent papers (Metcalfe et al.1996;McCracken et al.2000).Covering ∼50arcmin 2this survey comprises an area ∼10times larger area than the separate HDF-N and HDF-S ﬁelds.For comparison,we also present a complementary analysis of clustering amplitudes measured in these smaller ﬁelds,utilising the catalogues produced in Metcalfe et al (2000).Although similar studies of ω(θ)exist in the lit-erature (Efstathiou et al.1991;Roche et al.1993;Brain-erd,Smail,&Mould 1994;Hudon &Lilly 1996;Woods &Fahlman 1997)our survey diﬀers primarily in its depth2McCracken et.al(B∼28)and broad wavelength coverage(in this analysis we consider samples selected in BRIK bandpasses).To interpret our results we use redshift distributions derived from the luminosity evolution models we have de-scribed in our previous papers((McCracken et al.2000;Met-calfe et al.1996).These models are able to reproduce all the observable quantities of the faintﬁeld galaxy popula-tion(counts,colours,redshift distributions),at least for low Ω0universes and within current observational uncertainties (Metcalfe et al.1996);it is these successes which give us con-ﬁdence in using our models as probe of the clustering his-tory of the Universe,rather than using our measurements of Aωas a probe of the underlying redshift distributions. In our models,highΩ0Universes can be accommodated by the model if we add an extra population of low luminosity galaxies with constant star-formation rates which boost the counts at faint(B>25m)magnitude levels(Campos1997). We also considerﬂat cosmologies withΛ=0.For reference, the scaling relation computed for a model with stable clus-tering and no luminosity evolution is also presented.Models such as those presented in this paper are rela-tively successful in describing clustering measurements per-formed on deep blank-ﬁeld surveys like the one detailed in this work(Roche et al.1993;Brainerd,Smail,&Mould 1994).However,observations of the clustering properties of Lyman-break galaxies(Madau et al.1996)indicate that these objects have comparable clustering properties(Gi-avalisco et al.1998)to some classes of locally observed galax-ies,making such objects initially diﬃcult to understand in terms of this monotonic scaling of r0with redshift.We will explain how these observations can be understood in the context of the results presented in this paper.Our paper is organised as follows:in Section2we de-scribe in outline the preparation of our datasets;in Section3 we describe the techniques we use to measure and analyse our data;in Section4we present our measurements of the projected correlation function inﬁve bandpasses in compar-ison with previous work and investigate if our errors esti-mates are realistic;in Section5we compare our correlation measurements with the predictions of our evolutionary mod-els;andﬁnally,in Section6we outline the main conclusions from this work.2OBSER V ATIONS AND CATALOGUESFull details of the optical observations comprising the WHDF will be presented in a forthcoming paper(Metcalfe et al2000).A subset of our infrared observations of the WHDF is described in McCracken et al.(2000)which com-prises the K<20UKIRT observations.Additional infrared observations at Calar Alto Observatory produced a second catalogue limited at H<22.5which will be fully described in a separate paper(McCracken et al,in preparation).In this section we will brieﬂy describe our object detection and photometry techniques which are very similar to that usedin our previous galaxy counts papers(Metcalfe et al.1991;Jones et al.1991;Metcalfe et al.1995;McCracken et al.2000).All our optical data discussed in this paper was takenat the William Herschel Telescope(WHT),with the excep-tion of a short I−band exposure made at the Isaac NewtonTelescope(INT).After bias subtraction andﬂat-ﬁelding,the sky back-ground is removed and isophotal image detection is carriedout.These images are then removed from the frame,replacedby a local sky value,and the resulting frame smoothed heav-ily before being subtracted from the original.This producesa veryﬂat background.The isophotal detection process isthen repeated.A Kron(1980)-type pseudo-total magnitudeis then calculated for each image,using a local value of sky.Table1shows the magnitude limits for ourﬁelds.As inour previous papers the minimum Kron radius is set to bethat for an unresolved image of high signal-to-noise,and thecorrection to total is the light outside this minimum radiusfor such an image.Our measurement limits give the totalmagnitudes of unresolved objects which are a3σdetectioninside the minimum radius(which is typically∼1.4′′forthe WHDF data).Star-galaxy separation was done on theB frame using the diﬀerence between the total magnitudeand that inside a1′′aperture,as described in Metcalfe et al.(1991).This enabled us to separate to B∼24m.Some addi-tional very red stars were identiﬁed from the R and I frames.As the WHDF is at high galactic latitude the stellar con-tamination should in any case be quite low.For the purposesof measuring the correlation function,masksﬁles were alsoconstructed to cover regions containing bright galaxies orstars.The area of theﬁeld aﬀected by such bright objects isless than10%of the total.Similar methods were also used to generate cataloguesfrom the north and south Hubble deepﬁelds(i.e.,we donot use any of the existing HDF catalogues but use ourown independently written object detection and photometrysoftware).One signiﬁcant diﬀerence between the HDF dataand our ground-based data is of course their much higherresolution.As described fully in Metcalfe et al(2000,inpreparation),we visually inspect all detections on our HDFN/S data in an attempt to reduce the number of spuriousentries in our catalogues.We also carry out a’reassembly’process in which multiple detections on an individual galaxyare combined to produce a single detection.This admittedlysubjective procedure is unavoidable in the HDF cataloguesgiven the extremely high resolution of the data.3METHODS AND TECHNIQUES3.1Determining the angular correlation functionWe use the normal estimator of Landy&Szalay(1993),given in equation 1.Here we follow the usual notationwhere DD indicates the number of galaxy-galaxy pairs,DRgalaxy-random pairs and RR random-random pairs for agiven angular separation and bin width:ω(θ)=DD−2DR+RRGalaxy clustering in the Herschel deepﬁeld3Filter U B R I K HLimit(3σ)26.827.926.323.5/25.620.022.5Area(arcmin2)48.548.548.588.3/53.047.250Table1.Photometric limits of the WHDF.The two magnitude limits in I refer to two separate surveys,one carried out at the INT (and covering88.3arcmin2and the other based on WHT data.For a range of magnitude-limited samples of each cata-logue,ω(θ)is computed using equation1for a series of binsspaced in increments of0.2in log(θ),whereθis in degrees.As we have only observed oneﬁeld we cannot use theﬁeld-to-ﬁeld variance to estimate the errors in each bin;insteadwe implement a bootstrap-resampling technique(Barrow,Sonoda,&Bhavsar1984;Ling,Barrow,&Frenk1986).Inthis method,the error in each bin is computed from thevariance of the estimator as applied to a large(∼200)num-ber of bootstrap-resampled catalogues.As expected,thesebootstrap errors are larger(normally∼×2)than the normal√Ω2 θ−δdΩ1dΩ2(3)whereθis the angular separation of each galaxy pair and dΩ1and dΩ2the solid angle subtended by each pair.If we assume a power-law correlation function,ω(θ)∝θ−0.8we may calculate this quantity for ourﬁelds by direct integra-tion.Typically weﬁnd C∼13for the WHDF and∼40for the HDF(we must assume a slope for power-law correlation function as we cannot calculate it directly from this data;−0.8allows us to compare our work with similar studies in the literature).The error on Aω,the overallﬁt,is determined from the method of Marquardt(1963),as described in Press et al. (1986).This method combines errors on each bin in an in-dependent manner to calculate the total error of theﬁt. Figure1showsﬁts made for the B−band catalogue.We determine correlation amplitudes for the Hubble deepﬁeld data using a similar procedure.In this case we ﬁt ourﬁnal power law to an average of the correlation func-tion determined independently on each of the three WFPC2 chips.For our NICMOS correlation amplitude,we compute our correlation functions from the total numbers of pairs from both surveys.For all these space-based data sets the ﬁeld of view is extremely small,and consequently the re-quired integral constraint correction is very large.Addition-ally,the small numbers of pairs involved means thatﬁts are generally dependent on three or fewer bins,and for this rea-son our resulting correlation amplitudes determined from these data should be regarded as upper limits on theﬁttedamplitudes,rather than deﬁnitive measurements.In order to Figure1.ω(θ)as measured for samples limited at B<27m and B<28m.The solid line shows theﬁt toω(θ)=Aω(θ−0.8−C) where C is the“integral constraint”term described in the text and Aωis the value ofω(θ)at1◦try to reduce problems from“merged”objects as described in Section2we carry out ourﬁts at angular separation>1′′.3.2Modelling the correlation functionWe would like to compare our measured correlation ampli-tudes with those of model predictions.In order to do this we must assume a functional form for the spatial correlation function.From the results of large surveys(Groth&Peebles 1977;Davis&Peebles1983;Maddox et al.1990b)it is found thatξ(r)(the spatial correlation function)is well approxi-mated byξ(r)=(r0/r)γ,at least for scales<20h−1Mpc. Projecting a model forξ(r)onto the two-dimensional distri-bution of galaxies measured byω(θ)involves integrating this function over redshift space using Limber’s formula(Limber 1953).We must parametrise the scaling of the correlation func-tion with redshift.Early papers(Groth&Peebles1977; Phillipps et al.1978)assumed a scaling of the form ξ(r,z)=h(z) r04McCracken et.alwhereh(z)=(1+z)−(3+ǫ)(5) (in this case r is the proper distance);this relation has been used in many recent observationally-motivated studies inves-tigating the projected two-point function(Efstathiou et al. 1991;Roche et al.1993;Brainerd,Smail,&Mould1994; Infante&Pritchet1995a;Brainerd&Smail1998).To derive an expression forω(θ),the projected corre-lation function,we note that for small angles,the relation betweenω(θ)andξ(r)becomes(Efstathiou et al.1991)ω(θ)=√Γ(γ/2)Adz 2dz/∞dNdγ−1A(z)(dr(z)/dz)(8)where d A(z)is the angular diameter distance and dr(z)/dz is the derivative of the proper distance.Analysis of the aforementioned large local redshift sur-veys suggests thatγ=1.8,leading to three cases of interest to us:clusteringﬁxed in proper coordinates,in which case ǫ=0.0;clusteringﬁxed in co-moving coordinates which givesǫ=−1.2.Finally,the predictions of linear theory give ǫ=1.0.This formalism has been widely used in many papers which investigate the clustering of faintﬁeld galaxies:see, for example,Infante&Pritchet(1995b),Woods&Fahlman (1997).As we have already noted,in these“epsilon models”characterised by equation4the co-moving galaxy correla-tion length decreases monotonically with redshift(providing of courseǫ>−1.2,which produces models with clustering constant in co-moving co-ordinates)However,several recent works have indicated that this may not be a realistic as-sumption.In theoretical studies,both N-body simulations (Colin et al.1999)and semi-analytic models(Baugh et al. 1999;Kauﬀmann et al.1999)indicate that the co-moving galaxy correlation length decreases until z∼1−2after which it increases again.These theoretical studies(Gover-nato et al.1998)also allow us to explain the high clustering amplitudes observed for Lyman break galaxies at z∼3(Gi-avalisco et al.1998;Adelberger et al.1998)as a consequence of their formation in highly biased environments.Further-more,the clustering growth is expected to be more rapid for less massive objects and and for clustering amplitudes measured on smaller scales(Baugh et al.1999).Motivated by these works we also model our correla-tion amplitudes using a modiﬁcation of equation4.In place of the normal epsilon parametrisation,we have used in the relativistic Limber’s equation a more general form for the evolution ofξ(r,z),namelyξ(r,z)= r com0(z)(1+z)r0 γ(10) To illustrate the possible eﬀect of modelling more exactlythe evolution of the correlation function,we have used the evolution seen in the large N-body simulation of Kravtsov &Klypin(1999);the semi-analytic models mentioned above produce a similar form for the evolution ofξ(r,z)in their simulations.As ourﬁeld sample is dominated by spirals, we have therefore considered the haloes of the simulation having velocity v>120km−1.Also,asω(θ)for these deep ﬁelds has,as usual,beenﬁtted to a−0.8power law,we have converted the Colin et al.data to provide the same correlation strength as a−1.8power law forξ(r,z)at a comoving separation of0.3h−1Mpc,which at the depths of our data here corresponds roughly to the angular scale of ourestimates forω(θ).Finally,to obtain the function,r com(z), a splineﬁt was made to the converted Colin et al.data points with a simple linear extrapolation to redshifts larger than the maximum redshift,z=5,for which they have estimated the correlation function for their simulation.Fig.2plots the resulting form of the evolution used for r com(z) normalised to r0.In using this in Limber’s equation,we have taken,as with Roche et al.(1993),r0=4.3h−1Mpc,which is little diﬀerent from the converted Colin et al.value of 4.2h−1Mpc.Galaxy clustering in the Herschel deepﬁeld53.3Calculating dn/dzFrom equation7we see that the amplitude ofω(θ)depends on the redshift distribution,dn/dz.To produce these red-shift distributions we employ a pure luminosity evolution (PLE)model in which star-formation increases exponen-tially with look-back time.Earlier versions of these models are discussed in our previous papers(Metcalfe et al.1991; Metcalfe et al.1995;Metcalfe et al.1996),and a full descrip-tion of the model used in this paper is given in(McCracken et al.2000).In this paper we assume H0=50kms−1Mpc−1, although changing the value of H0does not markedly af-fect our conclusions.Two values of the deceleration param-eter q0=0.05and q0=0.5,are adopted,corresponding to open andﬂat cosmologies respectively.The input parame-ters to our models consist of observed local galaxy param-eters(namely,rest-frame colours and luminosity functions) for each of theﬁve morphological types(E/S0,Sab,Sbc, Scd and Sdm)we consider in our models.These morpho-logical types are divided into early-type(E/S0/Sab)and spiral(Sbc/Scd/Sdm)and these two classes are each given a separate star-formation history,parametrised in terms of an e-folding timeτ.We compute the k+e corrections us-ing the models of Bruzual&Charlot(1993).We could,in principle,sub-divide the spirals into diﬀerent morphologi-cal types each with diﬀerent star formation histories but for simplicity we do not;(k+e)corrections for the diﬀerent types are fairly similar to each other in these models in any case.Instead,taking a Sbc model as representative of all types we produce the other types by normalising the Sbc track to the observed rest-frame colours.As in our earlier papers(Jones et al.1991;Metcalfe et al.1991;Metcalfe et al. 1995;McCracken et al.2000),the normalisations of our lu-minosity functions are chosen to match the galaxy counts at B∼18−20and we seek to explain the low number counts at bright magnitudes from a combination of photometric er-rors and anomalous galaxy clustering,rather than substan-tial and hence unphysical evolution at low redshift in the luminosity of galaxies.Our models also include the eﬀects of the Lyman-αforest,and,for spiral types,dust extinction corresponding to the Large Magellanic Cloud as described in Pei(1992).The model redshift distributions produced are in good agreement with the redshift distributions of the CFRS (Lilly et al.1995a)and from the Keck Hawaii redshift sur-vey(Cowie,Songaila,&Hu1996).To illustrate the eﬀect which the inclusion of the evolutionary corrections have on our computed correlation function scaling relation,we also calculate an non-evolving redshift distribution.This is pro-duced by applying k−corrections only to each galaxy type. 4MEASURED AMPLITUDESIn this Section we will present a comparison between our measurements of Aωand those in the literature.We defer an analysis of the implications these measurements have for the growth of galaxy clustering,as well as a discussion of our evolutionary models,to Section5;here we present com-parisons only with the non-evolving,ǫ=0,q0=0.05model.In panels a–d of Figure3we plot ourﬁtted correlation amplitudes extrapolated to one degree(ﬁlled symbols,cir-cles for WHDF and squares for HDF)as a function of sam-ple limiting magnitude for BRIK bandpasses in comparison with measurements from the literature(open symbols).The solid line shows the predictions of the stable clustering,ǫ=0non-evolving(i.e.,no luminosity evolution)model,com-puted assuming r0=4.3h−1Mpc and q0=0.05(This value of r0was chosen to produce the correct clustering ampli-tude at brighter magnitudes as measured from early Schmidtplate surveys(Jones,Shanks,&Fong1987;Stevenson et al. 1985).We adopt the same value of r0for all bandpasses;inSection5.4we discuss if this is an appropriate assumptionfor our data.)Starting with the B−band,we note that here ourWHDF sample reaches extremely high galaxy surfacedensity—approaching∼106gal deg−2at B=28m,and furthermore it probes to the highest redshift;our low-q0evolutionary models indicate that by B∼28we reachingz med∼2.Moreover,our measurements of the B−band cor-relation function are signiﬁcantly deeper than any previouslypublished work.Our brightest bin,at B<27.0,is in agree-ment with the correlation amplitude measured by Metcalfe et al.(1995).Faintwards of B=27,our correlation am-plitudes remainﬂat.The errors on ourﬁtted correlations in B are relatively low in comparison with our other band-passes because at B<28we detect∼6000galaxies,more than in any other bandpass.Our HDF-N/S clustering mea-surements are in agreement with the measurement from the much larger area of the WHDF.Our non-evolving models have some important diﬀer-ences with those used in the earlier works of Roche et al. (1993)and Metcalfe et al.(1995).Firstly,our models in-clude the eﬀects of internal extinction by dust(correspond-ing to A B=0.3mag,using the dust model of Pei(1992)) and reddening by the Lyman alpha forest(as modelled in Madau(1995)).Both of these eﬀects may become signiﬁcant at the very faintest magnitudes we reach,where z med>2. Secondly,our k−corrections are computed from the mod-els of Bruzual&Charlot(1993)for both our evolving and non-evolving models,whereas Roche et al.(1993)and Met-calfe,Fong,&Shanks(1995)used polynomialﬁts to the spectral energy distributions of Pence(1976)for their non-evolving models.Theseﬁts extend only to z∼2and are held constant at higher redshifts.Thirdly,the redshift dis-tributions in these earlier papers were artiﬁcially truncated at z=3.The sum eﬀect of these diﬀerences is that in Roche et al.(1993)and Metcalfe et al.(1995)the slope of the Aω–magnitude limit scaling relation remains constant whilst our slope begins to decrease at B∼26.By this magnitude limit the diﬀerence between our predictions and these previous works is∼0.2in log(Aω).Our R−band correlations plotted in panel(b)of Fig-ure3reach R<26,although the number of galaxies in this catalogue is much smaller(∼300)than in B−and consequently our errors are larger.Our measured clustering amplitude at R<25.5agrees well with the faintest data point of Brainerd,Smail,&Mould(1994);unfortunately, our survey area is too small to permit us to check our clus-tering amplitudes with values from the literature measured at brighter magnitudes such as the large,∼2deg2CCD survey of Roche&Eales(1999).Our measured clustering amplitudes in R−in the WHDF are much lower than the predictions of the non-evolving,stable clustering model.Our HDF clustering measurements are in good agreement with6McCracken et.alFigure3.The logarithm of the amplitude of the angular correlation functionω(θ)at one degree(Aω)in the WHDF(ﬁlled circles), HDF-N(ﬁlled squares)and HDF-S(ﬁlled pentagons)shown as a function of apparent magnitude for BRIK selected samples(panels a–d).For I,correlations are plotted as a function of sample median magnitude.Open symbols show points from the literature.The solid line shows the predictions a non-evolving model withǫ=0and with r0=4.3h−1Mpc and q0=0.05.Error bars on our measurements are calculated by a bootstrap resampling technique,as described in Section3.1.Galaxy clustering in the Herschel deepﬁeld7the HDF clustering measurements of Villumsen,Freudling, &Da Costa(1997).For our I−band measurements,shown in panel(c)of Figure3,we follow the practice in the literature and show correlation amplitudes as a function of sample median mag-nitudes and not limiting magnitudes.We follow the same procedure for our model correlation amplitudes which are plotted at the median magnitude of each magnitude lim-ited slice.In addition to our I<26WHT data,we have a second,larger image taken at the INT which overlaps the WHDF.This covers a total of∼80arcmin2to I<23.5and allows us to determine Aωfrom I med=20to I med=22(the three brightest WHDF bins on the graph).The faintest bin in this INT dataset is in agreement with our measurements from the brightest bin of the WHT dataset.Furthermore, the preliminary result from the large-area0.2deg2survey of Woods et al.(in preparation),shown as an open square, is agreement with our WHT measurement.At I med∼26, measurement from the HDFﬁelds appear to favour the lower values found in the WHDF.We note also that fainter I med∼21,our measurement are below the predictions of the non-evolvingǫ=0model.Faintwards of I med∼23a discrepancy emerges be-tween our measurements and two previously published stud-ies.At I med∼24,our WHDF clustering measurements are ∼5times lower than the measurements made by Brain-erd&Smail(1998)over two slightly smallerﬁelds of area ∼30arcmin2at a similar limiting magnitude.At brighter magnitudes,our points are also below the faintest bins of Postman et al.(1998).This work is a large-area CCD survey covering a contiguous16deg2area and is currently the most reliable determination of galaxy clustering over wide angles and at intermediate(z∼1)depths.We defer a detailed analysis of these diﬀerences until Section4.1where we will attempt to quantify if the discrepancies between our survey and the works of Postman et al.and Brainerd&Smail could be explained in terms of cosmic variance eﬀects.Finally,we turn to an investigation of galaxy correla-tions for K−selected samples.Until very recently measuring ω(θ)at near-infrared wavelengths was time-consuming and diﬃcult as typical detectors covered only∼1arcmin2.How-ever,wide-format IR arrays are becoming available making it now possible to conduct wide,deep surveys of the near-infrared sky.Theﬁlled circles in panel(d)of Figure3shows clustering amplitudes determined from our faint,H<22.5, wide area(∼50arcmin2)Calar Alto Survey are shown, which will be described fully in a forthcoming paper(Mc-Cracken et al2000,in preparation).Similarly,also plotted are clustering measurements from our6′×6′UKIRT IR-CAM3mosaic(McCracken et al.2000).At K∼27we have computed a single point from NICMOS data taken as part of the north and south Hubble deepﬁelds program(we trans-form from H to K using a model(H−K)colour).We note that all our measurements are in agreement with the predic-tions of our stable clustering,no luminosity evolution model.In plotting the H−limited Calar Alto points on our K−limited scaling relation we make two assumptions:ﬁrstly,at K∼22,(H−K)∼0.3;and secondly,for a given surface density,the clustering properties of H−selected and K−se-lected galaxies is identical.Theﬁrst assumption seems rea-sonable,given that at K∼20,galaxies in our survey have (H−K)∼0.3and it is unlikely that they become signiﬁ-cantly bluer by K∼22.The K−selected(I−K)histogramsshown in McCracken et al.(2000)support this.Also given that our Calar Alto H<20Aωagrees with our UKIRT K<19.5point,we conclude that our second assumption isalso valid.Our points at K=19−20agree with the survey of Roche,Eales,&Hippelein(1998)and Roche&Eales(1999);however at fainter magnitudes there is a discrepancy between our amplitudes and the measurement of Carlberg et al.(1997).Once again,we defer a detailed discussion ofthe possible explanation of these diﬀerences until the follow-ing section.4.1Quantifying errors in the correlation function In this Section we will investigate if we have estimated the magnitude of our correlation function error bars correctly.The small size of ourﬁeld means our integral constraint (equation(3)corrections are large,and consequently accu-rate measurements ofω(θ)are dependent on an accurate de-termination of this quantity.Our main motivation is to see if we can explain the discrepancies between our measurements of Aωat I<25and K∼21.5with those of Brainerd&Smail(1998)and Carlberg et al.(1997).There are already indications that such“extra”variance could be signiﬁcant at the depths of our survey.Postman et al.(1998)directlyaddress this question at shallower depths in their work which covers∼16deg2.By extracting250independent16′×16′ﬁelds from their survey(each of which isﬁve times larger than the WHDF but at a brighter limiting magnitude)theyﬁnd that the variance onω(1′)is comparable to its mean value of∼0.045,with extreme values reaching×3this.Fur-thermore,they suggest that as the error distribution for Aωis non-Gaussian,and skewed positively,there could be many more areas in which Aωis below the mean value,rather than above it.To quantify the amount of“extra”variance which could aﬀect clustering measurements in a very deepﬁeld like the WHDF we adopt a simple approach and generate large mock catalogues using the method of Soneira&Peebles(1978). This is an purely empirical approach to generate a hierar-chically clustered distribution of points.We start by placing within a sphere of radius R a random distribution of sub-spheres each of radius R/λ.Within each of these a further n spheres of radius Rλ2are added.This continues through L levels;in our simulation we adopt L=9.The amplitude of the correlation function isﬁxed by the number of centres used and the fraction of the total number of points which are retained;these quantities must be determined by trial and error.We measure the variance on the correlation functionfor many subsamples of this catalogue.We start by gen-erating a catalogue covering6.25deg2with the same sur-face density of objects as in our real catalogue at I<25 (corresponding to∼7.5×105galaxies).Next,we mea-sureω(θ)over the full simulated catalogue area.Our aim is to produce a catalogue for which theﬁtted correlation amplitude log(Aω)at I<25is midway between the re-sult of Brainerd&Smail(log(Aω)=−2.93+0.05−0.06)and ourown(log(Aω)=−3.61+0.16−0.26).Once a catalogue with the de-sired correlation amplitude is produced it is randomly sub-sampled to produce200sub-areas each of which has the。

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Gravity and form particle swarm on each particle, which attract more particles, gas ball under appropriate conditions, in the center of the hot, dense enough, can generate burning helium and hydrogen producing stars. Born in the right as the stars in the Eagle nebula.
The formation and early history of the earth
4.6 billion years ago, the primitive earth, dead frozen world, through three effect to gain energy and began to evolution and development. • 1 ° impact effect: interstellar dust high-speed collision, the kinetic energy to heat energy • 2 ° compression effect: interstellar dust landing on the surface, increase external quality, internal squeezed, compression can be converted into heat energy. • 3 ° radioactive decay effect: radioactive elements in the interior of the earth (uranium, thorium, rubidium, etc.). Release huge energy • Evolution results: composition of the molten iron flows to the center of the earth, the formation of iron core, it is a rocky composition form structures (silicate).

高三英语科学前沿单选题30题

高三英语科学前沿单选题30题1.The discovery of a new planet is a major breakthrough in the field of_____.A.astronomyB.biologyC.chemistryD.physics答案：A。

本题考查名词词义辨析。

A 项“astronomy”天文学，发现新行星是天文学领域的重大突破；B 项“biology”生物学，与发现新行星无关；C 项“chemistry”化学，也不符合题意；D 项“physics”物理学，同样不涉及发现新行星。

2.The study of the human brain belongs to the field of_____.A.psychologyB.neuroscienceC.geologyD.mathematics答案：B。

A 项“psychology”心理学，主要研究心理现象；B 项“neuroscience”神经科学，研究人类大脑；C 项“geology”地质学，与大脑无关；D 项“mathematics”数学，也不涉及大脑研究。

3.The development of new materials is an important area in_____.A.engineeringB.literatureC.historyD.art答案：A。

A 项“engineering”工程学，涉及新材料的开发；B 项“literature”文学，不相关；C 项“history”历史，不符合；D 项“art”艺术，与新材料开发无关。

4.The research on climate change is mainly carried out in the field of_____.A.geographyB.economicsC.politicsD.music答案：A。

A 项“geography”地理学，气候变化的研究主要在地理学领域进行；B 项“economics”经济学，与气候变化研究的关系不大；C 项“politics”政治学，不是主要领域；D 项“music”音乐，完全不相关。

外太空的10大奥秘

条评论文：mtarmymanSince the beginning of life, man has looked to the stars with a sense of wonder. Between then and now, many advances have been made in the fields of astronomy, mathematics, and physics in an attempt to explain the things we see above, yet the more we believe we understand, the less we really seem to know. In something as big as the universe, there are bound to be unexplainable phenomena, and things we truly can’t grasp. The universe shows us how small we really are, and in a plac e so big, is it really plausible to believe that we are alone? And is there any reason someone might not want us to know? This is a list of what I believe to be some of the best mysteries and conspiracy theories of outer space.自从有生命开始，人类就怀着好奇心仰望星空。

从那时起到现在，天文、数学和物理等领域取得了许多进展，试图解释我们所看到的头顶上的世界。

但我们越是相信自己懂得的多，我们实际所知道的似乎就越少。

上海市浦东新区2021届高三上学期一模英语试题含解析

D. Because he had to attend a business meeting.
18. A. His flight number and arrival time.
B. The cause of the flight's late arrival.
C. The number of his luggage check.
D. It can create smells and give them off to any scene.
15. A. It helps shoppers locate the right brand of perfume.
B. It helps shoppers check out the perfumes before they buy.
阅读下面短文，在空白处填入1个适当的单词或括号内单词的正确形式。
Since astronomers confirmed the presence of planets beyond our solar system, called exoplanets, humans_________1_________(wonder) how many could harbor life.
Our galaxy holds at least an______4______(estimate) 300 million of these potentially habitable worlds, based on even the most conservative interpretation of the results in a new study to be published in The Astronomical Journal.

the galaxy翻译

the galaxy翻译"the galaxy"可以翻译为"银河系"或"星系"，它是指地球所在的星际空间中的巨大星球系统。

以下是一些关于"the galaxy"的用法和中英文对照例句：1. The galaxy is home to billions of stars and other celestial objects.银河系是亿万颗恒星和其他天体的家园。

2. Our solar system is located in the Milky Way galaxy.我们的太阳系位于银河系中。

3. Astronomers have discovered many exoplanets outside our galaxy.天文学家在我们的银河系外发现了许多系外行星。

4. The Andromeda galaxy is the closest spiral galaxy to the Milky Way.安德洛美达星系是离银河系最近的螺旋星系。

5. The Hubble Space Telescope has captured stunning images of distant galaxies.哈勃太空望远镜捕捉到了遥远星系的惊人图像。

6. Scientists are still studying the formation and evolution ofgalaxies.科学家们仍在研究星系的形成和演化。

7. The galaxy is estimated to be about 13.6 billion years old.银河系估计有大约136亿年的历史。

8. The center of our galaxy contains a supermassive black hole.我们银河系的中心包含一个超大质量黑洞。

有关银河的文章英语

有关银河的英文文章The Milky Way, often referred to as the Galaxy, is a vast and magnificent spiral of stars, dust, gas, and other celestial bodies that we call home. It is named for its appearance in the night sky as a hazy, milky band of light that stretches across the heavens. This ethereal glow is actually the combined light of billions of stars that are too far away to be seen individually. The Milky Way is not just a beautiful sight to behold; it is also a complex and fascinating system that has captivated the minds of astronomers and scientists for centuries.The Milky Way is a barred spiral galaxy, meaning it has a central bar-shaped region with spiral arms extending outward from it. It is enormous, containing an estimated 200 billion stars and spanning a diameter of approximately 100,000 light-years. Our own Sun is just one of these stars, located on the inner edge of one of the spiral arms, about 26,000 light-years from the Galactic Center.One of the most intriguing aspects of the Milky Way is its structure. The galaxy is composed of three main components: the disk, which contains the stars, gas, and dust; the halo, a spherical region that extends beyond the disk and is populated by older stars and globular clusters; and the central bulge, a dense region at the heart of the galaxy that contains mostly older stars.The disk of the Milky Way is where most of the action takes place. It is made up of stars, gas, and dust that are organized into spiral arms. These arms are not solid structures, but rather regions of higher density that are separated by gaps. The arms are home to star-forming regions, where clouds of gas and dust collapse under their own gravity to form new stars. The M ilky Way’s spiral structure is thought to be caused by gravitational interactions between the stars and gas in the disk, as wellas the influence of the central black hole.The halo of the Milky Way is a spherical region that surrounds the disk and extends outward for hundreds of thousands of light-years. It is populated by older stars that are metal-poor and have orbits that take them far away from the plane of the disk. The halo also contains globular clusters, which are tightly packed groups of thousands to millions of stars that orbit the center of the galaxy.At the heart of the Milky Way lies the central bulge, a dense region that is packed with stars. This region is thought to be the site of intense star formation in the early history of the galaxy. It is also home to a supermassive black hole known as Sagittarius A*, which has a mass equivalent to millions of Suns. This black hole exerts a powerful gravitational influence on the surrounding stars and gas, shaping the structure of the galaxy.Studying the Milky Way has been a challenging task for astronomers due to our position within it. We cannot see the galaxy as a whole, as we are embedded within its disk. However, advances in technology and observation techniques have allowed us to piece together a comprehensive picture of our galactic home. We have mapped its structure using radio waves, X-rays, and visible light, revealing the locations of stars, gas, dust, and other components.The Milky Way is not static; it is constantly evolving. New stars are being born in star-forming regions, while older stars are dying and expelling their outer layers into space. The galaxy is also growing through the accretion of smaller galaxies and star clusters. In fact, our own Milky Way is destined to merge with our nearest neighbor, the Andromeda Galaxy, in several billion years.Despite our advances in understanding the Milky Way, there are still many mysteries surrounding it. We do not fully understand how spiral galaxies like our own form and evolve. We also know little about the nature of dark matter, which is thought to make up a significant portion of the mass of the galaxy but has never been directly detected.In conclusion, the Milky Way is more than just a pretty sight in the night sky; it is our home, a vast and complex system that contains billions of stars and countless other celestial bodies. It has captivated the imaginations of people throughout history and continues to inspire awe and wonder in those who gaze upon it. As we continue to explore and study our galactic home, we will undoubtedly uncover more secrets and mysteries that lie hidden within its depths.。

The evolution of clustering and bias in the galaxy distribution

a rXiv:as tr o-ph/98528v115May1998The evolution of clustering and bias in the galaxy distribution B y J.A.Peacock Institute for Astronomy,Royal Observatory,Edinburgh EH93HJ,UK This paper reviews the measurements of galaxy correlations at high redshifts,and discusses how these may be understood in models of hierarchical gravita-tional collapse.The clustering of galaxies at redshift one is much weaker than at present,and this is consistent with the rate of growth of structure expected in an open universe.If Ω=1,this observation would imply that bias increases at high redshift,in conﬂict with observed M/L values for known high-z clusters.At redshift 3,the population of Lyman-limit galaxies displays clustering which is of similar amplitude to that seen today.This is most naturally understood if the Lyman-limit population is a set of rare recently-formed objects.Knowing both the clustering and the abundance of these objects,it is possible to deduce em-pirically the ﬂuctuation spectrum required on scales which cannot be measured today owing to gravitational nonlinearities.Of existing physical models for the ﬂuctuation spectrum,the results are most closely matched by a low-density spa-tially ﬂat universe.This conclusion is reinforced by an empirical analysis of CMB anisotropies,in which the present-day ﬂuctuation spectrum is forced to have the observed form.Open models are strongly disfavoured,leaving ΛCDM as the most successful simple model for structure formation.2J.A.Peacockcommon parameterization for the correlation function in comoving coordinates:ξ(r,z)=[r/r0]−γ(1+z)−(3−γ+ǫ),(1.2) whereǫ=0is stable clustering;ǫ=γ−3is constant comoving clustering;ǫ=γ−1isΩ=1linear-theory evolution.Although this equation is frequently encountered,it is probably not appli-cable to the real world,because most data inhabit the intermediate regime of 1<∼ξ<∼100.Peacock(1997)showed that the expected evolution in this quasilin-ear regime is signiﬁcantly more rapid:up toǫ≃3.(b)General aspects of biasOf course,there are good reasons to expect that the galaxy distribution will not follow that of the dark matter.The main empirical argument in this direction comes from the masses of rich clusters of galaxies.It has long been known that attempts to‘weigh’the universe by multiplying the overall luminosity density by cluster M/L ratios give apparent density parameters in the rangeΩ≃0.2to0.3 (e.g.Carlberg et al.1996).An alternative argument is to use the abundance of rich clusters of galaxies in order to infer the rms fractional density contrast in spheres of radius8h−1Mpc. This calculation has been carried out several diﬀerent ways,with general agree-ment on aﬁgure close to(1.3)σ8≃0.57Ω−0.56m(White,Efstathiou&Frenk1993;Eke,Cole&Frenk1996;Viana&Liddle1996). The observed apparent value ofσ8in,for example,APM galaxies(Maddox,Efs-tathiou&Sutherland1996)is about0.95(ignoring nonlinear corrections,which are small in practice,although this is not obvious in advance).This says that Ω=1needs substantial positive bias,but thatΩ<∼0.4needs anti bias.Although this cluster normalization argument depends on the assumption that the density ﬁeld obeys Gaussian statistics,the result is in reasonable agreement with what is inferred from cluster M/L ratios.What eﬀect does bias have on common statistical measures of clustering such as correlation functions?We could be perverse and assume that the mass and lightﬁelds are completely unrelated.If however we are prepared to make the more sensible assumption that the light density is a nonlinear but local function of the mass density,then there is a very nice result due to Coles(1993):the bias is a monotonic function of scale.Explicitly,if scale-dependent bias is deﬁned asb(r)≡[ξgalaxy(r)/ξmass(r)]1/2,(1.4) then b(r)varies monotonically with scale under rather general assumptions about the densityﬁeld.Furthermore,at large r,the bias will tend to a constant value which is the linear response of the galaxy-formation process.There is certainly empirical evidence that bias in the real universe does work this way.Consider Fig.1,taken from Peacock(1997).This compares dimen-sionless power spectra(∆2(k)=dσ2/d ln k)for IRAS and APM galaxies.The comparison is made in real space,so as to avoid distortions due to peculiar veloc-ities.For IRAS galaxies,the real-space power was obtained from the the projectedThe evolution of galaxy clustering and bias3Figure1.The real-space power spectra of optically-selected APM galaxies(solid circles)and IRAS galaxies(open circles),taken from Peacock(1997).IRAS galaxies show weaker clustering, consistent with their suppression in high-density regions relative to optical galaxies.The relative bias is a monotonic but slowly-varying function of scale.correlation function:Ξ(r)= ∞−∞ξ[(r2+x2)1/2]dx.(1.5)Saunders,Rowan-Robinson&Lawrence(1992)describe how this statistic can be converted to other measures of real-space correlation.For the APM galaxies, Baugh&Efstathiou(1993;1994)deprojected Limber’s equation for the angular correlation function w(θ)(discussed below).These diﬀerent methods yield rather similar power spectra,with a relative bias that is perhaps only about1.2on large scale,increasing to about1.5on small scales.The power-law portion for k>∼0.2h Mpc−1is the clear signature of nonlinear gravitational evolution,and the slow scale-dependence of bias gives encouragement that the galaxy correlations give a good measure of the shape of the underlying massﬂuctuation spectrum.2.Observations of high-redshift clustering(a)Clustering at redshift1At z=0,there is a degeneracy betweenΩand the true normalization of the spectrum.Since the evolution of clustering with redshift depends onΩ,studies at higher redshifts should be capable of breaking this degeneracy.This can be done without using a complete faint redshift survey,by using the angular clustering of aﬂux-limited survey.If the form of the redshift distribution is known,the projection eﬀects can be disentangled in order to estimate the3D clustering at the average redshift of the sample.For small angles,and where the redshift shell being studied is thicker than the scale of any clustering,the spatial and angular4J.A.Peacockcorrelation functions are related by Limber’s equation(e.g.Peebles1980): w(θ)= ∞0y4φ2(y)C(y)dy ∞−∞ξ([x2+y2θ2]1/2,z)dx,(2.1)where y is dimensionless comoving distance(transverse part of the FRW metric is[R(t)y dθ]2),and C(y)=[1−ky2]−1/2;the selection function for radius y is normalized so that y2φ(y)C(y)dy=1.Less well known,but simpler,is the Fourier analogue of this relation:π∆2θ(K)=The evolution of galaxy clustering and bias5 ever,the M/L argument is more powerful since only a single cluster is required, and a complete survey is not necessary.Two particularly good candidates at z≃0.8are described by Clowe et al.(1998);these are clusters where signiﬁcant weak gravitational-lensing distortions are seen,allowing a robust determination of the total cluster mass.The mean V-band M/L in these clusters is230Solar units,which is close to typical values in z=0clusters.However,the comoving V-band luminosity density of the universe is higher at early times than at present by about a factor(1+z)2.5(Lilly et al.1996),so this is equivalent to M/L≃1000, implying an apparent‘Ω’of close to unity.In summary,the known degree of bias today coupled with the moderate evolution in correlation function back to z=1 implies that,forΩ=1,the galaxy distribution at this time would have to consist very nearly of a‘painted-on’pattern that is not accompanied by signiﬁcant mass ﬂuctuations.Such a picture cannot be reconciled with the healthy M/L ratios that are observed in real clusters at these redshifts,and this seems to be a strong argument that we do not live in an Einstein-de Sitter universe.(b)Clustering of Lyman-limit galaxies at redshift3The most exciting recent development in observational studies of galaxy clus-tering is the detection by Steidel et al.(1997)of strong clustering in the popula-tion of Lyman-limit galaxies at z≃3.The evidence takes the form of a redshift histogram binned at∆z=0.04resolution over aﬁeld8.7′×17.6′in extent.For Ω=1and z=3,this probes the densityﬁeld using a cell with dimensionscell=15.4×7.6×15.0[h−1Mpc]3.(2.3) Conveniently,this has a volume equivalent to a sphere of radius7.5h−1Mpc,so it is easy to measure the bias directly by reference to the known value ofσ8.Since the degree of bias is large,redshift-space distortions from coherent infall are small; the cell is also large enough that the distortions of small-scale random velocities at the few hundred km s−1level are also ing the model of equation (11)of Peacock(1997)for the anisotropic redshift-space power spectrum and integrating over the exact anisotropic window function,the above simple volume argument is found to be accurate to a few per cent for reasonable power spectra:σcell≃b(z=3)σ7.5(z=3),(2.4) deﬁning the bias factor at this scale.The results of section1(see also Mo& White1996)suggest that the scale-dependence of bias should be weak.In order to estimateσcell,simulations of synthetic redshift histograms were made,using the method of Poisson-sampled lognormal realizations described by Broadhurst,Taylor&Peacock(1995):using aχ2statistic to quantify the nonuni-formity of the redshift histogram,it appears thatσcell≃0.9is required in order for theﬁeld of Steidel et al.(1997)to be typical.It is then straightforward to ob-tain the bias parameter since,for a present-day correlation functionξ(r)∝r−1.8,σ7.5(z=3)=σ8×[8/7.5]1.8/2×1/4≃0.146,(2.5) implyingb(z=3|Ω=1)≃0.9/0.146≃6.2.(2.6) Steidel et al.(1997)use a rather diﬀerent analysis which concentrates on the highest peak alone,and obtain a minimum bias of6,with a preferred value of8.6J.A.PeacockThey use the Eke et al.(1996)value ofσ8=0.52,which is on the low side of the published range of ingσ8=0.55would lower their preferred b to 7.6.Note that,with both these methods,it is much easier to rule out a low value of b than a high one;given a singleﬁeld,it is possible that a relatively‘quiet’region of space has been sampled,and that much larger spikes remain to be found elsewhere.A more detailed analysis of several furtherﬁelds by Adelberger et al. (1998)in fact yields a biasﬁgure very close to that given above,so theﬁrstﬁeld was apparently not unrepresentative.Having arrived at aﬁgure for bias ifΩ=1,it is easy to translate to other models,sinceσcell is observed,independent of cosmology.For lowΩmodels, the cell volume will increase by a factor[S2k(r)dr]/[S2k(r1)dr1];comparing with present-dayﬂuctuations on this larger scale will tend to increase the bias.How-ever,for lowΩ,two other eﬀects increase the predicted densityﬂuctuation at z=3:the cluster constraint increases the present-dayﬂuctuation by a factor Ω−0.56,and the growth between redshift3and the present will be less than a factor of4.Applying these corrections givesb(z=3|Ω=0.3)The evolution of galaxy clustering and bias7 87GB survey(Loan,Lahav&Wall1997),but these were of only bare signiﬁcance (although,in retrospect,the level of clustering in87GB is consistent with the FIRST measurement).Discussion of the87GB and FIRST results in terms of Limber’s equation has tended to focus on values ofǫin the region of0.Cress et al.(1996)concluded that the w(θ)results were consistent with the PN91 value of r0≃10h−1Mpc(although they were not very speciﬁc aboutǫ).Loan et al.(1997)measured w(1◦)≃0.005for a5-GHz limit of50mJy,and inferred r0≃12h−1Mpc forǫ=0,falling to r0≃9h−1Mpc forǫ=−1.The reason for this strong degeneracy between r0andǫis that r0parame-terizes the z=0clustering,whereas the observations refer to a typical redshift of around unity.This means that r0(z=1)can be inferred quite robustly to be about7.5h−1Mpc,without much dependence on the rate of evolution.Since the strength of clustering for optical galaxies at z=1is known to correspond to the much smaller number of r0≃2h−1Mpc(e.g.Le F`e vre et al.1996),we see that radio galaxies at this redshift have a relative bias parameter of close to 3.The explanation for this high degree of bias is probably similar to that which applies in the case of QSOs:in both cases we are dealing with AGN hosted by rare massive galaxies.3.Formation and bias of high-redshift galaxiesThe challenge now is to ask how these results can be understood in cur-rent models for cosmological structure formation.It is widely believed that the sequence of cosmological structure formation was hierarchical,originating in a density power spectrum with increasingﬂuctuations on small scales.The large-wavelength portion of this spectrum is accessible to observation today through studies of galaxy clustering in the linear and quasilinear regimes.However,non-linear evolution has eﬀectively erased any information on the initial spectrum for wavelengths below about1Mpc.The most sensitive way of measuring the spectrum on smaller scales is via the abundances of high-redshift objects;the amplitude ofﬂuctuations on scales of individual galaxies governs the redshift at which these objectsﬁrst undergo gravitational collapse.The small-scale am-plitude also inﬂuences clustering,since rare early-forming objects are strongly correlated,asﬁrst realized by Kaiser(1984).It is therefore possible to use obser-vations of the abundances and clustering of high-redshift galaxies to estimate the power spectrum on small scales,and the following section summarizes the results of this exercise,as given by Peacock et al.(1998).(a)Press-Schechter apparatusThe standard framework for interpreting the abundances of high-redshift objects in terms of structure-formation models,was outlined by Efstathiou& Rees(1988).The formalism of Press&Schechter(1974)gives a way of calculating the fraction F c of the mass in the universe which has collapsed into objects more massive than some limit M:F c(>M,z)=1−erf δc2σ(M) .(3.1)8J.A.PeacockHere,σ(M)is the rms fractional density contrast obtained byﬁltering the linear-theory densityﬁeld on the required scale.In practice,thisﬁltering is usually performed with a spherical‘top hat’ﬁlter of radius R,with a corresponding mass of4πρb R3/3,whereρb is the background density.The numberδc is the linear-theory critical overdensity,which for a‘top-hat’overdensity undergoing spherical collapse is1.686–virtually independent ofΩ.This form describes numerical simulations very well(see e.g.Ma&Bertschinger1994).The main assumption is that the densityﬁeld obeys Gaussian statistics,which is true in most inﬂationary models.Given some estimate of F c,the numberσ(R)can then be inferred.Note that for rare objects this is a pleasingly robust process:a large error in F c will give only a small error inσ(R),because the abundance is exponentially sensitive toσ.Total masses are of course ill-deﬁned,and a better quantity to use is the velocity dispersion.Virial equilibrium for a halo of mass M and proper radius r demands a circular orbital velocity ofV2c=GMΩ1/2m(1+z c)1/2f 1/6c.(3.3)Here,z c is the redshift of virialization;Ωm is the present value of the matter density parameter;f c is the density contrast at virialization of the newly-collapsed object relative to the background,which is adequately approximated byf c=178/Ω0.6m(z c),(3.4) with only a slight sensitivity to whetherΛis non-zero(Eke,Cole&Frenk1996).For isothermal-sphere haloes,the velocity dispersion isσv=V c/√The evolution of galaxy clustering and bias9 and the more recent estimate of0.025from Tytler et al.(1996),thenΩHIF c=2for the dark halo.A more recent measurement of the velocity width of the Hαemission line in one of these objects gives a dispersion of closer to100km s−1(Pettini,private communication),consistent with the median velocity width for Lyαof140km s−1 measured in similar galaxies in the HDF(Lowenthal et al.1997).Of course,these ﬁgures could underestimate the total velocity dispersion,since they are dominated by emission from the central regions only.For the present,the range of values σv=100to320km s−1will be adopted,and the sensitivity to the assumed velocity will be indicated.In practice,this uncertainty in the velocity does not produce an important uncertainty in the conclusions.(3)Red radio galaxies An especially interesting set of objects are the reddest optical identiﬁcations of1-mJy radio galaxies,for which deep absorption-line spectroscopy has proved that the red colours result from a well-evolved stellar population,with a minimum stellar age of3.5Gyr for53W091at z=1.55(Dun-10J.A.Peacocklop et al.1996;Spinrad et al.1997),and4.0Gyr for53W069at z=1.43(Dunlop 1998;Dey et al.1998).Such ages push the formation era for these galaxies back to extremely high redshifts,and it is of interest to ask what level of small-scale power is needed in order to allow this early formation.Two extremely red galaxies were found at z=1.43and1.55,over an area 1.68×10−3sr,so a minimal comoving density is from one galaxy in this redshift range:N(Ω=1)>∼10−5.87(h−1Mpc)−3.(3.9) Thisﬁgure is comparable to the density of the richest Abell clusters,and is thus in reasonable agreement with the discovery that rich high-redshift clusters appear to contain radio-quiet examples of similarly red galaxies(Dickinson1995).Since the velocity dispersions of these galaxies are not observed,they must be inferred indirectly.This is possible because of the known present-day Faber-Jackson relation for ellipticals.For53W091,the large-aperture absolute magni-tude isM V(z=1.55|Ω=1)≃−21.62−5log10h(3.10) (measured direct in the rest frame).According to Solar-metallicity spectral syn-thesis models,this would be expected to fade by about0.9mag.between z=1.55 and the present,for anΩ=1model of present age14Gyr(note that Bender et al.1996have observed a shift in the zero-point of the M−σv relation out to z=0.37of a consistent size).If we compare these numbers with theσv–M V relation for Coma(m−M=34.3for h=1)taken from Dressler(1984),this predicts velocity dispersions in the rangeσv=222to292km s−1.(3.11) This is a very reasonable range for a giant elliptical,and it adopted in the following analysis.Having established an abundance and an equivalent circular velocity for these galaxies,the treatment of them will diﬀer in one critical way from the Lyman-αand Lyman-limit galaxies.For these,the normal Press-Schechter approach as-sumes the systems under study to be newly born.For the Lyman-αand Lyman-limit galaxies,this may not be a bad approximation,since they are evolving rapidly and/or display high levels of star-formation activity.For the radio galax-ies,conversely,their inactivity suggests that they may have existed as discrete systems at redshifts much higher than z≃1.5.The strategy will therefore be to apply the Press-Schechter machinery at some unknown formation redshift,and see what range of redshift gives a consistent degree of inhomogeneity.4.The small-scaleﬂuctuation spectrum(a)The empirical spectrumFig.2shows theσ(R)data which result from the Press-Schechter analysis, for three cosmologies.Theσ(R)numbers measured at various high redshifts have been translated to z=0using the appropriate linear growth law for density perturbations.The open symbols give the results for the Lyman-limit(largest R)and Lyman-α(smallest R)systems.The approximately horizontal error bars showThe evolution of galaxy clustering and bias11Figure2.Theradius R.Thecircles)Theredshifts2,4,...The horizontal errors correspond to diﬀerent choices for the circular velocities of the dark-matter haloes that host the galaxies.The shaded region at large R gives the results inferred from galaxy clustering.The lines show CDM and MDM predictions,with a large-scale normalization ofσ8=0.55forΩ=1orσ8=1for the low-density models.the eﬀect of the quoted range of velocity dispersions for aﬁxed abundance;the vertical errors show the eﬀect of changing the abundance by a factor2atﬁxed velocity dispersion.The locus implied by the red radio galaxies sits in between. The diﬀerent points show the eﬀects of varying collapse redshift:z c=2,4,...,12 [lowest redshift gives lowestσ(R)].Clearly,collapse redshifts of6–8are favoured12J.A.Peacockfor consistency with the other data on high-redshift galaxies,independent of the-oretical preconceptions and independent of the age of these galaxies.This level of power(σ[R]≃2for R≃1h−1Mpc)is also in very close agreement with the level of power required to produce the observed structure in the Lyman alpha forest(Croft et al.1998),so there is a good case to be made that theﬂuctu-ation spectrum has now been measured in a consistent fashion down to below R≃1h−1Mpc.The shaded region at larger R shows the results deduced from clustering data (Peacock1997).It is clear anΩ=1universe requires the power spectrum at small scales to be higher than would be expected on the basis of an extrapolation from the large-scale spectrum.Depending on assumptions about the scale-dependence of bias,such a‘feature’in the linear spectrum may also be required in order to satisfy the small-scale present-day nonlinear galaxy clustering(Peacock1997). Conversely,for low-density models,the empirical small-scale spectrum appears to match reasonably smoothly onto the large-scale data.Fig.2also compares the empirical data with various physical power spectra.A CDM model(using the transfer function of Bardeen et al.1986)with shape parameterΓ=Ωh=0.25is shown as a reference for all models.This appears to have approximately the correct shape,although it overpredicts the level of small-scale power somewhat in the low-density cases.A better empirical shape is given by MDM withΩh≃0.4andΩν≃0.3.However,this model only makes physical sense in a universe with highΩ,and so it is only shown as the lowest curve in Fig.2c,reproduced from theﬁtting formula of Pogosyan&Starobinsky(1995; see also Ma1996).This curve fails to supply the required small-scale power,by about a factor3inσ;loweringΩνto0.2still leaves a very large discrepancy. This conclusion is in agreement with e.g.Mo&Miralda-Escud´e(1994),Ma& Bertschinger(1994),Ma et al.(1997)and Gardner et al.(1997).All the models in Fig.2assume n=1;in fact,consistency with the COBE results for this choice ofσ8andΩh requires a signiﬁcant tilt forﬂat low-density CDM models,n≃0.9(whereas open CDM models require n substantially above unity).Over the range of scales probed by LSS,changes in n are largely degenerate with changes inΩh,but the small-scale power is more sensitive to tilt than to Ωh.Tilting theΩ=1models is not attractive,since it increases the tendency for model predictions to lie below the data.However,a tilted low-Ωﬂat CDM model would agree moderately well with the data on all scales,with the exception of the ‘bump’around R≃30h−1Mpc.Testing the reality of this feature will therefore be an important task for future generations of redshift survey.(b)Collapse redshifts and ages for red radio galaxiesAre the collapse redshifts inferred above consistent with the age data on the red radio galaxies?First bear in mind that in a hierarchy some of the stars in a galaxy will inevitably form in sub-units before the epoch of collapse.At the time ofﬁnal collapse,the typical stellar age will be some fractionαof the age of the universe at that time:age=t(z obs)−t(z c)+αt(z c).(4.1) We can rule outα=1(i.e.all stars forming in small subunits just after the big bang).For present-day ellipticals,the tight colour-magnitude relation only allows an approximate doubling of the mass through mergers since the termination ofThe evolution of galaxy clustering and bias13Figure3.The age of a galaxy at z=1.5,as a function of its collapse redshift(assuming an instantaneous burst of star formation).The various lines showΩ=1[solid];openΩ=0.3 [dotted];ﬂatΩ=0.3[dashed].In all cases,the present age of the universe is forced to be14 Gyr.star formation(Bower at al.1992).This corresponds toα≃0.3(Peacock1991).A non-zeroαjust corresponds to scaling the collapse redshift asapparent(1+z c)∝(1−α)−2/3,(4.2) since t∝(1+z)−3/2at high redshifts for all cosmologies.For example,a galaxy which collapsed at z=6would have an apparent age corresponding to a collapse redshift of7.9forα=0.3.Converting the ages for the galaxies to an apparent collapse redshift depends on the cosmological model,but particularly on H0.Some of this uncertainty may be circumvented byﬁxing the age of the universe.After all,it is of no interest to ask about formation redshifts in a model with e.g.Ω=1,h=0.7when the whole universe then has an age of only9.5Gyr.IfΩ=1is to be tenable then either h<0.5against all the evidence or there must be an error in the stellar evolution timescale.If the stellar timescales are wrong by aﬁxed factor,then these two possibilities are degenerate.It therefore makes sense to measure galaxy ages only in units of the age of the universe–or,equivalently,to choose freely an apparent Hubble constant which gives the universe an age comparable to that inferred for globular clusters.In this spirit,Fig.3gives apparent ages as a function of eﬀective collapse redshift for models in which the age of the universe is forced to be14 Gyr(e.g.Jimenez et al.1996).This plot shows that the ages of the red radio galaxies are not permitted very much freedom.Formation redshifts in the range6to8predict an age of close to 3.0Gyr forΩ=1,or3.7Gyr for low-density models,irrespective of whetherΛis nonzero.The age-z c relation is ratherﬂat,and this gives a robust estimate of age once we have some idea of z c through the abundance arguments.It is therefore14J.A.Peacockrather satisfying that the ages inferred from matching the rest-frame UV spectra of these galaxies are close to the aboveﬁgures.(c)The global picture of galaxy formationIt is interesting to note that it has been possible to construct a consistent picture which incorporates both the large numbers of star-forming galaxies at z<∼3and the existence of old systems which must have formed at very much larger redshifts.A recent conclusion from the numbers of Lyman-limit galaxies and the star-formation rates seen at z≃1has been that the global history of star formation peaked at z≃2(Madau et al.1996).This leaves open two possibilities for the very old systems:either they are the rare precursors of this process,and form unusually early,or they are a relic of a second peak in activity at higher redshift,such as is commonly invoked for the origin of all spheroidal components. While such a bimodal history of star formation cannot be rejected,the rareness of the red radio galaxies indicates that there is no diﬃculty with the former picture. This can be demonstrated quantitatively by integrating the total amount of star formation at high redshift.According to Madau et al.,The star-formation rate at z=4is˙ρ∗≃107.3h M⊙Gyr−1Mpc−3,(4.3) declining roughly as(1+z)−4.This is probably a underestimate by a factor of at least3,as indicated by suggestions of dust in the Lyman-limit galaxies(Pettini et al.1997),and by the prediction of Pei&Fall(1995),based on high-z element abundances.If we scale by a factor3,and integrate toﬁnd the total density in stars produced at z>6,this yieldsρ∗(z f>6)≃106.2M⊙Mpc−3.(4.4) Since the red mJy galaxies have a density of10−5.87h3Mpc−3and stellar masses of order1011M⊙,there is clearly no conﬂict with the idea that these galaxies are theﬁrst stellar systems of L∗size which form en route to the general era of star and galaxy formation.(d)Predictions for biased clustering at high redshiftsAn interesting aspect of these results is that the level of power on1-Mpc scales is only moderate:σ(1h−1Mpc)≃2.At z≃3,the correspondingﬁgure would have been much lower,making systems like the Lyman-limit galaxies rather rare.For Gaussianﬂuctuations,as assumed in the Press-Schechter analysis,such systems will be expected to display spatial correlations which are strongly biased with respect to the underlying mass.The linear bias parameter depends on the rareness of theﬂuctuation and the rms of the underlyingﬁeld asb=1+ν2−1δc(4.5)(Kaiser1984;Cole&Kaiser1989;Mo&White1996),whereν=δc/σ,andσ2is the fractional mass variance at the redshift of interest.In this analysis,δc=1.686is assumed.Variations in this number of order10 per cent have been suggested by authors who have studied theﬁt of the Press-Schechter model to numerical data.These changes would merely scale b−1by a small amount;the key parameter isν,which is set entirely by the collapsed。

托福听力天文学背景知识

托福听力天文学背景知识英文回答：As an astronomy enthusiast, I have always been fascinated by the wonders of the universe and the vastnessof space. My interest in astronomy began when I was a child.I remember looking up at the night sky and being amazed by the countless stars twinkling above me. I would spend hours reading books about space and learning about the different celestial bodies.One of the most interesting aspects of astronomy is the study of galaxies. Galaxies are massive systems of stars, gas, and dust that are held together by gravity. There are billions of galaxies in the universe, each containingbillions of stars. The Milky Way, which is the galaxy that our solar system is a part of, is just one of many galaxies in the universe.Studying galaxies can provide valuable insights intothe formation and evolution of the universe. Astronomers use various techniques to study galaxies, such as observing their light emissions, measuring their distances, and analyzing their chemical compositions. By studying the properties of galaxies, astronomers can learn about the processes that shape the universe.For example, the study of galaxies has led to the discovery of dark matter and dark energy. Dark matter is a mysterious substance that cannot be directly observed, but its presence can be inferred from its gravitational effects on visible matter. Dark energy, on the other hand, is an even more mysterious force that is responsible for the accelerating expansion of the universe. These discoveries have revolutionized our understanding of the cosmos.中文回答：作为一个天文学爱好者，我一直对宇宙的奇迹和广阔的空间深感着迷。

备考2021高考语法填空+阅读理解题源09：科技文-恒星是如何形成的？

备考2021高考语法填空09How Stars Form in Nearby Galaxies恒星是如何在附近星系形成的导读：Stars are born in dense clouds of molecular hydrogen gas that permeates interstellar space of most galaxies. 恒星诞生于氢气分子稠密云中，而这些氢气分子弥漫在大多数星系星际空间中。

第一部分练习How stars form in galaxies1、____________ （remain）a major open question. Robert Feldmann sheds new light2、____________ this topic with the help of a data-driven re-analysis of observational measurements. Stars are born in dense clouds of molecular hydrogen gas 3、____________ permeates interstellar space of most galaxies. While the physics of star formation is complex, recent years 4、____________ (see) substantial progress towards understanding how stars form in a galactic environment. What 5、____________ (ultimate)determines the level of star formation in galaxies, however, remains an open question.In principle, two main factors influence the star formation activity: the amount of molecular gas that is present in galaxies6、____________ the timescale over7、____________ the gas reservoir is depleted by converting it into stars. While the gas mass of galaxies is regulated by 8、____________ competition between gas inflows, outflows, and gas consumption, the physics of the gas-to-star conversion is currently not well understood. Given its potentially critical role, many efforts 9、____________ (undertake) to determine the gas depletion timescale observationally.However, these efforts resulted in conflicting findings partly because of the challenge in measuring gas 10、____________ (mass) reliably given current detection limits.参考答案：1、remains2、on3、that4、have seen5、ultimately6、and7、which8、a9、have been undertaken10、masses备考2021高考科技类时政新闻阅读题源09第二部分双语阅读TOPICS:Astronomy Astrophysics Stars University Of Zurich 主题：苏黎世大学天文天体物理学之星By UNIVERSITY OF ZURICH JANUARY 3, 2021由苏黎世大学2021年1月3日。

The Asymmetry of Galaxies Physical Morphology for Nearby and High Redshift Galaxies

a r X i v :a s t r o -p h /9907399v 2 5 J a n 2000The Asymmetry of Galaxies:Physical Morphology for Nearby and HighRedshift GalaxiesChristopher J.Conselice,Matthew A.BershadyDepartment of Astronomy,University of Wisconsin,Madison,475N.Charter St.Madison,WI,53706-1582(chris@,mab@)Anna JangrenDepartment of Astronomy and Astrophysics,Pennsylvania State University,525Davey Lab,UniversityPark,PA,16802(jangren@)Subject headings:galaxies:morphology,evolution;galaxies:parameters:asymmetry,color,concentrationABSTRACTWe present a detailed study of rotational asymmetry in galaxies for both morphologicaland physical diagnostic purposes.An unambiguous method for computing asymmetry isdeveloped,robust for both distant and nearby galaxies.By degrading real galaxy images,we test the reliability of this asymmetry measure over a range of observational conditions,e.g.spatial resolution and signal-to-noise (S/N).Compared to previous methods,this new algorithm avoids the ambiguity associated with choosing a center by using a minimization method,and successfully corrects for variations in S/N.There is,however,a strong relationship betweenthe rotational asymmetry and physical resolution (distance at ﬁxed spatial resolution);objects become more symmetric when less well-resolved.We further investigate asymmetry as a function of galactic radius and rotation.We ﬁndthe asymmetry index has a strong radial dependence that diﬀers vastly between Hubble types.As a result,a meaningful asymmetry index must be speciﬁed within a well-deﬁned radiusrepresentative of the physical galaxy scale.We enumerate several viable alternatives,whichexcludes the use of isophotes.Asymmetry as a function of angle (A φ)is also a useful indicator of ellipticity and higher-order azimuthal structure.In general,we show the power of asymmetry as a morphological parameter lies in the strong correlation with (B −V )color for galaxiesundergoing normal star formation,spanning all Hubble types from ellipticals to irregulargalaxies.Interacting galaxies do not fall on this asymmetry-color “ﬁducial sequence,”as these galaxies are too asymmetric for their color.We propose to use this fact to distinguish between ‘normal’galaxies and galaxies undergoing an interaction or merger at high redshift.1.Introduction1.1.Galaxy MorphologyEver since galaxies were recognized as distinct physical systems,one of the main goals in extragalactic astronomy has been to characterize their forms,or morphology,and to determine how this classiﬁcation relates to physical properties.This basic taxonomical process is indeed the basis for any observational science.Theﬁrst attempts at classiﬁcation were on a subjective level,and began with the work of Curtis (1918),Hubble(1926,1936),and Sandage(1961).As more images of galaxies became available,the morphological system developed by Hubble was generally adopted by all astronomers,and later reﬁned by van den Bergh(1960a,1960b)and de Vaucoulers(1959).Other morphological systems were also developed by Morgan(1958)based on the correlation of the physical characteristics of galaxy spectra with the concentration of the light proﬁles.Yet since the time of Hubble’s1926work,the system of morphology for galaxies has changed little.When Hubble developed his original morphological system,his sample consisted of mostly nearby,luminous galaxies,with only3%“irregular”galaxies.These galaxies were not well incorporated in his sequence,but for his purposes,the morphological system developed was adequate for classifying97%of his sample.As deeper galaxy catalogues emerged,however,more and more galaxies fell into the catch-all,“irregular”morphological class.Today,Hubble Space Telescope(HST)imaging reveals that a large fraction of distant galaxies have morphologies that do notﬁt into the the elliptical-spiral Hubble sequence.The Hubble sequence also fails to be useful when classifying galaxies in clusters,with most galaxies classiﬁed as S0or E–classiﬁcations which fail to account of the wide range of cluster galaxy properties(e.g.Koopmann &Kinney1998).Spectral parameters are often more useful in these cases(e.g.Dressler&Gunn1992). Today we classify irregular galaxies not simply in a morphological system,but with regard to the physical mechanisms in operation or the salient physical conditions(e.g.starburst galaxies,interacting galaxies, gas-rich and gas-poor).A morphological classiﬁcation which reﬂects these physical diﬀerences would be a powerful tool for studying the mechanisms driving galaxy evolution.Such studies naturally must include high redshift galaxies.Therefore,a morphological system that encompasses all galaxies,and works sensibly over a wide range in redshift is absolutely essential,but at present does not exist.Recently,new methods of classifying galaxies have been proposed.One line of eﬀort has been to train artiﬁcial neural networks to reproduce the Hubble scheme in an objective way(Burda&Feitzinger1992, Storrie-Lombardi et al.1992,Serra-Ricart et al.1993,Odewahn1995,Naim et al.1995,Odewahn et al. 1996).Spiekermann’s(1992)approach using fuzzy logic was along this line.The number of galaxy images in modern surveys,such as the“Sloan Digital Sky Survey”will be enormous,and hence such automatable methods of morphological classiﬁcation are desirable.However,a Hubble classiﬁcation carries with it the limitations mentioned above;a system that can classify galaxies in a straightforward and quantitative manner that is based on a sound physical and morphological basis would be preferable.Another approach to galaxy classiﬁcation has been to develop sets of quantitative measures of the bulk image structures of galaxies.These methods have the potential to either replace,modify,or improve the current Hubble scheme.The new classiﬁcations generally rely on a set of photometric and/or spectral properties that are internally correlated,and correspond also with the apparent morphology of galaxies. Morgan’s(1958,1959)use of central light concentration was theﬁrst example of such a classiﬁcation. Indeed,the use of concentration indices for inferring the morphology of galaxies has continued to improve, and along with surface-brightness and asymmetry has become one of the major tools for classifying both nearby and distant galaxies(e.g.Okamura,Kodaira,&Watanabe1984;Doi et al.1993;Abraham et al.1994;Jangren et al.1999).A diﬀerent method–applicable for spirals–has been suggested by Elmegreen &Elmegreen(1982):measures of spiral arm morphology,particularly their patchiness,can be used for classiﬁcation.Related attempts to classify galaxies have included the use of principle component analysis of photometric structures(Whitmore1984;Watanabe et al.1985;Han1995).These systems revealed correlations of physical and morphological features of galaxies,but have not been generally adopted for practical use,and the basic Hubble(1926)system still lives on.A key element missing from recent work listed above is the connection made by Morgan between image structure and stellar content(i.e.between light concentration,or central surface-brightness,and spectral type).Ironically,in parallel to the above eﬀorts to quantify image structure,there has been considerable eﬀort to develop quantitative methods of spectral classiﬁcation based on broad-band colors(Bershady1995) and spectra(Connolly et al.1995,Zaritsky et al.1995,Folkes et al.1996,Bromley et al.1998,Ronenet al.1999).What is needed,then,is to go full circle to where Morgan left oﬀ,by tying together the spectral types with the quantitative classiﬁcation based image structure.Here,we propose that using a measure of asymmetry and color for galaxies is a powerful method towards accomplishing this goal.In an accompanying paper(Jangren et al.1999)we explore the additional parameters of size,surface-brightness and image concentration.1.2.Asymmetry as a Physical ClassiﬁerSymmetry has always been one the most basic features and assumptions of most galaxy morphology systems,but also one of the most overlooked for more detailed study.The earliest galaxy morphology papers by Curtis(1918)and Hubble(1926)described galaxies in terms of their symmetry,in most cases a 180◦symmetry.Hubble(1926)describes elliptical and spirals galaxies in their most basic terms as systems “characterized by rotational symmetry about dominating nuclei”.In fact,it is striking how symmetric galaxy systems are,and as we will show,almost always have a minimum asymmetry at a180◦rotation angle.Models of galaxies often assume that the mass distribution of a galaxy is symmetric.Galaxies are, toﬁrst order,dynamically relaxed systems.Understanding how and in what manner the distribution of galaxy light is asymmetric can help reveal dynamical processes in galaxies.For example,galaxies disturbed by interactions or mergers will tend to have large asymmetries.For quite some time there has been considerable eﬀort to characterize the asymmetry in HI gas in spiral galaxies(e.g.Baldwin et al.1980; Richter&Sancisi1994);attempts to do this in optical light are relatively recent(e.g.Rix&Zaritsky 1995;Kornreich,Haynes,&Lovelace1998;Rudnick&Rix1998).While HI-studies beneﬁt directly from kinematic data,optical studies oﬀer complementary information since optical photons predominantly come from stars,which are collisionless,and are believed to trace well the underlying matter distribution in the disk.The quantitative use of asymmetry as a morphological parameter was usedﬁrst by Schade et al.(1995) as a characterization of distant galaxies observed with the Hubble Space Telescope(HST).Further use of symmetry for galaxies in deep HST images has been carried out by Abraham et al.(1996a,1996b)and van den Bergh et al.(1996).These papers,however,use asymmetry only as a crude,type-characterization of distant galaxies in the framework of the Hubble Sequence.Attempts to characterize asymmetry for nearby galaxies,and its usefulness as a morphological parameter within existing frameworks wasﬁrst carried out by Conselice(1997;hereafter C97).In C97it was shown that asymmetry increased with Hubble Type,but with a large spread.Potentially more important was the strong correlation found between color and asymmetry,and a lack of a strong correlation between luminosity and asymmetry for the narrow absolute magnitude of the C97sample.In this paper we investigate further the relationship between asymmetry and other physical parameters, such as color and luminosity,and the usefulness of asymmetry as a morphological parameter.From these results,our expectations are that asymmetry can be incorporated as a pillar of a new classiﬁcation system which better describes and correlates with physical features and parameters than the Hubble sequence.The paper proceeds as follows.The calibration data set of local galaxies used for this study is described in the next section.In§3,we then compare diﬀerent methods for computing asymmetry,and propose a new procedure for measuring asymmetry as a robust quantity.This method includes an iterative scheme forﬁnding the center of rotation(§3.3),a noise correction(§3.4),and a well-deﬁned radius of extraction. We demonstrate how asymmetry changes as a function of both the rotation angle used to compute it(§4.1), and as a function of galactic radius(§4.2).We also discuss the correlation between asymmetry and other physical parameters,i.e.the(B−V)color of a galaxy(§4.3),the Hubble type,and the concentration of light(§4.4).Resolution eﬀects are considered in§5.1.In§4.3we also discuss the causes of asymmetry, concluding that asymmetries are produced by either star formation in spiral arms,or dynamical eﬀects related to interactions with other galaxies.We show these two causes can be distinguished by examining their position in a color-asymmetry diagram.These results are directly applicable to distant galaxies with resolved structure,such as those in the Hubble Deep Field(HDF).2.Calibration Data SetThe data used in this present study are the full set of113galaxies in the Frei et al.(1996)catalog (hereafter referred to as the Frei sample).In contrast,C97was limited to face-on spirals,or ellipticals from the same sample;inclined systems,irregulars and active galaxies were left out.2.1.PhotometryThe current sample under study consists of82galaxies imaged in the B J and R bands(Gullixon et al. 1995),and31in the Gunn g,r,and i bands.The scale for the B J and R images is1.34”per pixel with a ﬁeld of view of7’x11’;for the g,r,and i images the scale was1.19”pixel−1with aﬁeld of view of16’x16’. The g,r,and i images have relatively lower S/N than the B J and R images because of substantially shorter exposures times.In addition to the usual processing(bias subtraction andﬂat-ﬁelding),Frei et al.removed foreground stars.Occasionally,a star that is projected on a bright part of the nucleus was not removed, and causes a false high value for the asymmetry number for those galaxies.For consistency between the above photometric subsets,we use the B−V colors listed in the Third Reference Catalogue of Bright Galaxies(de Vaucouleurs et al.1991,RC3)for purely photometric purposes. (Structural parameters are computed from the images described above.)The adopted B−V colors are observed,i.e.uncorrected for Galactic and internal extinction,and heliocentric velocity(the k-correction). These corrections are small and hence have no qualitative impact on the conclusions of this paper.We adopt the distances and B absolute magnitudes given by Tully(1988).We note,however,that these M B include the above corrections.(A more consistant treatment is presented in Jangren et al.1999.)Theadopted values of M B,B−V,and distance are listed in Tables1and2.2.2.Sample CharacteristicsThe Frei sample includes Hubble types from early ellipticals and S0s,to late-type spirals,irregulars and galaxies with peculiar features.Several of the galaxies in the sample contain features such as rings and bars. Most of the galaxies in the sample are nearby,with a large portion of the ellipticals coming from the Virgo cluster.All of the galaxies were chosen away from the galactic equator and are generally near the Northern Galactic Cap.However,the Frei sample consists only of bright,high surface brightness galaxies.Hence,we are not considering the large population of LSB or dwarf galaxies that make up the bulk of all galaxies in the universe.It is important to realize that the Frei sample is not likely to be an accurate representation of the entire local galaxy population,but only samples a range of Hubble types for the brightest,nearby galaxies.For illustrative purposes,in the remainder of this paper we have selected21galaxiesthat are representative examples of total sample of113used in this study.These21galaxies span of T-types,inclinations and colors.The remaining sample can be viewed at/∼frei/galaxy.3.The Asymmetry AlgorithmThe asymmetry Aφ,whereφis the angle of rotation,is a quantitative parameter based on comparing a source image with its rotated counterpart.In principle Aφis straight-forward and quick to measure in its simplest form.We compare several diﬀerent methods,including those presented by Abraham et al.(1996a; hereafter A96)and C97in the context of aφ=180◦rotation,to determine if they are robust morphological measures over a range of astronomical conditions.On this basis,we develop a more sophisticated approach, ultimately based on the algorithm of A96.3.1.Image PreparationBefore a rotational asymmetry measurement can be made,basic digital image processing must be completed(i.e.bias subtraction,ﬁeldﬂattening,fringe correction,cosmic-ray removal,and bad pixel interpolation).In addition,any objects in the galaxy’s image which are not part of the galaxy,such as foreground stars,or foreground and background galaxies must be removed by blanking the contaminated portion of the images,or subtracting the contaminating source.Contaminating sources tend to be at random locations with respect to the primary source,and hence residuals from this decontamination process will add to the asymmetry depending on their amplitude relative to the source brightness.In the case of unresolved contaminating sources,e.g.stars,the removal is straightforward.Foreground and background galaxies are more diﬃcult to remove or exclude both because of their more complex and extended image structure,and because their identiﬁcation as separate from the primary source can require further information and judgment.This complication becomes particularly important in ultra-deep images such as the HDF,but we do not pursue this further here as it is not an issue for the current study.In addition to any foreground stellar images,the mean background level for each image must becarefully subtracted.This will become clear in the next section where we deﬁne the speciﬁc computational algorithm.A signiﬁcant non-zero background level can radically alter the measured asymmetry value.After a successful background subtraction and object decontamination,however,it is then possible to perform the asymmetry measurement without further image calibration or processing.3.2.Methods of ComputationThe rotational asymmetry measurement procedure consists of(1)deﬁning an image center and “extraction”region;(2)rotating the image about this center by angleφ,and(3)performing a comparison of the resultant rotated image with the original image,within the extracted region.This comparison,however, can have several mathematical forms.In published studies(e.g.C97,A96),the comparison is made by subtracting the rotated image from the original,although in principle the product or ratio might be useful. We have found that only subtraction appears to work well,and discuss only this possible algorithm further. The details of the centering,and choice of rotation angle(§3.3and§4.1respectively)are critical,but do not depend on the mathematical form of the asymmetry algorithm.Once the rotated image is subtracted from the original image,we then have a residual image of all asymmetric features of the galaxy.The asymmetry measurement is completed by measuring the amplitude of the pixel values in the residual image,and normalizing this amplitude by a corresponding measure in the original image.Here again,several mathematical possibilities exist.The method used in C97consists of summing the square of the pixels in the residual image,and normalizing this value by dividing by the sum of the square of the pixels in the original image.Since the pixel values in the residual image will be,on average,half negative and half positive pixel values,half the above ratio gives gives the asymmetry number for that galaxy:Σ(I o−Iφ)2A2rms=.2Σ|I o|Again,the sum is over all pixels within a prescribed,matching region of the original and rotated images. We will call this procedure the“ABS”asymmetry method.For both methods the lowest possible value for the asymmetry parameter is0,while the highest is1.A value of0corresponds to a galaxy that is completely symmetric,that is the diﬀerence(I o−Iφ)=0at all points in the diﬀerence image formed from subtracting the rotated image from the original image.A values of1corresponds to a galaxy that is completely asymmetric such that on average|(I o−Iφ)|=I o.Values for most galaxies lie between these two extremes(see Tables1,2,3,and4forφ=90◦and180◦).Comparing the above two asymmetry computations forφ=180◦rotations,weﬁnd that the values for A abs are similar to the the values found for A rms,as measured in the red.The A abs values have slightlylarger asymmetries at high A as can be seen in Figure1from the positive value of A abs-A rms at large A rms. As a function of wavelength,the RMS asymmetries show a clear trend towards higher diﬀerences in A(blue) -A(red)at larger(red)asymmetries,as seen in Figure2;this can be seen to a lesser extent for the ABS method in Figure3.(Here,‘blue’corresponds either to the B or g bands,and‘red’corresponds to either R or r bands.)The average diﬀerence in A(blue)-A(red)for the RMS method is0.015overall,and0.05at A(red)>0.1.The ABS method yields asymmetries that are fairly constant between bands with an average A(blue)-A(red)of0.005over all asymmetry values.However,weﬁnd the ABS method gives a tighter correlation between asymmetry and color than the RMS method,contrary to our expectations.The RMS method was expected to be a better indicator of star formation since it weights higher the brighter,asymmetric features.The brightness of a star forming region in a galaxy is a function of the density,squared,and hence the RMS method should better trace higher contribution from denser regions of star formation.While either method can be used to get physical information,the better correlation of ABS asymmetries with color lead us to use the ABS method for the remainder of the paper.3.3.Centering CorrectionsOne of the most crucial aspects of the rotational asymmetry computation is the choice of a center of rotation.Centers that diﬀer by only a small amount(relative to a galaxy’s characteristic size)typically produce substantially diﬀerent asymmetry values.For example,a change in the center of rotation by just one pixel for the Frei et al.sample(roughly1%of a half-light radius)can change the value of the asymmetry by as much as50%.However,this becomes less of a problem when the scale of the galaxy becomes smaller, such that as the sampling decreases so does the need for precise centering.To overcome this centering problem,we deﬁne the center of rotation to be the position which yields a minimum value for theφ=180◦asymmetry.Toﬁnd such a center in practice,an initial guess is made for a galaxy’s rotational center.Thisﬁrst step can be automated by choosing the mean,or mode of the light distribution as a reasonable initial guess;our tests indicate that the initial guess does not alter the ﬁnal asymmetry.In most cases,there is a clear central pixel which is approximately in the center of the galaxy,for example,the brightest pixel in the galaxy.For irregular and edge-on galaxies however,there is not a clear-cut brightest point,or even a well deﬁned center,and it is for these galaxies that this method of minimum center is most eﬀective.Operationally,after the asymmetry is computed at that initial position,the asymmetry is computed again for centers at the surrounding eight points in a3×3grid.The distance from the central point to the eight surrounding points can be set at any value.In this work,we use a distance of0.1pixels,corresponding to roughly0.1%of the half-light radius.We use the task’rotate’in IRAF to perfom the asymmetry measurements via bi-linear interpolation.If the asymmetry parameter at the center is lower than the asymmetry value at any of the eight surrounding points,then the asymmetry parameter is taken to be the value at the center.The algorithm eﬀectively creates a synthetic grid of asymmetry values arranged by x,y center positions.If the center pixel does not give the asymmetry minimum,as is usually the case,then the procedure repeats,with the new center the pixel value where the minimum was located.This process continues until a minimum is found for the asymmetry.Once this location is found,we deﬁne this to be the ‘asymmetry centroid’and use that computed asymmetry for the asymmetry parameter of the galaxy.One possible problem with this method ofﬁnding the minimum asymmetry is the existence of localasymmetry minima.We have tested this by computing the asymmetry parameter over a wide range of centers for a set of21representative galaxies from the Frei sample.The second columns of Figures4,5, 6,and7are pictorial representations of the asymmetries values at all pixel locations about the inner3x3 arcsec of these21galaxies.It can be seen in these images that no signiﬁcant local minima exist throughout the image.While the detailed shape of these‘asymmetry planes’diﬀer from galaxy to galaxy(and indeed, contain considerable information about the light distribution)a well-deﬁned minimum exists in each case. In the presence of suﬃcient noise,this condition will break down.We characterize this behavior via simulations in the following section.3.4.Noise CorrectionsThe rotational asymmetry,as deﬁned here,is by its very nature a pixel-by-pixel diﬀerence algorithm, and hence can be substantially aﬀected by noise.Clearly this eﬀect must be accounted for if asymmetry is to be a robust classiﬁer.An example of the eﬀects of noise on the asymmetry value of a galaxy is illustrated in Figure8.The eﬀects of both correlated and uncorrelated noise are relevant.Here,however,we develop a correction for uncorrelated noise and defer handling of correlated noise to a later study on the Hubble Deep Field.The eﬀects of uncorrelated noise in practice are easy to correct by simultaneously performing the asymmetry measurement on both the source and a neighboring,blank area of the image(see A96).The method for computing the asymmetry of the‘blank’area is the same as before,with one exception:there is no normalization by the sum of the original pixels,since in the case of the sky-subtracted background,the sum is zero on average.This procedure is then repeated in a‘centering’grid until a minimum of the noise is found,precisely the same way the minimum asymmetry of the object is found.This‘blank’asymmetry value is then subtracted from the value measured for the object,thereby correcting statistically for theeﬀects of uncorrelated noise present in the object image.Theﬁnal formula used to compute the asymmetrycan be written as:A abs=min[Σ|(I o−Iφ)|Σ|I o|],where I represents the image pixels,and B represents the blank region(background)pixels.Note that the possible range of asymmetry values now spans from0to2.However,due to the application of the minimization condition,the values are rarely ever greater than1,and this primarily occurs whenφ=90◦.When deﬁning a blank region it is necessary to either use an extraction region the same size as the one used on the galaxy,or more practically,scale the sum of the blank region by the relative size of the object to‘blank region’areas.The extraction region used to deﬁne the background should be big enough to be representative,but should be small and distant enough from the galaxy so as to not include any diﬀuse light –and hence gradients–from the sources.Figure8shows the diﬀerences between the computed asymmetry of a galaxy with added noise and the original asymmetry as a function of S/N.It can be seen from this plot that the asymmetry diﬀerences becomes very large at lower S/N.To test how successful our algorithm of removing noise is at eﬀectively reproducing the correct value for the asymmetry parameter,we artiﬁcially degraded the Frei et al.galaxy images by adding simulated, random noise.The noise-corrected asymmetry values measured in these images allowed us to assess the systematic behavior with S/N.We compute the S/N as ratio of the signal from the galaxy within the half-light radius to the noise contribution from the sky,source,and detector read-noise within the same aperture.Results of these S/N tests are shown in Figure9.We use35galaxies from our sample which spanall Hubble types and inclinations to perform these simulations.Weﬁnd that for all these various galaxies, the value of asymmetry parameter found at lower S/N is,on average,still near the values found in the original images.Below S/N∼100,the noise begins to heavily dominate the asymmetry.In this regime,the rotation center yielding the minimum asymmetry(described in Section3.3)is determined largely by the noiseﬁeld. This is compensated in the noise correction since weﬁnd the minimum again for the blankﬁeld where the background correction is calculated.If we did not re-center on the blank region whenﬁnding the background-level asymmetry,this correction would get relatively larger than the galaxy’s asymmetry at successively lower S/N values.As a consequence,the corrected asymmetry would systematically become negative at low S/N values.In our current scheme,we avoid this pit-fall.Even for S/N<100,our simulations show that measured asymmetries have error bars that still overlap with the actual value, although the errors are very large.Errors for images with S/N>500are typically around0.02(rms),while at S/N between100and300have errors around0.05(rms).At S/N<100,the error on the asymmetry become very high,i.e.exceeding0.60(rms)for S/N<50.From Figure9however,we conclude that for all galaxies with S/N values>100their asymmetries can be computed reliably,which we deﬁne to be when the rms errors are less than0.05.A feature of our asymmetry algorithm,which comes naturally from the noise corrections,is an ability to estimate an error on the computed,corrected asymmetries.We have tested this via Monte Carlo methods andﬁnd that these estimates are accurate.14.ResultsThe following presentation is based on the results in Tables1and2,which list the asymmetry values and their estimated errors for the113galaxies in the Lowell and Palomar sample forφ=180◦and90◦, computed within the radius r(η=0.2),and calculated as described in the previous section with centering and noise corrections.The extraction aperture based on theη-function is described in section§4.2.4.1.Asymmetry as a function ofφRotational asymmetry,as we have deﬁned it,has heretofore been explored only in the context of 180◦rotation.However,rotation by other angles can potentially yield more physical and morphological information.In particular,the azimuthal variations of galaxy light proﬁles can be probed,akin to the seminal work of Schweizer(1976a,1976b).While it is not our intent to pursue such a detailed study here, we do show that other angles of rotation can provide diagnostics which allow us to improve upon the utility of the180◦asymmetry correlation with color.4.1.1.180◦Rotation:ﬂocculent and dynamical asymmetriesThe rotation of a galaxy by180◦should yield the minimum rotational asymmetry since most galaxies appear to have a strong azimuthal axi-symmetry.As such,A180is expected to be sensitive both to either。

2023年山西省运城市高考英语模拟试卷+答案解析(附后)

2023年山西省运城市高考英语模拟试卷ANPR's Student Podcast（播客）Challenge is back- for a fifth year!This year's competition will open for entries on January 6，2023 and close on April 28.As in past years，our judges will choose winners in two categories：grades five through eight and grades nine through twelve.Entries must be submitted by an educator or a student leader who's 18 years old or older.Another important rule is that the maximum length of your podcast is within eight minutes，and longer entries will be disqualified.Our judges will use the following criteria to narrow down and choose the winners：Information and structure，40 percentDoes the podcast tell a good story or teach us something new and important？Is it structured in a way that keeps listeners engaged Can we easily follow the story you're telling or the information you're explaining？Have you spent time cutting out unnecessary information to make sure the main ideas come through clearly？Personality and creativity，40 percentDoes it have personality，or does it sound like you' re reading from a script（脚本）？Does it make us laugh or cry or leave us deep in thought？Production，20 percentWe're not judging you on how fancy your equipment is and we don't expect you to be an expert on recording and editing sound，but we hope you'll try.Some podcasts may use a narration（讲述）format.Others may be more of an interview format.If you use sound apart from interviews and narration，make sure it is clear and smooth.1. What is the deadline for handing in your podcast？______A. January 6.B. February 18.C. March 26.D. April 28.2. Who are qualified to submit the podcast to the competition？______A. All monitors.B. Any student.C. Teachers.D. Parents.3. What is a requirement for the entries？______A. They should be more than eight minutes.B. They must be well structured and edited.C. They have to adopt an interview format.D. They must be produced with special sound effects.BOn February 20，the science fiction magazine Clarkesworld was forced to stop accepting any new articles from writers after it was flooded with AI written stories. "By the time we closed on the 20th，we had received 500 human written stories and 700 AI written ones，" said editor-in-chief Neil Clarke. "It was increasing at such a speed that we figured that by the end of the month，we would have doubled the number of articles we normally have.The rate had been growing from previous months，and we were concerned that we had to do something to stop it."Worries about AI misuse have frequently appeared in headlines recently，particularly since the launch of ChatGPT in November，2022，which can not only answer a broad range of questions，but also create original poems and stories. Clarke said magazines like his，which pay contributors for their work，were being targeted by people trying to make quick money.He said he had already spoken to editors of other magazines and that all of them had agreed to stop acceptingAI-written articles.He also admitted that the humor of his sci-fi magazine being targeted by AI robots is not lost on him."You know，our mascot（吉祥物）is a robot.So we see the irony，" he said."But the thing is that science fiction is often intended to give a warning to people.We don't celebrate technology just because it exists.We want to make sure that we're using it right.And there are some significant legal and moral issues around this technology that we're not ready to accept.Clarke said the magazine didn't know how to deal with the issue，and part of the motivation to speak out was in the hope of finding some solutions.He also said the quality of the AI written stories was very poor.4. What's the matter with the magazine Clarkesworld______A. It will close down forever.B. It was targeted by AI writers.C. It stopped paying contributors.D. It has lost many good authors.5. What can we infer about other magazines' attitude to the AI-written stories？______A. Disapproving.B. Favorable.C. Unknown.D. Tolerant.6. What does Neil Clarke say about science fiction？______A. It often intends to find some solutions.B. It welcomes the existing new technologies.C. It will accept AI written stories in the near future.D. It often tries to warn the dark side of technologies.7. Where is this text most likely from？______A. A notice.B. A science fiction.C. A news report.D. A book review.CThe new Webb telescope has discovered what appear to be galaxies（星系）that date back to within 600 million years of the Big Bang.The six newly discovered objects suggest that the early universe may have been developing unexpectedly fast to produce these huge galaxies.While the new telescope has spotted even older gala xies，dating to within 300 million years of the beginning of the universe，it's the size of these six galaxies that shock the researchers."Most galaxies in this era are still small and only gradually growing larger over time，" lead researcher Ivo Labbe of Australia's Swinburne University of Technology said. "But these six galaxies are fast-tracking to maturity.Why this is the case or how this works is unknown."According to the report，which was published in the journal Nature on Wednesday，each of the six objects weighs billions of times more than our sun.In one of them，the total weight of all its stars may be as much as 100 billion times greater than our sun.The PennsyIvania State University's Joel Leja，who also took part in the study，said，"What we found is so unexpected that it actually creates problems for science and it might call the whole picture of early galaxy formation into question."These galaxy observations were among the first set of data from the ＄10 billion Webb telescope，which was just launched over a year ago.Unlike Hubble，the bigger and more powerful Webb can see through clouds of dust with its infrared（红外的）vision and discover galaxies previously undetected.Scientists hope to eventually observe the first stars and galaxies formed following the creation of the universe 13.8 billion years ago.The researchers are still waiting for official confirmation. "It's possible that a few of the objects might not be galaxies，but black holes.One early lesson from Webb is to let go of our expectations and be ready to be surprised，" Labbe said. "Next year it will tell us."8. What is special about the six newly detected objects______A. Their age.B. Their color.C. Their size.D. Their shape.9. What do the underlined words "fast- tracking to maturity" in paragraph 3mean______A. Turning quickly.B. Circling smoothly.C. Travelling fast.D. Growing rapidly.10. What can we learn about the two telescopes？______A. Hubble can see further than Webb.B. Webb is more powerful than Hubble.C. Webb is much cheaper than Hubble.D. Hubble is relatively bigger than Webb.11. What does Ivo Labbe mean in the last paragraph______A. The data might not be complete.B. The researchers will be disappointed.C. He does not agree with Joel Leja.D. The new Webb telescope is unreliable.DDuring the industrial age，when high school was key to the American dream，public -school systems covered the costs of earning a diploma.Today，however，as college degrees have replaced high school diplomas as the ticket into the middle class，families are forced to cover the costs of higher education and more.If the information-age economy demands a workforce with higher education，the US government needs to make the same deal with students and their families：Anyone willing to work hard and earn the degree should be able to attend college- for free. With that basic bargain in mind，Michigan has lately joined Oregon，Rhode Island and Tennessee in experimenting with ways to make community college free.Under the terms of the Chicago Star Scholarship，a program that has already enrolled more than 6，000 students，if a student at a public high school in Michigan maintains a B average，the state will provide a free degree at a local community college.Then，through another program Chicago Star Plus，students who have scored 3.0 GPA are qualified to receive a tuition discount at 18 of the four year colleges located in Michigan.Chicago Star Scholarship and Chicago Star Plus are already changing young lives.Its high school graduation rate grew from 56.9 percent in 2011 to 78.2 percent in 2022.And Chicago Star Plus' college attending rate is 86 percent，well above the national average of 62.7 percent.More than a century ago，America achieved an explosion of social mobility by creating a supportive public school system that runs to 12th grade.By adding community colleges to the nation's public-school systems and educational requirements，we can strengthen the belief in the American dream again.12. What does the author suggest the US government do today______A. Cancel all college students' debts.B. Reduce the costs for the middle class.C. Provide free higher education for qualified students.D. Help poor families to cover the fees of higher education.13. Who can receive the Chicago Star Scholarship？______A. Any student who has achieved 3.0 GPA.B. All public high school students in Michigan.C. All students admitted into the 18 four -year colleges.D. Any Michigan public high schooler who maintains a B average.14. What is the third paragraph mainly about？______A. The significance of the programs in Michigan.B. The high dropout rate in the US colleges.C. The potential costs of Chicago Star Plus.D. The popularization of higher education in the US.15. How is the text mainly developed？______A. By analyzing data.B. By listing examples.C. By making comparisons.D. By conducting surveys.According to Jaime Roberts，good consulting is often about loosening the body，opening the mind and，more often than not，keeping the mouth shut.Your body language mattersJaime Roberts has been one of my go to experts for advice for decades.When I once asked her why she was so good at consulting，she was quick to mention her body language. "（1）______ ，" she said. "Otherwise，they might not open up to me as much as I would want them to.You don't have to fix the problemThat's another thing Jaime Roberts has learned on the job. "People who ask 'What should I do？' often want to process a problem themselves. （2）______ ，" she said. "Part of the trick is remembering that listening is the best thing you have to do，in most cases.，"You don't need to give advice right nowTexts and FaceTime might be immediate，but your advice doesn't have to be. （3）______ . "Forcing yourself to give advice when you can't will do more harm than good，" she said.（4）______ .You're bound to hear about problems you haven't experienced firsthand.That's why Jaime Roberts says you should let them know that you're just human beings with limited experience. （5）______ .A.Don't say their choices are wrongB.You cannot give advice as giving someone an orderC.I try to appear relaxed and avoid looks of shock or judgmentD.You don't need to have the same problem to be a good consultantE.But you should let them know you will do your best to understand themF.You're a good consultant if you can help them fix the problem on their ownG.You can politely explain to them that you will talk to them when you're ready16. A. A B. B C. C D. D E. EF. FG. G17. A. A B. B C. C D. D E. EF. FG. G18. A. A B. B C. C D. D E. EF. FG. G19. A. A B. B C. C D. D E. EF. FG. G20. A. A B. B C. C D. D E. EF. FG. GSujata Halarkar would like to eat fish curry（咖喱）every day.It's a very（1）______ curry with the basic ingredients（原料），nothing very fancy.However，it's a recipe passed down from her （2）______ who is still living in Mumbai，India.Halarnkar now lives in Yuma，Arizona，but she （3）______ in Mumbai，and her grandparents lived in a（n）（4）______ coastal village.Her mother would send her to her grandparents' home for （5）______ .There，her grandma would cook this curry for her."They lived in a neighboring village and I went there almost every week.That is one of the （6）______ memories I had about my childhood，" Halarnkar said. "We had apretty and peaceful beach to ourselves and we would（7）______ fish from the sea every morning.（8）______ later，fish curry is still the comfort food to Halarnkar，who said her family always cooks it when they，（9）______ at weekends in the US."We'll go out to the fish market，buy fresh （10）______ and make this curry，" she said."We don't even worry about vegetables.We just eat some steamed rice and this fish curry."Halarnkar has passed on the （11）______ to her daughter Natasha，who lives in San Diego and shares Halarnkar's love of cooking.And even though the next （12）______ has the recipe，Halarnkar said she still （13）______ the curry her grandma made in India.In fact，she's looking forward to having it next time she goes to （14）______ her."I'm 10% sure that she is going to make it for me when I （15）______ there，" Halarnkar said.21. A. expensive B. extraordinary C. new D.traditional22. A. grandmother B. husband C. aunt D. neighbor23. A. passed away B. settled down C. grew up D. cried out24. A. dangerous B. nearby C. busy D. ugly25. A. parties B. schools C. weekends D. gifts26. A. saddest B. hardest C. strangest D. best27. A. see B. catch C. raise D. save28. A. Days B. Weeks C. Months D. Decades29. A. work B. play C. hunt D. gather30. A. chicken B. fish C. meat D. milk31. A. recipe B. talent C. house D. thought32. A. store B. village C. generation D. guest33. A. avoids B. invents C. hides D. prefers34. A. pay B. hug C. visit D. treat35. A. arrive B. leave C. move D. marry36. China has planted millions of trees in its northwest over the past twodecades as part of its（1）______ （amaze）fight against the expandingdeserts.The effort has paid off.Around 2000，deserts across the country were stillincreasing by 10，400 m2 a year.But in 2017，they were decreasing by more than 2，400 m2 a year.The（2）______ （achieve）was confirmed by a study from the Laboratory of Climate and Environmental Sciences in Paris "In 1999，the Chinese government began planting millions of trees in its Grain for Green Program.It（3）______ （carry）out to repair damaged farmland in northwestern China，（4）______ is roughly the size of France，" says Philppe Ciais，a researcher at the laboratory. "I was there a few months ago，and it is indeed surprising that once bare landscapes are now almost fully covered by plants. ""The growth of forests is significant（5）______ necessary progress in the fight against desertification，" says Jianping Huang，a researcher at Lanzhou University. "But it's still too early to determine whether it has solved the problem.Researchers have found that many of the plant species（6）______ （introduce）to the region use more water（7）______ native vegetation.It could lead to water shortages for humans.The national forestry department has recognized the error.In recent years，it has worked more closely with researchers and communities to find ways to plant less（8）______ （thirst）plants that have economic value."All（9）______ （program）need to take into account local conditions，" the forestry department said in March. "（10）______ （we）efforts should go towards keeping vegetation sustainable，rather than simply planting more trees. "(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)37. 假定你是李华。

关于银河系的资料知识500字作文

关于银河系的资料知识500字作文英文回答：The Milky Way is a barred spiral galaxy in the constellation Sagittarius. It is the second largest galaxy in the Local Group, after the Andromeda Galaxy, and contains approximately 200 billion stars. The Milky Way hasa diameter of about 100,000 light-years and a mass of about1 trillion solar masses. The sun is located about 27,000 light-years from the center of the Milky Way, in one of the galaxy's spiral arms.The Milky Way is divided into several structural components:The bulge: A central region of the galaxy that is dominated by old, red stars.The disk: A flattened region of the galaxy that contains the majority of the galaxy's stars, including thesun.The halo: A spherical region of the galaxy that contains old, metal-poor stars.The Milky Way is surrounded by a number of dwarf galaxies, including the Large and Small Magellanic Clouds. These galaxies are thought to be satellites of the Milky Way.The Milky Way is a very active galaxy. There is a large amount of star formation occurring in the galaxy's spiral arms. The galaxy also has a supermassive black hole at its center. This black hole is called Sagittarius A and has a mass of about 4 million solar masses.The Milky Way is home to a wide variety of astronomical objects, including stars, planets, nebulae, and star clusters. The galaxy is also thought to contain a large amount of dark matter. Dark matter is a mysterious substance that does not emit any light and cannot be directly observed. However, its presence can be inferredfrom its gravitational effects on other objects.The Milky Way is a fascinating galaxy that is still being studied by astronomers. Astronomers are particularly interested in learning more about the galaxy's history, structure, and composition. The Milky Way is also a potential target for future space exploration missions.中文回答：银河系是人马座中的一个棒旋星系。

The CNOC2 Field Galaxy Redshift Survey

a rXiv:as tr o-ph/985131v111May1998The CNOC2Field Galaxy Redshift Survey B y R.G.Carlberg 1,5,6,H.K.C.Yee 1,6,S.L.Morris 2,6,H.Lin 1,6,M.Sawicki 1,6,G.Wirth 3,6,D.Patton 3,6,C.W.Shepherd 1,E.Ellingson 4,6,D.Schade 2,6,C.J.Pritchet 3,&F.D.A.Hartwick 31Department of Astronomy,University of Toronto,2Dominion Astrophysical Observatory,Herzberg Institute of Astrophysics,National Research Council of Canada,3Department of Physics &Astronomy,University of Victoria,4Center for Astrophysics &Space Astronomy,University of Colorado,5Observatories of the Carnegie Institution of Washington,6Visiting Astronomers,Canada–France–Hawaii Telescope,which is operated by the National Research Council of Canada,le Centre National de Recherche Scientiﬁque,and the University of Hawaii.The CNOC2ﬁeld galaxy redshift survey (hereafter CNOC2)is designed to provide measurements of the evolution of galaxies and their clustering over the redshift range 0to 0.7.The sample is spread over four sky patches with a total area of about 1.5square degrees.Here we report preliminary results based on two of the sky patches,and the redshift range of 0.15to 0.55.We ﬁnd that galaxy evolution can be statistically described as nearly pure luminosity evolution of early and intermediate SED types,and nearly pure density evolution of the late SED types.The correlation of blue galaxies relative to red galaxies is similar on large scales but drops by a factor of three on scales less than about 0.3h −1Mpc,approximately the mean scale of virialization.There is a clear,but small,60%,change in clustering with 1.4mag of luminosity.To minimize these population eﬀects in our measurement of clustering evolution,we choose galaxies with M k,e r ≤−20mag as a population whose members are most likely to be conserved with redshift.Remarkably,the evolution of the clustered density in proper co-ordinates at r ∼<10h −1Mpc,ρgg∝r γ0(1+z )3,is best described as a “de-clustering”,∝(1+z )0.6±0.4.Or equivalently,thereis a weak growth of clustering in co-moving co-ordinates,x 0∝(1+z )−0.3±0.2.This conclusion is supported by the pairwise peculiar velocities which rise slightly,but not signiﬁcantly,into the past.The Cosmic Virial Theorem appliedto the CNOC2data gives Q ΩM /b =0.11±0.04,where Q is the three point correlation parameter and b the bias.Similarly,galaxy groups have a virialmass-to-light ratio (evolution corrected)of M virial /L k,e R ≃215h L ⊙/M ⊙,or ΩM =0.15±0.05.2The CNOC2CollaborationFigure1.The distribution on the sky,in seconds of arc,of the galaxies with redshifts and m R≤21.7mag in19of the20ﬁelds in the0223+00patch.clustering dynamics and its relation to galaxy evolution on scales smaller than approximately20h−1Mpc over the0≤z≤0.7range.To meet these goals requires a“CfA-class”survey(Davis&Peebles1983)which contains roughly104 galaxies in106h−3Mpc3to allow subsampling and to provide minimal coverage of a representative set of clustering environments.For observational convenience the survey is distributed over four patches,each nominally containing20 Multi-Object Spectrograph,MOS,(LeF`e vre et al.1994)ﬁelds of approximately 9′×8′on the sky.The layout(minus oneﬁeld)is shown in Figure1.Theﬁelds are observed in the UBgRIﬁlters,with the R(Kron-Cousins) magnitudes(measured as total magnitudes,Yee1991)being used to deﬁne the survey.The photometric sample extends to about m R=24mag,with comparable depths in the otherﬁlters,except for U and I which extend to23mag.The spectroscopic sample is drawn from a“mountain”version ofthe photometric sample with a nominal limit of m R=21.5mag.Eachﬁeldis observed with two spectroscopic masks,the“bright”mask extending tom R≃20mag and the“faint”mask extending to the limiting magnitude.Slits for additional fainter objects are placed in any otherwise unoccupied areas. Together the two masks largely eliminate the problem of slit crowding and have the further beneﬁt of increasing the eﬃciency of the observations.The spectra are band limited with aﬁlter extending from4400-6300˚A,which gives a statistically complete sample over the0.15≤z≤0.55range,with emission line galaxies visible over0≤z≤0.7.The average completeness of the resulting redshift sample relative to the photometric sample is about50%.The success rate for obtaining redshifts from spectra is about85%after accounting for the fraction of objects expected to be outside our passband.The failures are mainly due to poor seeing,poor transparency and objects in the corners of the MOS. The redshift distribution for one patch is shown in Figure2.The results below are derived assuming H0=100h km s−1Mpc−1and q0=0.1.The CNOC2Redshift Survey3Figure2.The line-of-sight distance versus the transverse distance in the Dec direction from theﬁeld centre,in proper co-ordinates,in the0223+00patch.2.Evolution of the Luminosity FunctionThe availability of UBgRI photometry for our sample allows us to classify CNOC2galaxies by colour and to compute the luminosity functions(LF)for diﬀerent galaxy populations in a number of diﬀerent bandpasses.In particular, we give details of our LF methods and descriptions of CNOC2LF evolution results in Lin et al.(1998a),and confront our LF,number count,and colour distribution data against a variety of galaxy evolution models in Lin et al. (1998b).In Lin et al.1998a we calculate LF parameters in the B AB,R,and U bands for“early,”“intermediate,”and“late”CNOC2galaxies,classiﬁed usingﬁts of UBRI colours to the galaxy spectral energy distributions(SED’s)of Coleman, Wu&Weedman1980.We present a description of the LF evolution using the following convenient model,M∗(z)=M∗(0)−Qzα(z)=α(0)ρ(z)=ρ(0)100.4P z,where M∗andαare the usual Schechter LF parameters,ρis the galaxy number density,and P and Q parameterize the rates of number density evolution and luminosity evolution,respectively.We plot our B AB LF results in Figure3and show2σP-Q error contours in Figure4.Weﬁnd that the faint-end slope of the LF is steeper for late-type galaxies relative to early-type objects,consistent with previous LF studies at both intermediate and low redshifts,(e.g.,Lilly et al.1995,Ellis et al.1996,Lin et al.1996a).Moreover,the LF’s of the early and intermediate populations evolve diﬀerently from that of late-type galaxies.4The CNOC2CollaborationFigure3.Evolution of the B AB luminosity functions(solid curves and points)for early-,inter-mediate-,and late-type CNOC2galaxies in three redshift bins(z increases from top to bottom). Also shown areﬁducial LF’s(dotted curves)from the lowest-redshift bin for each galaxy type. Results shown are for q0=0.1.Speciﬁcally,weﬁnd that the LF’s of early and intermediate types show primarily positive luminosity evolution(Q≈1.5)and only modest density evolution (P≈−1),while the late-type LF is bestﬁt by strong positive number density evolution(P≈3)and little luminosity evolution(Q≈0.5).We also conﬁrm the trend seen in previous smaller intermediate-redshift samples that the luminosity density of late-type galaxies increases strongly with redshift,but that the luminosity density of early-type objects remains relatively constant with z. These general conclusions hold for either q0=0.1(as in the LFﬁgures shown) or q0=0.5.Speciﬁc comparisons against the Canada-France(Lilly et al.1995) and Autoﬁb(Ellis et al.1996)redshift surveys show general agreement among our LF evolution results,although there remain some detailed discrepancies with respect to the B-selected Autoﬁb survey,which may be due to diﬀerences in galaxy classiﬁcation or sample selection methods.In Lin et al.1998a we also compute SED type distributions,UBgRI number counts,and various colour distributions for CNOC2galaxies.The number counts and colour distributions for all R<21.5CNOC2galaxies(not just those with redshifts in our completeness range0.1<z<0.55used to compute the LF)are well matched once we extrapolate our LF evolution models toz≈0.75,thus providing additional checks on the validity of our LF evolution results.In addition,we have veriﬁed that various systematic eﬀects,speciﬁcallyThe CNOC2Redshift Survey5Figure4.The two sigma conﬁdence contours in P(number density evolution parameter)versus Q(M∗evolution parameter)for the B AB luminosity functions of early,intermediate,late,and early+intermediate CNOC2samples.The intersection of the horizontal and vertical dotted lines indicates no-evolution,P=Q=0.Results shown are for q0=0.1.patch-to-patch variations,photometric errors,surface brightness selection, redshift incompleteness,and apparent magnitude incompleteness,do not signiﬁcantly aﬀect our results.Subsequent papers on galaxy population evolution in CNOC2will also make use of the morphological and spectral information that will become available for CNOC2galaxies once the appropriate data are fully reduced.We are also in the process of deriving properly calibrated photometric redshifts,which should provide another factor of two increase in useful sample size for R<21.5galaxies. Future papers will further explore the issue of LF evolution using these even larger CNOC2galaxy data sets.3.Two Point CorrelationsOn scales where clustering is strongly nonlinear the two point correlation function is a dynamically useful statistic,which is now fairly well calibratedto initial conditions via n-body simulations(e.g.Jenkins et al.1997).Our survey is suﬃciently densely sampled,with a velocity accuracy of100km s−1 or better,that we normally derive all our results from the two dimensional correlation function,ξ(r p,r z),shown in Figure5,which ratios excess pairs to the smooth background at projected separation r p and redshift separation r z. We estimateξ(r p,r z)with the classical estimator DD/DR−1(Peebles1980), which has the advantage of simplicity and speed.The DD·RR/(DR·DR)−1 and(DD−2DR+RR)/RR estimators lead to no signiﬁcant changes of the results presented here.The real space correlation function can be derived from the projected correlation function,w p(r p)= ξ(6The CNOC2CollaborationFigure5.The two dimensional correlation over the0.15≤z≤0.55range.The plot is sym-metrized about the centre and smoothed with aﬁlter that increases with distance from the origin.The apparentﬂattening of the contours at large distances is not yet statistically signiﬁ-cant.integral extends to inﬁnity w p(r p)/r p=Γ(1/2)Γ((γ−1)/2)/Γ(γ/2)(r0/r p)γ.The immediate complication with this measure ofξ(r)is that when applied to the data the sum needs to be truncated at someﬁnite r z.The minimum r z is that required to sum over the random pairwise velocities along the line of sight,say H(z)r z≥3σ12,or approximately10h−1Mpc.At larger r z the sum converges roughly as1−(r0/r z),that is,relatively slowly.However,increasing the cutoﬀr z beyond about50h−1Mpc increases the noise from large scale structure.The results here use cutoﬀr z of20to50h−1Mpc,andﬁts to the resulting w p(r p) use data with r p≤10h−1Mpc.We make no correction for correlation beyond the cutoﬀr z,which is generally less than10%,even for the unrealistic pure power law correlation model.(a)Luminosity and Colour Dependence of CorrelationsThe auto-correlations of red and blue galaxies(of all luminosities)are shown in Figure6.The sample is split approximately in half at(B−R)0=1.25 which divides the galaxies into those with low and high star formation rate. The resulting subsamples have nearly identical mean redshifts,0.35,but the red subsample has a mean luminosity of M R=−20.5mag as compared to the blue M R=−19.8mag,so there will be some excess of red over blue asa result of luminosity dependent correlation,see Figure7.The blue galaxy auto-correlation has a characteristic scale,roughly0.3h−1Mpc,shortward of which they fall well below red galaxies.A similar trend in the Elliptical/Spiral ratio is reported in the APM(Loveday et al.1995)and CfA+SSRS2survey (Marzke,private communication).A comparison to the pairwise velocity dispersion,approximately350km s−1,and the properties of groups found inThe CNOC2Redshift Survey7Figure6.Auto-correlations as a function of colour.The pincushions are for red galaxies,the circles are for the blue galaxies.The blue galaxies appear to have a characteristic length for correlation change of about0.3h−1Mpc.The errorﬂags are computed from the diﬀerence of the√twoﬁelds and greatly exceed the8The CNOC2CollaborationFigure7.Auto-correlations as a function of luminosity.The pincushions are for M k,eR≤−20 galaxies and the circles for those between−18.5and−20mag.is,very approximately,ξ∝∆(M)−2∝M(n+3)/6,where∆(M)is the massﬁeld variance for spheres containing mass M,which for a perturbation spectrum, P(k)∝k n,is∆∝M−(n+3)/6.For n≃−2expected from CDM-like spectra on galaxy scales,we then expect a correlation amplitude ratio of1.58for the factor of four diﬀerence in luminosity.That is,we attribute the luminosity dependence of the correlation as reﬂecting an underlying primordial diﬀerence in the correlations,roughly as expected for galaxy formation in dark matter potential wells.4.Evolution of the Two Point Correlation FunctionAt low redshift the evolution of galaxy correlations can be adequately described withξ(r,z)=(r0/r)γ(1+z)−(3+ǫ),where the lengths are measured in proper units.This double power law model does not allow any variationof the correlation slope,γ,with redshift.The model might seem theoretically na¨ive,but it is usually a better description of the data than any available non-linear realization of a range of CDM models(Colin,Carlberg&Couchman 1997,Jenkins et al.1997).At low redshiftγ=1.8is the canonical empirical value(Davis&Peebles1983).As redshift increases there are three very general possibilities as,veriﬁed in n-body simulations(Colin,Carlberg&Couchman 1997):•ǫ≃0for particle clustering ifΩM low,•ǫ≃1for particle clustering ifΩM≃1,and,•ǫ≃−1for dark matter halo clustering,with weakΩM dependence.The entire set of n-body particles deﬁnes the evolution of the massﬁeld.Halos with densities of200ρc evolve in numbers as described by the Press-Schechter model(Press&Schechter1974).However these densities are too low to work as a one-to-one association of galaxies inside groups and clusters,althoughThe CNOC2Redshift Survey9Figure8.The BC96model estimated of the speciﬁc star formation rate(multiplied with15Gyr, assuming a duty cycle of unity)versus the model mass for the CNOC2galaxies.Galaxies of low mass and low star formation rate will be below the m R limit of our survey.they may be appropriate for less clusteredﬁeld galaxies.Halo cores at densities well above the virialization density,103−104ρc,remain distinct even in large clusters(Carlberg1994,Ghigna et al.1998)and are the best candidates for identiﬁcation with galaxies in the context of purely collisionless large scale structure simulations.A primary issue in studying the evolution of correlations is to be able to identify the same population at diﬀerent redshifts,since both luminosity and colour dependence of clustering can mimic or mask the desired eﬀect.Although not yet fully implemented,ﬁtting the photometric SED to a model gives an indicative mass-to-light ratio which can then be used estimate galaxy masses,as is shown in Figure8.We use the Bruzual and Charlot(1996)SEDτ=0.5,1, 1.5,2,4and20Gyr models and ages from1to19Gyr in steps of2Gyr.The very blue galaxies require1Gyr old models,which is the cause of the gap in the indicative star formation rate of Figure8.Theﬁtted models give a stellar M/L and a speciﬁc star formation rate,which is multiplied by10Gyr to give an indication of the signiﬁcance of star formation over a Hubble time,assuming that the duty cycle for star formation is100%.There are two indicative results from Figure8which will motivate our sample choice for correlation evolution estimation.First,the galaxy mass function shows no signiﬁcant evolution over our redshift range,although a30%or so variation would be within the limits. Second,there is a clear conﬁrmation of the strong statistical correlation between star formation and the stellar mass of galaxies.High luminosity galaxies,M k,eR ≤−20,are the closer than lower luminositygalaxies to being a certiﬁable mass invariant population,although the bluest members of this set likely have signiﬁcantly lower stellar masses which may10The CNOC2CollaborationFigure9.Estimates of r0andγfor high luminosity galaxies from the LCRS and CNOC2samples. The mean redshift,from top to bottom is0.080,0.135,0.28,and0.43.Contours are68,90and 99%conﬁdence levels.not be well conserved over our redshift range,if their star formation is steady in time.This population has the considerable advantage that an identically deﬁned sample can be found in the LCRS.The high luminosity galaxies withM k,eR ≤−20comprise a volume limited sample within the CNOC2data,andapproximate one within the LCRS sample.Two point correlation parameters,r0andǫ,for a power-law correlation function of the high luminosity galaxies are shown for various redshiftsin Figure9.This redshift sequence isﬁt to correlation evolution model,r0(z)γ=rγ0(1+z)−(3+ǫ),to estimateǫand r0,giving the result shown in Figure10.Weﬁnd that r0=5.15±0.15h−1Mpc andǫ=−0.6±0.4.These data strongly exclude clustering evolution that declines as rapidly as ǫ=1.One could erroneously infer such a rapid decline if one used a sample in which galaxies at higher redshifts are intrinsically less luminous or on the average bluer than those nearby,as is the case for the general population as a function of redshift.The rate of correlation evolution falls between the values expected for lowΩM particles(non-merging)and dark matter halos(which do merge). Our result can be re-stated in terms of the evolution of the correlation length in comoving co-ordinates,x0=r0(1+z)−(3+ǫ−γ)/γ),as x0∝(1+z)−0.3±0.2.It should be borne in mind that our estimate of correlation evolution is a preliminary result and that the errors will be reduced with the full sample. An important consideration is that the luminosity cut that deﬁnes our sample mixes together galaxies of a fairly wide range of masses and anti-correlated star formation rates.It seems likely that low and high star formation rate galaxies have diﬀerent correlation histories,which are mixed in the current approach.5.Galaxy Pairwise Velocities and Their EvolutionThe redshift space distortions inξ(r p,r z)reﬂect the dynamics of clustering. The random velocities elongate contours ofξ(r p,r z)at small r p and infall velocities squash the contours at large r p.These distortions depend onΩ,and the biasing of galaxies with respect to the massﬁeld.The data here have a local velocity accuracy of better than100km s−1,as explicitly demonstratedThe CNOC2Redshift Survey11Figure10.Estimates of r0at z=0andǫfor high luminosity galaxies from the LCRS and CNOC2samples.The result falls between theǫ=0(ﬁxed physical clustering)andǫ=−1.2of clusteringﬁxed in co-moving co-ordinates.Figure11.Theχ2versus model pairwise peculiar velocity,σ12within the LCRS sample(solid line)at a mean redshift0.10and the CNOC2sample(dashed line)at a mean redshift of0.36. using redundant spectra taken through diﬀerent spectrograph slit masks.This is comparable to the velocity accuracy of surveys at low redshift.The CNOC2 survey is designed to concentrate on scales less than10h−1Mpc so will not provide strong limits on the infall velocities.The pairwise peculiar velocities are derived from a model forξ(r p,r z)following the procedures of Croft,Dalton&Efstathiou(1998).Once the r0andγare derived from the velocity independent correlations,then we setΩM=0.2and computeχ2as a function ofσ12.In Figure11we show the reducedχ2versus the pairwise peculiar velocities for the LCRS sample at a mean redshift of0.10 and the CNOC2sample at mean redshift0.36.The minimum ofχ2rises slightly with redshift,although it is consistent with no change with redshift.Theǫmodel for clustering predicts with the Cosmic Virial Theorem(see below)that σ12(z)∝(1+z)−ǫ/2,provided that the bias is not changing with redshift.We conclude that the peculiar velocities evolve in accord with that predicted from the correlation function alone.This is strong evidence that biasing of galaxies with respect to dark matter is not a large eﬀect at these redshifts.The peculiar velocities also show a strong population dependence,as shown in Figure12.The red galaxies have a pairwise dispersion of about350km s−1, whereas the blue galaxies have a measured dispersion of about200km s−1.12The CNOC2CollaborationFigure 12.The χ2versus model pairwise peculiar velocity,σ12for the red (solid line)and blue galaxies (dashed line)within the CNOC2sample.There is between 70and 100km s −1added in quadrature with the true velocities.Removing the velocity errors in quadrature would reduce the pairwise velocities of blue galaxies to about 150km s −1,which is a remarkably cold population.One can speculate that in as much as accretion is necessary to promote ongoing star formation,then star formation should be suppressed in regions of strongtidalﬁelds (the groups)and promoted in moderately dense regions of low velocity dispersion.A plot of the estimated star formation rate versus local phase density indicates a weak,but suggestive correlation.The cosmic virial theorem (CVT)estimates the value of ΩM in the ﬁeld (Davis &Peebles 1983)and is an important complement to studies of clusters as ΩM indicators.For a power law ξ(r ),the CVT readsQ ΩM (1+z )3r γ0r 2−γH 204(γ−1)(2−γ)(4−γ)The CNOC2Redshift Survey13Figure13.The number of groups found as a function of their line of sight(rest frame)velocity dispersion.The groups are selected from a volume of about2×105h−3Mpc3.Below100km s−1 there are few groups due to our velocity measurement error.•the relation between clustering and galaxy properties can be investigated. The highly nontrivial problem is to identify groups using redshift space data.We adopt a simple algorithm.We ratio the number of(selection function weighted) galaxies within a“window”to those in a random sample,as for the correlation function,to measure the redshift space density at the location of every galaxy. The window is generally0.5h−1Mpc in radius and±600km s−1in the redshift space direction.We then select from this list the galaxy with the highest overdensity and join to it all galaxies within a second,slightly larger window, 1200km s−1and0.8h−1Mpc.The sole output from this operation is an estimate of the location of the centre of the group in RA,Dec and z.The resulting centre has quite a weak dependence on the details of the windows provided they are not so small that groups are overlooked,or,that they are so big that hugeﬂuﬀy regions are selected as groups.The velocity cutoﬀis about three times the pairwise velocity dispersion.The cutoﬀin projected radius is20-30% of the correlation length,approximately the radius at which the redshift space correlation function,ξ(s),bends due to random velocities.Our estimated centre is then given to an algorithm which estimates the velocity dispersion,mass and total luminosity from galaxies within some aperture,usually0.4h−1Mpc and 900km s−1.These values are not particularly crucial,since neither the projected velocity dispersion nor the inferred M/L has a measurable radial gradient.The groups are shown in Figure13as a function of their line of sight velocity dispersion.Although these groups should have only a small population bias to estimate the global M/L,but they need to be calibrated against n-body data if their cosmological number densities are to be compared to Press-Schechter predictions.The comforting news from thisﬁgure is that there is no evidence for many high velocity dispersion groups which are likely to be bogus.If anything, it is likely that the∼10%of galaxies assigned to groups here means that we are missing some genuine groups.The virial mass-to-light ratio of the groups with six or more members is shown as a function of velocity dispersion in Figure14.The groups as a whole have a mean mass-to-light of about215h M⊙/L⊙,and the groups as individuals appear to be nearly consistent with having the same value.On the other hand,there14The CNOC2CollaborationFigure14.The group mass-to-light ratio as a function of velocity dispersion for groups with six or more members.The drop in M/L at small velocity dispersion may be a result of correlated errors in both axes,however it could have an origin in dynamical friction.Figure15.Group luminosity plotted against mass.These quantities are not intrinsically corre-lated by the measurement.The solid line is the average group M/L=215h M⊙/L⊙and the dashed line is for the population adjusted rich cluster M/L=300h M⊙/L⊙.The more massive groups appear to be consistent with clusters,but the smaller ones appear to have lower M/L values.is an indication that lower velocity dispersion groups have lower M/L values. The two axes in Figure14are statistically correlated,therefore we plot the mathematically independent quantities of group luminosity versus virial mass in Figure15.The more massive(or equivalently,higher velocity dispersion)groups have M/L values consistent with the mean value of300h M⊙/L⊙for CNOC1 clusters,after adjusting0.12mag to account for population diﬀerences and the slightly diﬀerent luminosity scales.An indication that lower luminosity groups are“under-massive”is still apparent in Figure15.This is perhaps not too surprising because there must be a scale at which the M/L characteristic of the meanﬁeld,300h M⊙/L⊙or so,drops into the“linear rise”regime characteristic of individual isolated galaxies(Zaritsky&White1994).The CNOC2Redshift Survey15Figure16.The mean surface density of the groups(arbitrary units)versus radius.The ratio of red(dashed)to blue(dotted)galaxies increases towards the centre.The solid line is for all galaxies.7.Internal Properties of GroupsThe cosmic virial theorem uses pairwise statistics,so itsΩM is dependent on a knowledge of the bias of the tracer galaxies relative to the massﬁeld.On the other hand,if the single particle velocity distribution can be found it allows the massﬁeld to be derived independently of the distribution of the tracer galaxies. Galaxy groups provided that opportunity,since the velocities can be measured with respect to the group mean velocity.This means that we can put limits on the bias of galaxies with respect to the massﬁeld on scales of about0.5h−1Mpc and less.We use the groups whose local centers indicated velocity dispersions more than150km s−1and had six or more members.The following analysis uses the group mean center(where there is usually no galaxy so the density reaches a plateau)and includes all galaxies within600km s−1in the frame of the group.Jeans Equation allows the massﬁeld,M(R)= ρ(r)dV,to derived from a tracer population,ν(r),which must be eﬀectively in equilibrium,but not necessarily distributed like the mass,M(r)=−σ2r rd ln r+d lnν16The CNOC2CollaborationFigure17.The projected velocity dispersion versus radius in the groups.Blue galaxies(dotted) have systematically higher velocity dispersions than the red galaxies(dashed),which are similar to the full sample(solid).This is quite distinct from the pairwise velocities,in which blue galaxies have signiﬁcantly lower velocities than red galaxies.This helps one to understand why the virial masses given by blue galaxies are about50%higher than the full sample.Red galaxies give virial masses that are98%of the full sample result.We take these surface density and velocity dispersion proﬁles as tentative evidence that the full galaxy distribution and the mass distribution in groups are similar.Within groups,blue galaxies are“anti-biased”with respect to the red galaxies and likely the mass as well.Although these results are both preliminary and clearly subject to statistical uncertainties,they would support the notion that these groups are in many ways dynamically similar to rich clusters although they do not have such extreme population diﬀerences as rich clusters and theﬁeld.These issues are a major area of investigation in the CNOC2survey.8.Ultra-Large Scale PowerMeasuring the power spectrum on scales of100-500h−1Mpc,roughly the scale of the“ﬁrst Doppler peak”in the CMBﬂuctuation spectrum,requires a survey that covers an appreciable fraction of the visible universe.Pencil beam surveys do just that,but only in one dimension which leads to the problem of aliasing in of shorter scale power into the derived1D power spectrum,P1(k).In view of previous results(Broadhurst et al.1990)and the fundamental interest in this statistic we measure the one dimensional power spectrum from the CNOC2data and compare it to various simple models.The one dimensional power spectrum P1(k)=|N−1 N i=1exp[ikx i]|2 (unweighted)is shown as the upper irregular line in Figure18.At very large k z this tends to1/N where N≃1500in each of our patches.The observed1D spectrum requires some care in interpretation since the1D power at a large wavenumber is an integral over the entire3D spectrum(Kaiser&Peacock1991) whose analysis we follow here.The1D power spectrum of the smooth n(z)is the W(k z)window function and is shown as the lower irregular line.Clearly the power at k z<0.01h−1Mpc−1is completely dominated by the smooth。

大众天文学英文版

大众天文学英文版English: Popular astronomy refers to the study and observation of celestial bodies and phenomena by amateur astronomers and the general public. It covers a wide range of topics such as stargazing, planetary exploration, telescope usage, and understanding the universe's mysteries. Through popular astronomy, people of all ages and backgrounds can develop a fascination with the cosmos and gain a deeper appreciation for the beauty and complexity of the universe. Many amateur astronomers contribute valuable observations and data to professional astronomers, helping to advance scientific knowledge and discovery in the field of astronomy. Popular astronomy also plays a crucial role in promoting science education and literacy, inspiring future generations to pursue careers in STEM fields. Overall, it serves as a bridge between the scientific community and the general public, fostering a sense of wonder and curiosity about the vast expanse of space beyond our planet.中文翻译: 大众天文学指的是业余天文爱好者和普通大众对天体和现象进行研究和观测的活动。

Detection of Weak Lensing in the Fields of Luminous Radiosources

a r X i v :a s t r o -p h /9507076v 1 20 J u l 1995A&A manuscript no.(will be inserted by handlater)2 B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous Radiosourcesous galaxy clumps distributed in the Large Scale Struc-tures of the Universe(hereafter LSS)if a substantial frac-tion of them have almost the critical surface mass den-sity.In fact,the excess of QSOs and radiosources around the Zwicky,the Abell and the ROSAT clusters reported recently(BSH94,SS95c)already supports the idea that cluster-like structures may play a signiﬁcant role in mag-nifying a fraction of bright quasars.If this hypothesis is true these massive,not yet detected deﬂectors in visible could show up through their weak lensing eﬀects on the background galaxies.The gravitational weak lensing analysis has recently proved to be a promising technique to map the pro-jected mass around clusters of galaxies(KS93,BMF94, FKSW94,SEF94).Far from the centers of such mass condensations,background galaxies are weakly stretched perpendicular to the gradient of the gravitationalﬁeld. With the high surface density of background galaxies up to V=27.5(≈43faint sources per square arcminute with V>25)the local shear(or polarization of the images)can be recovered from the measurement of the image distor-tion of weakly lensed background galaxies averaged over a sky aperture with typical radius of30arcsec.The implicit assumption that the magniﬁcation matrix is constant on the scanning aperture is not always valid and this obser-vational limitation will be discussed laterThe shear technique was also used with success to de-tect large unknown deﬂectors in front of the doubly im-aged quasar Q2345+007(BFK+93).This QSO pair has an abnormally high angular separation,though no strong galaxy lens is visible in its neighbourhood.The shear pat-tern revealed the presence of a cluster mass oﬀcentered at one arcminute north-east from the double quasar,which contributes to the large angular separation.Further ultra-deep photometric observations in the visible and the near infrared have a posteriori conﬁrmed the presence of the cluster centered on the center of the shear pattern and detected a small associated clump of galaxies as well,just on the QSO line of sight.Both lensing agent are at a red-shift larger than0.7(MDFFB94,FTBG94,PMLB+95). The predicting capability of the weak lensing was quite remarkable since it a priori provided a better signature of the presence of a distant cluster than the actual over-density of galaxies,which in the case of Q2345+007was almost undectable without a deep”multicolor”analysis.On a theoretical side,numerical simulations in stan-dard adhesion HDM or CDM models(BS92a)can predict the occurrence of quasar magniﬁcation.They have shown that the large magniﬁcations are correlated with the high-est amplitudes of the shear,which intuitively means that the largest weak lensing magniﬁcations are in the immedi-ate vicinity of dense mass condensations.For serendipity ﬁelds they found from their simulations that at least6%of background sources should have a shear larger than5%. However,for a subsample of rather bright radiosources or QSOs the probability should be larger,so that we can reasonably expect quasarﬁelds with a shear pattern above the detection level.Since we can detect shear as faint as3%(BMF94), both observational and theoretical arguments convince us to start a survey of the presence of weak shear around sev-eral bright radiosources.In practice,mapping the shear re-quires exceptional subarcsecond seeing(<0.8arcsec.)and long exposure times,typically4hours in V with a four meter class telescope.Observations of a large unbiased selected sample of QSOs will demand several years and before promoting the idea of a large survey we decided to probe a few bright QSOﬁelds where a magniﬁcation bias is more likely.In this paper,we report on a preliminary tests at CFHT and ESO ofﬁve sources at z≈1.The analysis of the shape parameters and the shear is based on the?bon-net95technical paper,with some improvements to mea-sure very weak ellipticities.Due to instrumental diﬃculties only one,Q1622+238,was observed at CFHT.Neverthe-less,we found a strong shear pattern in the immediate vicinity of the quasar quite similar to the shear detected in the QSO lens Q2345+007(BFK+93).The QSO is mag-niﬁed by a previously unknown distant cluster of galax-ies.The four other QSOs were observed with the imaging camera SUSI at the NTT with a signiﬁcantly lower instru-mental distortion but with a smallerﬁeld of view.In this case the limited size of the camera makes the mapping of strong deﬂector like in Q1622+238harder.However, with the high image quality of SUSI it is possible to see on the images a clear correlation between the amplitude and direction of the shear and the presence of foreground overdensities of galaxies.Some of them are responsible for a magniﬁcation bias of the QSO.By comparing the preliminary observations at CFHT and ESO we discuss important observational issues, namely the need for a perfect control of image quality and a largeﬁeld of view.We also show that invisible masses as-sociated with groups and poor clusters of galaxies can be seen through their weak lensing eﬀect with NTT at ESO. These groups of galaxies may explain the origin of a large angular correlation between the distribution of distant ra-diosources(z>1)and the distribution of low redshift galaxies(z<0.3)The study of the correlation between the local shear and nearby overdensity of foreground galaxies (masses)will be investigated in following papers after new spectrophotometric observations of the lensing groups. 2.Selection and observations of the sourcesThe double magniﬁcation bias hypothesis maximises the probability of a lensing eﬀect for luminous distant sources (BvR91).Therefore whenever possible we try to select sources that are both bright in radio(F>2Jy,V<18). We also looked at quasars with absorption lines at lower redshift,to know if some intervening matter on the lines of sight is present.The QSOs are chosen at nearly theB.Fort et al.:Detection of Weak Lensing in the Fields of Luminous Radiosources3 objectα50δ50m V zﬂux Tel./Instr.exp.numb.seeingtimeﬁles(arcsec.)Table1.Observational data for the5QSOsﬁelds.The V magnitude stars.The radioﬂux is the5009MHz value from the 1Jy catalogue.The total exposure time corresponds to the coaddition of several individual images with30-45minutes exposure time.The seeing is the FWHM of stars on the composite imagemean redshift of the faint background galaxies(z from0.8to1.)used as an optical template to map the shear offoreground deﬂectors.So far,we have observed5QSOs atredshift about1with a V magnitude and radioﬂux in therange from17to19and1.7to3.85respectively(Table1).Except Q1622+238(z=0.97)which was suspected tohave a faint group of galaxies nearby(HRV91),the4othercandidates(PKS0135-247,PKS1508-05,PKS1741-03,and3C446.0)have been only selected from the?hewitt87,andthe?veronveron85catalogues,choosing those objects withgood visibility during the observing runs.The V magni-tude of each QSO was determined with an accuracy betterthan0.05mag.rms from faint?landolt92calibration stars(Table1).The observations started simultaneously in June1994at the ESO/NTT with SUSI and at CFHT with FOCAM,both with excellent seeing conditions(<0.8”)and stabletransparency.For the second run at ESO in November1994,only one of the two nights has good seeing condi-tions for the observation of PKS0135-247.We used the1024×1024TeK and the2048×2048LORAL CCDs with15micron pixel,which correspond to0.13”/pixel at theNTT and0.205”/pixel at CFHT,and typicalﬁelds of viewof2’and7’respectively.In both cases we used a standardshift and add observing technique with30to45min expo-sures.The resultingﬁeld of view is given in table2.The total exposure was between16500and23700seconds in V(Table1).The focusing was carefully checked between each individual exposure.After prereduction of the data with the IRAF software package,all frames were coadded leading to a composite image with an eﬀective seeing of 0.78”at CFHT and0.66”-0.78”at NTT(Table1).Al-though the seeing was good at CFHT we are faced with a major diﬃculty when trying to get a point spread function for stars(seeing disk)with small anisotropic deviations from circularity less than b/a=0.05in every direction). This limitation on the measurement of the weak shear am-plitude will be discussed more explicitly in the following section.3.Measurement of the shearThe measurements of the shear patterns have been ob-tained from an average of the centered second order mo-Fig. 2.Histogram of the independent measurements of the axis ratio b/a in all theﬁelds with a scanning aperture of30 arcsec.radius.The peak around0.99is representative of the noise level that deﬁnes a threshold of amplitude detection near 0.985.menta as computed by Bonnet and Mellier(1995)of all individual galaxies in a square aperture(scanning aper-ture size:57+3/-5arcsec.)containing at least25faint galaxies with V between25and27.5(Table2).Because very elongated objects increase the dispersion of the mea-surement of the averaged shape parameters(see Bonnet and Mellier1995,Fig.4),and blended galaxies give wrong ellipticities,we rejected these objects from the samples. The direction of the polarization of background galaxies is plotted on each QSOﬁeld(Figures3b,3d,4b,5b,6b) at the barycentre of the25background galaxies that are used to calculate the averaged shear.Each plot has the4 B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous RadiosourcesFig.1.Figure1a:NTT Field of view of PKS1741which was used as a star template to study the instrumental distortion of the SUSI camera.Figure2b:plot of the apparent residual”shear amplitude”of the stars on5points of theﬁeld where the galaxy shears are determined in other NTT images;ﬁgures4,5,6same amplitude scale for comparison between images and the instrumental distortion found from a starﬁeld anal-ysis(Figure1b).This explains why the mapping is not rigorously made with a regular step between each polar-ization vector on theﬁgures.The small step variation re-ﬂects the inhomogeneity of the distribution of background sources.For the exceptional shear pattern of Q1622+238, a plot with a smaller sampling in boxes of22arcsec.gives a good view of the coherence of the shear(Figure3b).All other maps are given with a one arcminute box,includ-ingﬁgure3d,so that each measurement of the shear is completely independent.For quantitative study the coor-dinates of each measurement are given on table3with the value of the apparent amplitude1−b/a and the direction of the shear.The ellipticity e=1−b/a given in Table3 is drawn on the variousﬁelds with the same scale.A description of the technique used to map the shear can be found in?bonnet95.We have only improved when necessary the method to correct the instrumental distor-tion in order to detect apparent shear on the CCD images down to a level of about2.0%(Figure2).Notice that we call here”apparent shear”the observed shear on the im-age which is not corrected for seeing eﬀects and which is averaged within the scanning aperture.To achieve this goal we observed at NTT,in similar conditions as other radiosources,theﬁeld of PKS1741-03which contains ap-proximately26±6stars per square arcminute(Figure 1a,b).After a mapping of the instrumental distortion of stars we have seen that prior to applying the original?bon-net95method,it is possible to restore an ideal circular see-ing disk with a gaussian distribution of energy for stars in theﬁeld(pseudo deconvolution).The correction almost gives conservation of the seeing eﬀective radius with:s=√B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous Radiosources5ture(Figure1b).However we verify with the PKS1741-03ﬁeld that the restoration of the circularity of the spread function can give a residual”polarization”of stars in the ﬁeld as low as1−<b/a>=0.0009±0.0048(dispersion).In fact the restoration of the point spread function ap-peared to be more diﬃcult with CFHT images because of a higher level of instrumental distortion whose origin is not yet completely determined:guiding errors,atmospheric dispersion,larger mechanicalﬂexure of a non-azimuthal telescope,3Hz natural oscillation of the telescope(P. Couturier,private communication),optical caustic of the parabolic mirror,and indeed greater diﬃculties in getting excellent image quality on a largerﬁeld.Thus,the level of instrumental distortion measured on stars is currently 1−<b/a>=0.08-0.12with complex deviations from a circular shape.After the restoration of an ideal seeing spread function we are able to bring the shear accuracy of CFHT images to a level of0.03.But like the classical measurement of light polarization it should be far better to start the observations with a level of instrumental po-larization as low as possible.In summary we are now able to reach the intrinsic lim-itation of Bonnet&Mellier’s method on the measurement of the shear amplitude at NTT with a typical resolution of about60arcsec.diameter(25-30faint galaxies per res-olution element)with a rms error of about0.015(Figure 2).Below this value the determination of the amplitude of the shear is meaningless although the direction may still be valid.At CFHT the detectivity is almost two times less but theﬁeld is larger.We are currently developing meth-ods to correct the instrumental distortion at the same level we get with the NTT.This eﬀort is necessary for future programmes with the VLT which would be aimed toward the mapping of Large Scale Structures(shear of0.01)witha lower spatial resolution(>10arcminute apertures).4.ResultsIn this section we discuss the signiﬁcance of the shear pat-tern in each QSOﬁeld and the eventual correlation with the isopleth or isodensity curves of background galaxies with20<V<24.5.For a fair comparison both the iso-pleth(surface density numbers)or isoluminosity curves (isopleth weighted by individual luminosity)are smoothed with a gaussianﬁlter having nearly the resolution of the shear map(40”FWHM).1.Q1622+238A coherent and nearly elliptical shear pattern is de-tected with an apparent amplitude0.025±0.015at a distance ranging from50”to105”of the QSO(Figure 3b).The center of the shear can be calculated with the centering algorithm described by Bonnet&Mel-lier.The inner ellipses inﬁgure3b show the position of the center at the1,2and3σconﬁdence level.It co-incides with a cluster of galaxies identiﬁed on the deepV image10arcsec South-East from the QSO(Figure 3c).The external contour of the isopleth map inﬁg-ures3c corresponds to a density excess of galaxies of twice the averaged values on theﬁeld for a30arc-sec circular aperture.The isoluminosity map shows a light concentration even more compact than the num-ber density map.About70%of the galaxies of the condensation have a narrow magnitude range between V=24and24.5and are concentrated around a bright galaxy with V=21.22±0.02.This is typical for a clus-ter of galaxies.A short exposure in the I band gives a corresponding magnitude I=19.3±0.1for the bright central galaxy.A simple use of the magnitude-redshift relationship from a Hubble diagramme and the(V−I) colors of the galaxy suggest a redshift larger than0.5.By assuming such a redshiftObjectﬁeld Ng/N G Mag(pixels)/(arcsec.)range Table2.Table2:Number Ng of(background)galaxies from V=22to24.5which are used to trace isopleth and number N G of(distant)galaxies from V=25to27.5.detected on each observedﬁeldit is possible to mimic the shear map with a deﬂec-tor velocity dispersion of at least500km/sec.Aftera correction for the seeing eﬀect with the?bonnet95diagram and taking into account the local shear of the lens at the exact location of the QSO we can estimate that the magniﬁcation bias could be exceptionally high in this case(>0.75magnitude).Further spectropho-tometric observations of theﬁeld are needed to get a better description of the lens.It is even possible that multiply imaged galaxies are present at the center of this newly discovered cluster.2.PKS1741-03Thisﬁrst NTTﬁeld was chosen for a dedicated study of the instrumental distortion of the SUSI instrument.Indeed it is crowded with stars and the mapping of the isopleth was not done due to large areas of the sky occulted by bright stars.The center of theﬁeld of PKS1741-03shows a faint compact group of galaxies(marked g onﬁg1a).A de-tailed investigation of the alignment of individual faint galaxies nearby shows that a few have almost orthora-dial orientation to the center of the group.The ampli-tude of the”apparent”shear on theﬁg1b is low prob-ably because it rotates within the scanning aperture around a deﬂector having an equivalent velocity dis-6 B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous RadiosourcesFig.3.Figure3a:CFHTﬁeld of view of Q1622+238in V.North is at the top.Figure3b:Shear map of Q1622+238with a resolution step of22arcsec.The ellipses shows the position of the center of the central shear with the1,2,3σconﬁdence level. The center almost coincides with a distant cluster clearly visible onﬁgure3c.persion lower than400km/s.Outside the box the ap-parent shear is already below the1−<b/a>=0.015 threshold level and it is not possible to detect the cir-cular shear at distance from the group larger than one arcmin.This remark is important because it illustrates the limitation of the method in detecting lenses with a1−<b/a>=0.015on angular scales smaller than the scanning aperture.Therefore a low amplitude of the shear on the scanning aperture could be the actual signature of a small deﬂector rather than a sky area with a low shear!Although the compact group is only 30arcsec South-East of the QSO it might contribute toa weak lensing of PKS1741-03but it is diﬃcult to geta rough estimate of the amplitude of the magniﬁcationbias.3.PKS1508-05This is the second bright radiosource of the sample.At one arcminute North-West there is also a group arounda bright galaxy(G)which could be responsible for alarge shear.This distant group or cluster may con-tribute to a weak magniﬁcation by itself,but there is also a small clump of galaxies in the close vicinity of the radiosource with the brightest member at a distance of 8arcseconds only.The situation is similar to the case of the multiple QSO2345+007(BFK+93).This couldbe the dominant lensing agent which provides a larger magniﬁcation bias,especially if the nearby cluster has already provided a substantial part of the critical pro-jected mass density.4.3C446The radiosource is among the faintest in the optical (table1).There is a loose group of galaxies at40arc-sec South-West from the QSO.The orientation of the shear with respect to the group of galaxies can be reproduced with a rough2D simulation(Hue95)al-though atﬁrst look it was not so convincing as the PKS0135-247case.The lensing conﬁguration could be similar to PKS1508-05with a secondary lensing agentG near the QSO(ﬁg6a,b).Surprisingly there is also alarge shear amplitude which is not apparently linked to an overdensity of galaxies in V in the North-East corner.In such a case it is important to conﬁrm the re-sult with an I image to detect possible distant groups at a redshift between0.5and0.7.A contrario it is important to mention that the shear is almost null in the North-West area of theﬁeld which actually has no galaxy excess visible in V(ﬁg6b).B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous Radiosources7 Fig.4.Figure3c:Zoom at the center of theﬁeld of view of Q1622+238.The distant cluster around the bright central elliptical galaxy E is clearly identiﬁed on this very deep V image.Figure3d:Shear map of Q1622+238with a resolution step of60arcsec. similar to the resolution on other NTTﬁelds.The ellipses shows the position of the center of the central shear with the1,2,3σconﬁdence level.The center almost coincides with a distant cluster clearly visible onﬁgure3c.5.DiscussionDue to observational limitations on the visibility of ra-diosources during the observations the selection criteria were actually very loose as compared with what we have proposed in Section2for a large survey.The results we present here must be considered as a sub-sample of QSOs with a moderate possible bias.Nevertheless,for at least 3of the sources there are some lensing agents which are associated with foreground groups or clusters of galaxies that are detected and correlated with the shearﬁeld.For the2other cases the signature of a lensing eﬀect is not clear but cannot be discarded from the measurements.All the radiosources may have a magniﬁcation bias enhanced by a smaller clump on the line of sight or even an(unseen) foreground galaxy lying a few arcsec from the radiosource (compound lens similar to PKS1508).The occurrence of coherent shear associated with groups in theﬁeld of the radiosources is surprisingly high.This might mean that a lot of groups or poor clusters which are not yet identiﬁed contain a substantial part of the hidden mass of LSS of the Universe below z=0.8.Some of them responsible for the observed apparent shear may be the most massive pro-genitor clumps of rich clusters still undergoing merging.Although these qualitative results already represent a fair amount of observing time we are now quite convinced that all of theseﬁelds should be reobserved,in particular in the I and K bands,to assess the nature of the deﬂec-tors.Spectroscopic observation of the brightest members of each clump is also necessary to determine the redshift of the putative deﬂectors.This is an indispensable step to connect the shear pattern to a quantitative amount of lensing mass and to link the polarization map with some dynamical parameters of visible matter,such as the ve-locity dispersion for each deﬂector,or possibly the X-ray emissivity.at the present time,we are only able to say that there is a tendency for a correlation between the shear and light overdensity(FM94).From the modelling point of view,simulations have been done and reproduce fairly well the direction of the shear pattern with a distribution of mass that follows most of the light distribution given by the isopleth or isolumi-nosity contour of the groups in theﬁelds.Some of these condensations do not play any role at all and are probably too distant to deﬂect the light beams.Unfortunately,in order to make accurate modelling it is necessary to have a good estimate of the seeing eﬀect on the amplitude of the shear by comparing with HST referenceﬁelds,and good redshift determinations as well of the possible lenses to get their gravitational weight in theﬁeld.It is also impor-tant to consider more carefully the eﬀect of convolution8 B.Fort et al.:Detection of Weak Lensing in the Fields of Luminous RadiosourcesFig.5.Figure4a:NTTﬁeld of view for PK0135.North is at the top.Note the group of galaxies around g1,g2,g3and g4 responsible for a coherent shear visible onﬁgure4bFig. 6.Figure5a:NTTﬁeld of view for PKS1508.Note the North-West group of galaxies near the brighter elliptical E responsible for a larger amplitude of the shear onﬁgure5b and the small clump of galaxies g right on the line of sight of the QSO.of the actual local shear which varies at smaller scales than the size of the scanning beam(presently about one arcminute size).This work is now being done but is also waiting for more observational data to actually start to study the gravitational mass distribution of groups and poor clusters of galaxies in theﬁeld of radiosources.6.ConclusionThe shear patterns observed in theﬁelds ofﬁve bright QSOs,and the previous detection of a cluster shear in Q2345+007(BFK+93)provide strong arguments in fa-vor of the?bartelmann93b hypothesis to explain the large scale correlation between radiosources and foreground galaxies.The LSS could be strongly structured by nu-merous condensations of masses associated with groups of galaxies.These groups produce signiﬁcant weak lensing eﬀects that can be detected.A rough estimate of the mag-niﬁcation bias is given by the polarization maps around these radiosources.It could sometimes be higher than half a magnitude and even much more with the help of an in-dividual galaxy deﬂector at a few arcsec.of the QSO line of sight.The results we report here also show that we can study with the weak shear analysis the distribution of density peaks of(dark)massive gravitational structures (ieσ>500km/s)and characterise their association with overdensities of galaxies at moderate redshift(z from0.2 to0.7).A complete survey of a large sample of radiosource ﬁelds will have strong cosmological interest for the two as-pects we mentioned above.Furthermore,the method can be used to probe the intervening masses which are associ-ated with the absorption lines in QSOs or to explain the unusually high luminosity of distant sources like the ultra-luminous sources IR10214+24526(SLR+95)or the most distant radio-galaxy8C1435+635(z=4.25;LMR+94).Therefore we plead for the continuation of systematic measurements of the shear around a sample of bright ra-diosources randomly selected with the double magniﬁca-tion bias procedure(BvR91).Our veryﬁrst attempt en-countered some unexpected obstacles related to the lim-itedﬁeld of view of CCDs or the correction of instrumen-tal distortion.It seems that they can be overcome in the near future.We have good hopes that smooth distribu-tions of mass associated with larger scale structures likeB.Fort et al.:Detection of Weak Lensing in the Fields of Luminous Radiosources9 Fig.7.Figures6a:NTTﬁeld of3C446.Note onﬁgure6b the shear pattern relatively to the isopleth of possible foreground groups and the galaxies g on the line of sight of the QSOﬁlaments and wall structures could be observed with a dedicated wideﬁeld instrument that minimizes all instru-mental and observational systematics,or still better with a Lunar Transit telescope(FMV95). Acknowledgements We thank P.Schneider,N.Kaiser,R. Ellis,G.Monet,S.D’Odorico,J.Bergeron and P.Cou-turier for their enthusiastic support and for useful discus-sions for the preparation of the observations.The data obtained at ESO with the NTT would probably not have been so excellent without the particular care of P.Gitton for the control of the image quality with the active mirror. We also thank P.Gitton for his helpful comments and T. Brigdes for a careful reading of the manuscript and the en-glish corrections.This work was supported by grants from the GdR Cosmologie and from the European Community (Human Capital and Mobility ERBCHRXCT920001). 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a rXiv:as tr o-ph/61363v112Oct26Studying Galaxy Evolution with Spitzer and Herschel CUP Conference Series,Vol.**VOLUME**,2006V.Charmandaris,D.Rigopoulou,N.Kylaﬁs Biased galaxy formation in the ﬁelds of high-redshift AGN J.A.Stevens,1M.J.Page,2F.J.Carrera,3R.J.Ivison,4and Ian Smail 51Centre for Astrophysics Research,University of Hertfordshire,College Lane,Herts AL109AB,UK 2Mullard Space Science Laboratory,University College London,Holmbury St.Mary,Dorking,Surrey RH56NT,UK 3Instituto de Fisica de Cantabria (CSIC-UC),Avienida de los Castros 39005Santander,Spain 4UK Astronomy Technology Centre,Royal Observatory,Blackford Hill,Edinburgh EH93HJ,UK 5Institute for Computational Cosmology,Durham University,South Road,Durham DH13LE,UK Abstract.We discuss preliminary results from our programme to map the ﬁelds of high-redshift AGN.In the context of the hierarchical models such ﬁelds are predicted to contain an over-density of young,luminous galaxies destined to evolve into the core of a rich cluster by the present epoch.We have thus imaged from submillimetre to X-ray wavelengths the few-arcmin scale ﬁelds of a small sample of high-redshift QSOs.We ﬁnd that submillimetre wavelength data from SCUBA show striking over-densities of luminous star-forming galaxies over scales of ∼500kpc.Whilst many of these galaxies are undetected even in deep near-IR imaging almost all of them are detected by Spitzer at 4.5,8.0and 24µm,showing that they have extremely red colours.However,they are not detected in our XMM-Newton observations suggesting that any AGN must be highly obscured.Optical-through-mid-IR SEDs show the redshifted 1.6µm bump from star-light giving preliminary evidence that the galaxies lie at the same redshift,and thus in the same structure,as the QSO although this ﬁnding must be conﬁrmed with photometric and/or spectroscopic redshifts.1.IntroductionThe popular hierarchical model of galaxy formation predicts that elliptical galax-ies found today in the cores of rich clusters formed at high redshifts and at rare high-density peaks of the dark matter distribution.Within these regions,gas rich proto-galaxies merge together rapidly and form stars at a high rate.The same reservoir of gas used to build the stellar mass can also fuel the growth of the supermassive black holes (SMBH)found dormant in the centre of the galaxies at low redshift (Kauﬀmann &Haehnelt 2000).Since massive star formation is known to be a dusty phenomenon,the light from such young galaxies may well be highly obscured rendering the population inaccessible to optical techniques.Dust enshrouded star formation is,however,a luminous phenomenon in the submillimetre (hereafter submm)through far-IR waveband where the star-light absorbed by dust grains is re-emitted.12Stevens,Page,Carrera,Ivison and SmailUnfortunately,it is not currently feasible at submm/far-IR wavelengths to perform a survey of a randomly selected region of sky over an area suﬃciently large to ensure that rare structures in the early universe are contained within it. However,one method of locating such structures is to target theﬁelds of high-redshift AGN.Given their huge luminosities,such objects must already contain a SMBH,and therefore must represent some of the most massive objects in exis-tence at their epochs.They should thus act as signposts to the rare high-density peaks that we wish to study and can target with existing technology at submm wavelengths(Ivison et al.2000;Stevens et al.2003).This paper presents pre-liminary results from such a programme.We concentrate on two QSOﬁelds at 1<z<3,presenting submm results obtained with SCUBA on the JCMT and follow-up imaging at near-IR(UKIRT)and mid-IR(Spitzer)wavelengths.2.Over-densities of luminous,extremely red star-forming galaxies The two targets discussed here are the X-ray absorbed QSOs RX J094144.51+ 385434.8(z=1.82)and RX J121803.82+470854.6(z=1.74).The importance of these objects has been discussed extensively in the literature(Page et al.2004; Stevens et al.2005).See also the contribution by Page et al.in this volume.Figure 1.Submm,mid-and near-IR imaging of the RX J121803.82+470854.6ﬁeld.Left-hand panel shows850µm contours(2,3,4,5σ)on a deepK-band image whilst the right-hand panel shows the same contours on an8.0µm image.Note that dust peaks lacking K-band counterparts often dohave detections at8.0µm.Each panel is∼1arcmin square.Submm,near-and mid-IR images of the RX J121803.82+470854.6ﬁeld are shown in Fig.1.The850µm data reveal a large over-density of sources, particularly pronounced in the close vicinity(∼30arcsec)of the QSO.Results from blank-ﬁeld surveys predict,at most,one≥3σsource in addition to the QSO.The near-and mid-IR imaging gives an indication that many of these submm sources are indeed real and have extremely red colours.Many of the them are detected by Spitzer even when they are not seen in deep(K∼20.5)near-IR imaging;e.g.the two most signiﬁcant dust peaks in Fig.1.Star-formationHigh-redshift AGNﬁelds3 rates computed in the standard manner are at least several100M⊙yr−1.It can thus be concluded that we have discovered a large over-density of star-forming galaxies in the few hundred kpc-scale environment of the QSO.Figure2.Submm and mid-IR imaging of the RX J094144.51+385434.8ﬁeld.450µm contours on the850µm image(left),450µm contours on the4.5µm image(centre)and450µm contours on the24µm image(right).Submm contours start at2σand increase in1σsteps.Panels are∼1.0×1.5arcmin.The structure of galaxies is∼400kpc in extent(Stevens et al.2004).Fig.2shows submm and mid-IR data for the RX J094144.51+385434.8ﬁeld.Here we see a similar over-density of luminous star-forming galaxies to that discussed above.For this dataset the observing conditions were suﬃciently transparent that we were able to collect good data at450µm.These data show that the large-scaleﬁlamentary structure seen at850µm breaks up into individual star-forming galaxies when observed at higher resolution(∼8cf.∼14arcsec).Such datasets were very rarely obtained with SCUBA at450µm because of the diﬃculty of observing at short submm wavelengths from Mauna Kea.However,the increased sensitivity andﬁeld-of-view aﬀorded by SCUBA-2 will go a long way to alleviating this problem and we can look forwards to higher resolution images of distant galaxies.A second result is that the submm-selected galaxies are detected by Spitzer with both IRAC and MIPS(Fig.2)verifying their reality and,with the addi-tion of optical and near-infrared imaging,allowing us to construct SEDs of the individual galaxies(see Fig.3).Weﬁnd that the SEDs are quite similar to that of the local ULIRG Arp220if it is moved to the redshift of the QSO(z=1.82) suggesting that the bump we see in the spectra,peaking roughly in the4.5µm band is the redshifted1.6µm bump from star-light.This result provides the ﬁrst evidence that the luminous star-forming galaxies discovered by SCUBA are at the same redshift and in the same structure as the QSO.We are currently working to conﬁrm thisﬁnding with photometric and spectroscopic redshifts.2.1.Buried AGN?If these galaxies are to evolve into cluster elliptical galaxies then the SMBHs found at their centres at the current epoch should be active at z∼2.Our50ks XMM-Newton observations detect the QSOs but not the star-forming galaxies in4Stevens,Page,Carrera,Ivison and SmailFigure3.Optical through mid-IR spectra of the QSO RX J094144.51+385434.8(top dotted line and points)and the submm galaxies in its vicinity.The solid line is the spectrum of the local ULIRG Arp220redshifted toz=1.82and scaled arbitrarily(Silva et al.1998).theirﬁelds.If we assume that these galaxies contain an AGN with a luminosity L(2−10keV)=1044erg s−1and a photon indexΓ=2then the non-detections imply a column density N H>5×1023cm−2.Therefore,if these galaxies contain reasonably powerful AGN they must be highly obscured.3.Looking ahead to SCUBA-2and HerschelThe next year will see major new facilities operating at far-IR and submm wave-lengths.Both Herschel and SCUBA-2will provide much faster mapping speeds than those currently available allowing us to map an area of sky around the QSOs large enough to observe the wholeﬁlamentary structure of the collapsing proto-cluster rather than just the core region.Simulations show that this will require a map of at least20Mpc square at z=2(comoving units).At present a signiﬁcant amount of telescope time is required to map one hundredth of this area but SCUBA-2can map a region this large in only a few hours.ReferencesIvison,R.J.,Dunlop,J.S.,Smail,Ian,Dey,Arjun,Liu,M.C.,&Graham,J.R.,2000, ApJ,542,27Kauﬀmann,G.,&Haehnelt,M.,2000,MNRAS,311,576Page,M.J.,Stevens,J.A.,Ivison,R.J.,&Carrera,F.J.,2004,ApJ,611,L85 Page,M.J.,Carrera,F.J.,Ebrero,J.,Stevens,J.A.,&Ivison R.J.,this issue Silva,L.,Granato,G.L.,Bressan,A.,&Danese,L.,1998,ApJ,509,103Stevens,J.A.et al.2003,Nat,425,264Stevens,J.A.,Page,M.J.,Ivison,R.J.,Smail,Ian,&Carrera,F.J.,2004,ApJ,604, L17High-redshift AGNﬁelds5 Stevens,J.A.,Page,M.J.,Ivison R.J.,Carrera,F.J.,Mittaz,J.P.D.,Smail,Ian,& McHardy,I.M.,2005,MNRAS,360,610。