Stellar Occultation Observations of Saturn's North-Polar Temperature Structure

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Observation is a fundamental skill that can be applied in various fields,from science to art.When writing an essay on the topic of careful observation,you can explore its importance,its applications,and the benefits it brings to different areas of study and life. Heres a detailed outline and some content to help you get started on your essay:Title:The Art of ObservationIntroduction:Begin by defining observation and its significance.Introduce the concept of careful observation and its role in gaining deeper insights. Preview the main points you will discuss in the essay,such as the importance of observation in scientific research,its application in the arts,and its impact on personal growth.Body Paragraph1:Observation in Scientific ResearchDiscuss how careful observation is the cornerstone of scientific discovery.Provide examples of famous scientists who made significant contributions based on their observations e.g.,Galileos observations of celestial bodies,Darwins observations of species.Explain the process of scientific observation,including the use of tools and methods to ensure accuracy.Body Paragraph2:Observation in the ArtsExplore how artists use observation to capture the essence of their subjects.Discuss the role of observation in different art forms,such as painting,sculpture,and photography.Provide examples of artists known for their keen observational skills e.g.,Rembrandts attention to light and shadow,Ansel Adams focus on natural landscapes.Body Paragraph3:Observation in Everyday LifeDiscuss the importance of observation in daily activities,such as reading body language, understanding social cues,and appreciating the beauty of the natural world.Explain how careful observation can lead to personal growth and a deeper understanding of the world around us.Provide personal anecdotes or observations that illustrate the value of being an attentive observer.Body Paragraph4:The Benefits of Careful ObservationHighlight the benefits of careful observation,such as improved problemsolving skills, enhanced creativity,and a greater appreciation for the world.Discuss the role of observation in education and how it can be taught and nurtured in students.Address potential challenges in developing observational skills,such as distractions or the need for patience and focus.Conclusion:Summarize the key points discussed in the essay,emphasizing the universal value of careful observation.Reflect on the personal impact of observation and how it can enrich ones life.End with a call to action,encouraging readers to cultivate their observational skills and to appreciate the world around them through a more attentive lens.Sample Introduction:Observation is more than just a passive act of watching it is an active engagement with the world that allows us to uncover hidden patterns,understand complex phenomena,and appreciate the beauty of our surroundings.Careful observation is a skill that transcends disciplines,from the meticulous documentation of a scientist to the intuitive insights of an artist.This essay will delve into the art of observation,exploring its significance in scientific research,its application in the arts,and its impact on our everyday lives. Sample Body Paragraph:In the realm of scientific research,careful observation is the lifeblood of discovery.It was through careful observation that Galileo Galilei was able to challenge the geocentric model of the universe,and it was Charles Darwins meticulous observations of finches on the Galapagos Islands that led to the development of his theory of evolution by natural selection.These examples illustrate the power of observation to reveal the underlying truths of our world.The process of scientific observation often involves the use of specialized tools and methods,such as telescopes,microscopes,and controlled experiments,to ensure that observations are accurate and reliable.Remember to use clear and concise language,provide relevant examples,and maintain a logical flow throughout your essay.This will help you effectively convey the importance and value of careful observation.。

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Sloan Extension for Galactic Underpinnings and Evolution(SEGUE)Segue(v.):To proceed to what follows without pauseHeidi Newberg1,Kurt Anderson2,3,Timothy Beers4,Jon Brinkmann3,Bing Chen5,Eva Grebel6, Jim Gunn7,Hugh Harris8,Greg Hennessy9,ˇZeljko Ivezic7,Jill Knapp7,Alexei Kniazev6,Steve Levine8,Robert Lupton7,David Martinez−Delgado6,Peregrine McGehee2,10,Dave Monet8,JeﬀMunn8,Michael Odenkirchen6,JeﬀPier8,Connie Rockosi11,Regina Schulte−Ladbeck12,J.Allyn Smith10,Paula Szkody11,Alan Uomoto13,Rosie Wyse13,Brian Yanny141Rensselaer Polytechnic Institute2New Mexico State University3Apache Point Observatory4Michigan State University5ESA/Vilspa,Madrid,Spain6Max-Planck-Institut f¨u r Astronomie,Heidelberg7Princeton University8US Naval Observatory,Flagstaﬀ9US Naval Observatory,DC10Los Alamos National Laboratory11University of Washington12University of Pittsburgh13Johns Hopkins University14Fermi National Accelerator LaboratoryI.Project SummaryA.Science GoalsWe propose an imaging and spectroscopic survey to unravel the structure,formation history, kinematics,dynamical evolution,chemical evolution,and dark matter distribution of the Milky Way.These results underpin our knowledge of the formation of the Milky Way Galaxy and of for-mation processes within the Milky Way,and will be the cornerstone of our understanding of galaxy formation processes in general.Cosmology is entering a precision era,facilitated by new work on the Cosmic Microwave Background by the Wilkinson Microwave Anisotropy Probe(WMAP)and on the distribution of galaxies by the Sloan Digital Sky Survey(SDSS)and by smaller,deeper large-telescope surveys.Galaxy formation and evolution,however,is still as data-starved as cosmology was twenty years ago.The Milky Way is the only galaxy in which we can hope to kinematically and spatially resolve the fossil record of evolution,since here the geometry is relatively unambiguous and intrinsically faint stars can be readily observed.Two key projects which focus on Galactic history and dynamics are:(1)detection of sub-structure in the Galactic halo,and(2)deﬁning and reﬁning our knowledge of the Milky Way’s Galactic disks.Other projects that will be necessary to realize the full potential of the key projects include understanding the relationship between SDSS photometry and the physical properties of stars,mapping the interstellar extinction in three dimensions,and studying the chemical evolution of the earliest Milky Way stars.To accomplish these goals,the existing SDSS hardware and software will be used to image (inﬁve SDSS passbands)four thousand square degrees of the Milky Way at low Galactic latitude and to sample the stars in this new region and in the existing high-latitude SDSS survey to targetand obtain spectra of240,000stars.These spectra will allow determinations of radial velocities and chemical abundances,which will allow us to study kinematics,dynamics,and the chemical history of the Galaxy.Key Project1:Halo SubstructureSDSS data have already been used to trace the tidal stream from the Sagittarius dwarf galaxy,and to discover a second large tidal stream in the plane of the Milky Way.The structure of the Milky Way’s halo is suﬃciently lumpy that it has so far deﬁed a consistent globalﬁt to the smooth component of the spheroid stars.The halo may contain a(possiblyﬂattened)power law component,aﬂattened inner halo,at least two large tidal streams,a dozen dwarf galaxies and a hundred globular clusters.Some of the dwarf galaxies and globular clusters are currently being pulled apart by tidal forces.Some of the stars in the components that appear to be smooth in density may retain kinematics of the stellar associations in which they were born.Disentangling the structure of the Milky Way halo requires that individual stellar associations can be separated by population(age and metallicity),kinematics,and spatial density.The SDSS and SEGUE photometry can be used for photometric parallax(spatial density)and isochrone ﬁtting to stellar components(into rough age and metallicity bins).Galaxy components can be separated kinematically with radial velocities.The stellar physical properties determined from spectroscopy and from imaging of open clusters serve as a check on the isochrones and further serve to illuminate the chemical composition of each component.The dynamics of stellar streams allow us toﬁt the Galactic potential’s shape and orientation, and constrain parameters characterizing the lumpiness of the halo dark matter.The dark matter itself could accrete with time as the stars do;knowledge of the Galactic merger history and grav-itational potential place important constraints on N-body models of galaxy formation and on the expected velocity distribution of dark matter particles.The velocity distribution of dark matter particles can aﬀect both the energy spectrum and annual modulation of the expected signal in dark matter direct detection experiments on the Earth.Key Project2:Disk structureImaging at low Galactic latitude will allow us to study the transition from thin disk to thick disk toﬂattened inner halo.There is general agreement on the number and exponential form of the Milky Way stellar disks,but little agreement on the exact parameters of each.This situation is similar to the state of our knowledge of the halo several years ago,when there was general agreement that the spheroidal population of stars was well modeled by a power law,but with no agreement on theﬂattening parameter(measurements range from c/a=0.4−1.0).As the current generation of precise data is beginning to show,the Milky Way’s disks are not as simple as the present models suggest.The fact that the stars associated with the large tidal stream in the plane of the Milky Way were initially widely attributed to an extended thick disk of stars underlines how little we know for sure about the number and detailed form of the Milky Way’s disks.SEGUE will use spectra(physical properties and radial velocities),photometry(stellar popu-lation and spatial density),and proper motions from outside catalogs to separate and normalize the Galactic components in the solar neighborhood.Additionally,the disk components will be traced using stars as close asﬁve or ten degrees from the Galactic plane,using techniques similar to those forﬁnding halo substructure.We do not expect to be able to trace all the spiral substructure of the young thin disk,as that is best studied at longer wavelengths,but we will be able to trace the structure,kinematics,and compositions of the other disks as a function of position in the Galaxy. This latter goal will require that we understand the three dimensional structure of the Interstellar Medium(ISM),including independent measures of dust from SEGUE observations,and its eﬀects on our stellar photometry.Formation HistoryThe identiﬁcation and characterization of the Milky Way components can be utilized as an archaeological“dig”illuminating the fossil record of galaxy evolution.We will study how many mergers and of what size and time series must have occurred to make the Milky Way.We will begin to be able to pick apart the chemical and dynamical evolution of the Galaxy as a whole.We will search for rare,especially low metallicity,stars that‘freeze-in’the state of the ISM during the earliest stages of star formation in the Universe.The rare stellar objects identiﬁed in this survey will provide followup targets of high scientiﬁc interest for the world’s largest telescopes.B.Survey DataApproximately four thousand square degrees of new imaging data,at moderate to low Galac-tic latitude,and spectra of240,000Galactic stars will be acquired.The imaging footprint was designed so that no part of the sky(aboveδ=−20◦observable from the Apache Point Observa-tory)is more than10◦from either an SDSS or a SEGUE imaging stripe.In the Galactic caps, no part of the sky is more than5◦from an imaging stripe.In addition,the scans are designed to tie the photometric calibration from the SDSS north Galactic cap to the scans in the south,and to cross each other a suﬃcient number of times to reduce systematic uncertainties in the overall photometric calibration.The positions of the spectroscopic plates are chosen to sample the Galaxy in all directions,so that no part of the observable sky is more than about ten degrees from a spec-troscopic plate,and to target well-studied open clusters.Figure1shows the approximate layout of the SEGUE imaging stripes and spectroscopic plates on the sky.The low Galactic latitude imaging enables studies of the metal-rich Galactic thin disk,the vertical structure of the thin and the thick disks,the Galactic warp andﬂaring,the three dimen-sional structure of the ISM,and present star forming regions.The imaging will be taken in similar weather conditions,at the same scanning rate(which translates to the same exposure time),and with the same instruments andﬁlters as the SDSS.Each stripe is2.5◦wide and requires two interleaved scans with the SDSS imaging camera,on separate nights,to complete.The imag-ing includes twelve constant Galactic longitude stripes which go through the Galactic plane and typically extend thirty-ﬁve degrees on either side(dashed green lines in Figure1).These stripes are separated by about20◦of Galactic longitude,varying somewhat to pass through known open clusters,SIRTF legacyﬁelds,and patches of low extinction near the Galactic plane.The constant Galactic longitude stripes connect and overlap SDSS imaging of the Galactic caps to facilitate the photometric calibration of both old and new data.In addition,three new SDSS stripes(72,79,and90,shown as solid green lines in Figure1) will be imaged in the South Galactic Cap.Only three stripes were imaged in the South Galactic Cap during the SDSS survey,and the additional stripes are needed to sample that part of the sky about every ten degrees.One stripe(red line in Figure1)follows the Sagittarius dwarf tidal stream across the northern sky.Two long(half-ﬁlled)strips(magenta lines in Figure1)cross the remaining SEGUE stripes,and will be used to cross-calibrate the stellar photometry to a level of at least2%(systematic+rms),and will trace low latitude structures,including the newly discovered tidal stream in the Galactic plane.The SDSS camera must scan along great circles,so all of these stripes describe great circles on the Celestial Sphere.The spectroscopic observations include1200spectra in each of200individual sky directions. The plate positions were chosen to sample the sky in all observable directions,and spectra will be selected to sample stars from one to100kpc from the Sun and from as many Galactic substructures as possible.Additional observations target regions of high interest such as open clusters,star formation regions,and known tidal streams in the halo.Each plate position is3◦in diameter.We will design two640-ﬁber plates in each plate position,with a total of about1200stellar targets-60-300306090120150180210240270300-90-60-300306090-90-60-30030609010230130l b s90s86s79s72s9s16s27s37s4418h22h2h 6h 6h 17.4h 2718.0h 618.6h 837.9h 498.6h 1621.1h -022.8h 25 1.3h 32 3.6h 17 5.0h -11Figure 1.Low Latitude Imaging and Spectroscopy Plan.The SFD (1998)reddening map is shown in Galactic coordinates;note the center is shifted to (l,b )=(120◦,0◦).Green,red,magenta (purple)lines indicate new SEGUE scans to be obtained.SEGUE Imaging at l =110degrees from −30◦<b <30◦has already been obtained as of Nov 2003(SDSS runs 4134,4135,4144,4152).The red line along the great circle with (node,incl)=(32◦,35◦)follows the Sagittarius dwarf tidal stream.Magenta lines indicate half-ﬁlled “strips”in portions of the sky at low Galactic latitude,and cross the constant longitude stripes for better calibration;the great circles arcs are deﬁned by (node,incl)=(259.9◦,43.6◦),(311.0◦,66.7◦).The total SEGUE imaging area is about 4000sq.degrees,of which 200sq.degrees has already been obtained.Black lines indicate existing or planned SDSS regular imaging.Black dotted reference lines are at b =0◦and declination (DEC)=−20◦(no SEGUE imaging or spectroscopy occurs at a DEC of <−20◦from Apache Point Observatory in the Northern hemisphere).Black long dashed lines mark constant Right Ascensions (RAs)of (18,22,2,and 6)bels above the top of the ﬁgure indicate RA,DEC start and end for a vertical SEGUE imaging stripe.Open black circles indicate positions of known Sagittarius dwarf tidal stream stars.Filled black circles indicate positions of known Monoceros stream stars.Open black diamonds indicate positions of known Galactic open clusters.The blue circles indicate individual 3-degree diameter positions of Galactic structure plate pairs (bright plate:45min exposure,plus faint plate:90min exposure),168blue plate pairs.Yellow circles indicate positions of ‘special plates,’landing on a known open cluster,the Sag.dwarf stream,or the Monoceros Ring structure.29blue plate pairs.Total:197plate pairs and about 240,000stellar spectra with resolving power R ∼2000,and 3<S/N <100for objects with 20.3>g >14.5.plus calibration objects.One plate will have the SDSS standard 45minute exposure time,and the other will be exposed for twice as long,allowing us to reach stellar targets as faint as g ∼20.3.Spectroscopic targets will include halo giants,metal-poor dwarfs,G disk and halo dwarfs,white dwarfs,and a large variety of rare stars.At low latitudes,targets within star-forming regions will be selected.II.Scientiﬁc CaseOur understanding of Galaxy evolution has advanced considerably since the monolithic col-lapse model of Eggen,Lynden-Bell and Sandage(1962)was adopted as the standard.Most experts now believe that the Galaxy was built up through a series of mergers(Searle&Zinn1978),though there is no agreement on the number and size of the merger events.These current models of galaxy formation stem from cold dark matter(CDM)simulations that show the outer halos accret-ing over billions of years(Steinmetz&Navarro2002),and from the increasing number of examples of moving groups and tidal disruption discovered in the halo of our galaxy(Majewski et al.2003; Newberg et al.2002;Odenkirchen et al.2001a;Irwin&Helmi et al.1999;Ibata,Gilmore,& Irwin1995;Grillmair et al.1995;Irwin&Hatzidimitriou1995),M31(Ferguson et al.2002),and other external galaxies(Shang et al.1998,Zucker et al.2004).It is possible that the hierarchical merging process is most important in the dark matter dominated galactic halos,while disks might form from the(angular momentum conserving)collapse of the gas within the stellar spheroid.However,Λcold dark matter simulations suggest merging may signiﬁcantly aﬀect the formation of disks as well(Abadi et al.2003).Evidence of mergers is currently most apparent in the outer halo where signatures of satellite accretion persist for many gigayears(Johnston,Spergel,&Hernquist1995).Dwarf galaxies and globular clusters are among the outer halo objects which are merging at the current epoch.It is also possible that there exist some lumps of dark matter in the outer halo that have not yet merged,and which do not contain stars(e.g.,Bullock,Kravtsov,&Weinberg2001).These latter structures could be evident by their perturbation of tidal tails and warping of disk structures.Our own Milky Way is the only galaxy that we can presently study at suﬃciently high spatial and kinematical resolution,and at suﬃcient depth,to address many of the open questions of galaxy formation and small-scale structure evolution in sub-halos.Our goal is to obtain the spectroscopic and photometric data required to unravel the structure,the formation history,the kinematic and dynamical evolution,the chemical evolution,and the distribution of the dark matter within and around the Milky Way.We propose two key projects,which contribute to our knowledge of the Galactic mass assem-bly and disk formation models.These projects are:(1)detection of substructure in the Galactic halo,and(2)deﬁning the structures of the Galactic disks.These are really two parts of the one key project to deﬁne the major components of the Milky Way galaxy,but are listed separately since they may require diﬀerent data sets and analysis methods.One may think of this proposed project as providing a large homogeneous input data set to a21st century model of the Galaxy–one which involves not only accurate multi-color photometry such as has gone into earlier models (Bahcall&Soneira1984),but large amounts of kinematic velocity and proper motion data which can be used to complete the dynamical and evolutionary picture.This technique is most similar to that used to construct the Besancon model of the Galaxy(Robin et al.2003),but with more input data.Detection of substructure in the Galactic halo requires photometry and radial velocities in as many directions as possible.The large tidal streams that have already been discovered are more than4kpc across,setting the scale over which we must sample the sky toﬁnd all large tidal structures.Characterizing the Galactic disks requires data collection primarily at low latitudes, and within a few kpc of the Galactic plane.The goal is to separate disk components by their stellar content,and then measure the global properties.These projects will separate and describe components using radial velocities,proper motions, chemical composition,photometric parallax,and isochroneﬁtting to photometry.In some sense, our survey is concentrated on the“big picture”of our galaxy.We will identify and constrain all of the largest components,paving the way for future inquiries which willﬁndﬁner substructure,S52-32-20.4S341+57-22.5S297+63-20.S6+41-20S223+20-19.4S200-24-19.8S167-54-21.5(RA,DEC)[l,b](0,0)[96,-60](15,0)[128,-63](30,0)[157,-58](45,0)[177,-49](60,0)[190,-37](75,0)[199,-25](90,0)[207,-11](105,0)[214,2](120,0)[221,15](135,0)[229,28](150,0)[239,41](165,0)[254,52](180,0)[276,60](195,0)[308,63](210,0)[337,58](225,0)[357,49](240,0)[10,37](255,0)[19,25](270,0)[27,11](285,0)[34,-2](300,0)[41,-15](315,0)[49,-28](330,0)[59,-41](345,0)[74,-52]15171921g *23171921231517192123151719212305101520253035404550Figure 2.Polar histogram of color-selected turnoﬀstars on the celestial equator .This data was obtained with the Sloan Digital Sky Survey.The radial distance gives the apparent dereddened g ∗magnitude.The angular position gives the RA.Galactic coordinates are labeled for reference.The shading of each cell indicates the relative number of counts of stars in each (r,θ)=(g ∗,α)bin.A typical absolute magnitude for stars with these colors is M g ∗=4.2.The feature at α=60◦is an artifact from imperfect reddening correction of a large dust cloud at this position.The streak at α=229◦represents stars in the globular cluster Palomar 5.The boldface labels indicate our names for identiﬁed structures of halo stars.S341+57-22.5at g ∗∼22.5,and S167-54-21.5at g ∗∼21.5are cross sections of the Sagittarius dwarf galaxy tidal stream.more accurately determine the chemical evolution,and measure proper motions for a large fraction of the stars in the Milky Way.A calibrated catalog of images,spectra,and associated derived quantities,will be the primary product of this survey.These will be generated in nearly real time,to be used for rapid follow-up work or as input targets to space-based or large aperture telescopes.The need for this global picture of our galaxy is well illustrated by the results of Newberg et al.(2000;Figure 2).In this ﬁgure,there are seven marked concentrations of stars.Concentrations S341+57-22.5and S167-54-21.5have been identiﬁed as cross sections through the tidal stream ofthe Sagittarius dwarf spheroidal galaxy,which is currently in the process of tidal disruption.The overdensities S223+20-19.4and S200-24-19.8are thought to be pieces of another tidal disrupting stream in the plane of the Milky Way galaxy.The concentrations in this region near the Galactic plane,at15th and17th magnitude near the anticenter are not named,but also are not understood in any global picture of the Milky Way.The overdensity S297+63-20.is thought to be another tidal stream,possibly associated with the Sagittarius dwarf galaxy,though this has not been conﬁrmed and remains controversial.The concentrations S6+41-20and S52-32-20.4are thought to be portions of the stellar spheroid,though their density distributions do notﬁt standard spheroidal models within the errors of our density measurements.One sees in Figure2a strong argument for a global view of the whole Milky Way,including low Galactic latitudes,since one cannot identify substructure without understanding the major Galactic components in which that substructure is embedded,and properly accounting for inter-stellar extinction.Many of the scientiﬁc analyses that we anticipate will be based on these data have counterparts in the much smaller-scale eﬀorts of individuals or groups,which,unavoidably, dilute their impact by acquiring data in a piecemeal and non-uniform fashion.A uniform survey creates a synergy which allows more global questions to be addressed and leaves behind a legacy data set against which future data sets will be compared.A better understanding of the Milky Way’s structure and evolution is already a“cornerstone”project in ESA’s science planning,through the GAIA satellite mission,and plays an important role in the deﬁnition of the science goals for NASA’s SIM and TPF missions,which are“key elements in NASA’s Origins Program.”We demonstrate here how a deep imaging and spectroscopic optical survey will complement as well as lay the groundwork for these ambitious satellite projects. Furthermore,SEGUE willﬁll a unique and vital niche complementing ongoing and planned large ground based Galactic structure programs such as RAVE and K.A.O.S.A.Characterization of the Component Stellar Structures in the Milky WayThe fossil record of galaxy evolution(star formation and mass assembly)is written in the chemical,kinematic,and spatial distribution of Galactic stars.The main recognized components of the Galaxy are the thin disk,the thick disk,the bulge,and the stellar spheroid.Recently many groups of astronomers have identiﬁed examples of Galactic structure that either requires additional components or an increase in the complexity of the traditional components.Kinematic studies show the existence of moving groups and coherent streams(numerous studies),and a group of stars(Gilmore,Wyse,&Norris2002)that may be part of the merger that puﬀed up the thick disk.Overdensities of stars over the Galactic bar(Parker,Humphreys,&Larsen2002)have been found in photometry.Also,a new metal-weak thick disk component has been proposed(see Norris 1994,Beers et al.2002and references therein).Clearly,even the basic stellar components of the Milky Way are not yet understood in depth. The complex substructure now being identiﬁed has undoubtedly biased the previous limited studies of thick disk structure,contributing to our present imprecise knowledge of the thick disk;study of many lines of sight over much of the sky will be necessary to unravel the substructure and obtain a more complete picture.This survey would speciﬁcally target the thick disk/halo boundary and substructure.The structures would be studied in stellar density from statistical photometric parallaxes,and in kine-matics through statistics of the radial velocities/metallicities in each component.We use the term ”statistical photometric parallax”to describe the method of using photometry to determine dis-tance(photometric parallax)in cases where the number of stars is large,so that statistics can be used to estimate the underlying spatial structure of the group.We will have a unique opportunity to study the stellar Metallicity Distribution Function(MDF),especially in the region where the thick disk and spheroid populations overlap.Figure3demonstrates preliminary results from SDSS-4-3-2-101[Fe/H]100010000100000Z D i s t a n c e (k p c )Figure 3.The distance and metallicity distribution of EDR stars.The distance distribu-tion of ∼4000stars from the SDSS Early Data Release (EDR)as a function of metallicity [Fe /H].One can clearly discriminate the presence of thick-disk stars with metallicities in the range -1.0<[Fe/H]<0and locations within a few kpc of the Sun,from the halo objects at large distances that extend to much lower metallicities.EDR spectra.Flaring and Warping of the Galactic PlaneThe disks of many galaxies both ﬂare and warp in their outer regions.Flaring is attributed to an increasing ratio of spherically distributed dark mass to disk mass with increasing distance from the center of the galaxy,and provides one of the few available methods of measuring the three-dimensional distribution of dark matter within a galaxy.The origin of Galactic warps is still something of a mystery.Tidal interactions with satellites and neighbors is an obvious cause;for example,the warp in the Galaxy is often attributed to the tidal inﬂuence of the Magellanic Clouds (e.g.,Weinberg and Nikolaev 2001;Garcia-Ruiz et al.2002)or of the Sagittarius dwarf spheroidal galaxy (Bailin 2003).However,not all warped galaxies appear to have (presently detected)neigh-bors.The warp andﬂare in the outer Galactic disk has been studied primarily using(radio)obser-vations of neutral hydrogen.The depth and color sensitivity of SDSS will allow the3-D structure of the northern warp in the Galaxy to be traced to distances beyond the entire known extent of the warp(20kpc,Binney1992),using photometrically identiﬁed giants,carbon stars(especially when combined with2MASS data)and red clump stars(e.g.,Margon et al.2002;Helmi et al.2003). The Structure of the Thick DiskHawley et al.(2002)show that early M dwarfs can be traced to distances of up to1kpc above the Galactic plane,well into the domain where the thick disk population dominates that of the thin disk.Since the stars of the thick disk are more metal-deﬁcient(typically by at least0.3-0.5 dex)than the thin disk stars,their colors,especially g−r,diverge from those of the metal-rich disk stars.One can therefore,at least in a statistical sense,separate the two populations.Aﬁrst look at the vertical structure of the thick disk from SDSS data has been carried out by Chen et al.(2001). Star counts in the thin and thick disks can be used to determine the initial mass function,and in particular the counts of lower-metallicity stars must be understood(see the recent discussion by Zheng et al.2001and Chabrier2003).The current SDSS imaging data provide star counts at high Galactic latitude only;under-standing and disentangling the vertical structure of both the thick and thin disks requires data covering the whole range of Galactic latitude at many longitudes.The Structure of the Galactic HaloSDSS data have already demonstrated the presence of very large structures in the Galactic halo(Yanny et al.2000;Ivezic et al.2000;Odenkirchen et al.2001a,b;Newberg et al.2002; Rave et al.2003;Yanny et al.2003).These structures include extra-tidal features around globular clusters and vast comoving stellar streams from accreted dwarf galaxies.These structures,and similar more tenuous analogues,may cover a signiﬁcant fraction of the sky.Imaging more sky allows such structures to be traced to larger angular sizes,and allows structures which do not completelyﬁll a great circle on the sky to be detected.Furthermore,high-metallicity globular clusters tend to be found at lower Galactic latitudes;there may be streamers and tails of diﬀerent color(metallicity)at lower latitudes.Indeed,recently Frinchaboy et al.2004showed that many low latitude open and globular star clusters are likely to be associated with a single large tidal stream in the Galactic plane.There is increasing evidence that even“globally recognized”structures,such as“the halo,”change dramatically with increasing Galactocentric distance.An inner,“ﬂattened”halo compo-nent,for example,has been indicated by many recent studies(Lemon et al.2003,Chiba&Beers 2000).Preston,Shectman&Beers(1991)have used the mean colors of blue horizontal-branch stars to indicate a possible decrease in the ages of stars with increasing Galactocentric distance. Sirko et al.(2004)use an analysis of the spectra of high-latitude A stars to demonstrate a change in the velocity ellipsoid of the halo with distance from the Galactic center.Both of these represent key results for understanding the formation of the Milky Way,which could be readily reﬁned and extended using our proposed survey eﬀort.Complexity of Galactic spheroid populations in other galaxies is traced by their globular cluster systems(at least in early-type galaxies with populous cluster systems that can be studied). Typically the globular cluster systems are bimodal,with bluer(lower metallicity)clusters mak-ing up a more extended and dynamically hotter system,and redder(higher metallicity)clusters comprising a system more centrally concentrated and sometimes rotating(e.g.many papers in IAU Symposium207,ed.Geisler,Grebel&Minniti2002).Typically theﬁeld-star populations have color and spatial distributions suggesting properties more similar to(and perhaps having。

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Venus Express Mission Definition ReportESA-SCI(2001)6 ESA-SCI(2001)6 October 20011An Orbiter for the study of the atmosphere, the plasma environment, and the surface of VenusMission Definition ReportEuropean Space Agency Agence Spatiale Européenne3 Venus Express Mission Definition Report ESA-SCI(2001)6ForewordVenus Express, an Orbiter for the study of the atmosphere, the plasma environment, and the surface of Venus, is a mission which was proposed to ESA in response to the Call for Ideas to re-use the Mars Express platform issued in March 2001. Venus Express together with two other missions, Cosmic DUNE and SPORT Express, was selected by ESA’s Space Science Advisory Committee for a Mission Definition Study. The industrial study of the three missions was conducted in parallel by Astrium-SAS (Toulouse, France) from mid-July to mid-October 2001. The payload included in the Venus Express Study comprises 5 instruments (ASPERA/MEx, PFS/MEx, SPICAM/MEx, VeRa/Rosetta, VIRTIS/Rosetta) from the Core payload of the original Proposal and the VENSIS/MEx radar in line with the SSWG recommendation. During the Study it was found scientifically reasonable and technically feasible to replace the standard Mars Express engineering Video Monitoring Camera by a scientific instrument, the Venus Monitoring Camera (VMC). The Mission Definition Report describes the scientific objectives of the Venus Express mission, presents selected payload set, and summarizes the results of the Mission Definition Study. This version of the report covers all science aspects of the mission but contains only a brief summary of the industrial study. The combined industrial study report for all the three missions is published in a separate cover. A complete Venus Express Mission Definition Report, including a comprehensive description of scientific goals, payload, and technical aspects of the spacecraft will be prepared by the end of 2001. The Venus Express Study was directly supported by the Science Study Team listed below.Mission science coordinationD.V. Titov, MPAe, Germany E. Lellouch, DESPA, France F.W. Taylor, Oxford University, UK L. Marinangeli, Universita d’Annunzio, Italy H. Opgenoorth, IRF-Uppsala, SwedenPrincipal InvestigatorsS. Barabash, IRF-Kiruna, Sweden /PI ASPERA J.-L. Bertaux, Service de Aeronomie, France /Co-PI SPICAM/ P. Drossart, DESPA, France /Co-PI VIRTIS/ V. Formisano, IFSI, Italy /PI PFS/ B. Haeusler, Universitaet der Bundeswehr, Germany /PI VeRa/ O. Korablev, IKI, Moscow, Russia /Co-PI SPICAM/ W.J. Markiewicz, MPAe, Germany /PI VMC/ M. Paetzold, Universitaet zu Koeln, Germany /Co-PI VeRa/ G. Picardi, Infocom Dpt. Univ. of Rome, Italy /PI VENSIS/ G. Piccioni, IAS, Italy /Co-PI VIRTIS/ J. Plaut, JPL/NASA, Pasadena, California, USA J.-A. Sauvaud, CESR-CNRS, France /Co-PI ASPERA/ P. Simon, BISA, Belgium /CO-PI SPICAM/The ESA members of the Scientific Directorate responsible for the study were: J-P. Lebreton, Study Scientist, Research and Science Support Department (RSSD), ESTEC M. Coradini, Science Planning and Coordination Office, ESA HQ, Paris G. Whitcomb, Future Science Projects and Technology Office, SCI-PF, ESTEC D. McCoy, Mars Express Project Team, SCI-PE, ESTEC. The Industrial study was lead by: Ch. Koeck (Study Manager), Astrium, France with support from: S. Kemble (Mission Analysis), Astrium, UK4 Venus Express Mission Definition Report ESA-SCI(2001)6L. Gautret (Payload Interface Engineering), Astrium, France P. Renard (System Engineering), Astrium, France F. Faye (Mars Express expertise), Astrium, France. Support was provided by the following colleagues within ESA:ESOC: M. Hechler and J. Rodriguez-Canabal, (Mission Analysis); R. Van Holtz, (Ground Segment definition) ESTEC A. Chicarro (Mars Express Project Scientist), RSSD/SCI-SO P. Falkner, (payload support), RSSD/SCI-ST P. Martin (Mars Express Deputy Project Scientist), RSSD/SCI-SO J. Romstedt (radiation environment analysis & payload support), RSSD/SCI-ST R. Schmidt (Mars Express Project Manager), SCI-PE J. Sorensen (radiation environment analysis), TOS-EMA P. Wenzel (Head of Solar System Division), RSSD/SCI-SO O. Witasse, (Science support), RSSD/SCI-SOThis report is available in pdf format at: http://solarsystem.estec.esa.nl/Flexi2005/ Requests for further information and additional hard copies of this report should be addressed to: Jean-Pierre Lebreton: Marcello Coradini: Jean-Pierre.Lebreton@esa.int Marcello.Coradini@esa.int5 Venus Express Mission Definition Report ESA-SCI(2001)6Executive SummaryThe first phase of Venus spacecraft exploration (1962-1985) by the Venera, Pioneer Venus and Vega missions established a basic description of the physical and chemical conditions prevailing in the atmosphere, near-planetary environment, and at the surface of the planet. At the same time, they raised many questions on the physical processes sustaining these conditions, most of which remain as of today unsolved. Extensive radar mapping by Venera-15,-16 and Magellan orbiters, combined with earlier glimpses from landers, have expanded considerably our knowledge of Venus’ geology and geophysics. A similar systematic survey of the atmosphere is now in order. This particularly concerns the atmosphere below the cloud tops, which, with the exception of local measurements from descent probes, has escaped detection from previous Venus orbiters. Many problems of the solar wind interaction, in particularly those related to the impact on the planetary evolution are still not resolved. The present proposal aims at a global investigation of Venus’ atmosphere and plasma environment from orbit, and addresses several important aspects of the geology and surface physics. The fundamental mysteries of Venus are related to the global atmospheric circulation, the atmospheric chemical composition and its variations, the surface-atmosphere physical and chemical interactions including volcanism, the physics and chemistry of the cloud layer, the thermal balance and role of trace gases in the greenhouse effect, the origin and evolution of the atmosphere, and the plasma environment and its interaction with the solar wind. Besides, the key issues of the history of Venusian volcanism, the global tectonic structure of Venus, and important characteristics of the planet’s surface are still unresolved. Beyond the specific case of Venus, resolving these issues is of crucial importance in a comparative planetology context and notably for understanding the long-term climatic evolution processes on Earth. The above problems can be efficiently addressed by an orbiter equipped with a suite of adequate remote sensing and in situ instruments. Compared with earlier spacecraft missions, a breakthrough will be accomplished by fully exploiting the existence of spectral “windows” in the near-infrared spectrum of Venus’ nightside, discovered in the late ‘80’-s, in which radiation from the lower atmosphere and even the surface escapes to space and can be measured. Thus, a combination of spectrometers, spectro-imagers, and imagers covering the UV to thermal IR range, along with other instruments such as a radar and a plasma analyzer, is able to sound the entire Venus atmosphere from the surface to 200 km, and to address specific questions on the surface that would complement the Magellan investigations. This mission will also tackle still open questions of the plasma environment focusing on the studies of nonthermal atmospheric escape. This issue will be addressed via traditional in situ measurements as well as via innovative ENA (Energetic Neutral Atom) imaging techniques. The instruments developed for the Mars Express and Rosetta missions are very well suited for this task. The following available instruments: SPICAM – a versatile UV-IR spectrometer for solar/stellar occultations and nadir observations, PFS – a high-resolution IR Fourier spectrometer, ASPERA – a combined energetic neutral atom imager, electron, and ion spectrometer, VIRTIS – a sensitive visible spectro-imager and mid-IR spectrometer, a radio science experiment VeRa, a wide-angle monitoring camera VMC, and subsurface and ionosphere sounding radar VENSIS will form the payload of the proposed Venus Express mission. Taken together, these experiments can address all the broad scientific problems formulated above. The Mission Definition Study demonstrated the feasibility of the proposed mission to Venus in 2005. The Mars Express spacecraft can accommodate the above mentioned experiments with minor modifications. The launch with Soyuz-Fregat can deliver this payload to a polar orbit around Venus with a pericenter altitude of ~250 km and apocenter of6 Venus Express Mission Definition Report ESA-SCI(2001)6~45,000 km. This orbit will provide complete coverage in latitude and local solar time. It is also well suited for atmospheric and surface sounding, as well as the studies based on solar and radio occultations. In comparison to the Pioneer Venus spinning spacecraft, Mars Express is an advanced 3 axis stabilised platform which provides significantly enhanced spectroscopic and imaging capabilities. The proposed duration of the nominal orbital mission is two Venus days (sidereal rotation periods) equivalent to ~500 Earth days. The Venus Express mission will achieve the following “firsts”: • First global monitoring of the composition of the lower atmosphere in the near IR transparency “windows”; • First coherent study of the atmospheric temperature and dynamics at different levels of the atmosphere from the surface up to ~200 km; • First measurements of global surface temperature distribution from orbit; • First study of the middle and upper atmosphere dynamics from O2, O, and NO emissions; • First measurements of the non-thermal atmospheric escape; • First coherent observations of Venus in the spectral range from UV to thermal infrared; • First application of the solar/stellar occultation technique at Venus; • First use of 3D ion mass analyzer, high energy resolution electron spectrometer, and energetic neutral atom imager; • First sounding of Venusian topside ionospheric structure; • First sounding of the Venus subsurface. Together with the Mars Express mission to Mars and the Bepi Colombo mission to Mercury, the proposed mission to Venus, through the expected quality of its science results, would ensure a coherent program of terrestrial planets exploration and provide Europe with a leading position in this field of planetary research. The international cooperation formed in the framework of the Mars Express and Rosetta missions will be inherited by the Venus Express and will include efforts of the scientists of European countries, USA, Russia, and Japan. The Venus Express orbiter will play the role of pathfinder for future, more complex missions to the planet, and the data obtained will help to plan and optimize future investigations. Venus studies can have significant public outreach given the exotic conditions of the planet and the interest in comparing Venus to Earth, especially in a context of concern with the climatic evolution on Earth.7 Venus Express Mission Definition Report ESA-SCI(2001)6Table of content1. INTRODUCTION................................................................................................................................................ 8 2. MISSION SCIENCE OBJECTIVES................................................................................................................. 8 2.1 LOWER ATMOSPHERE AND CLOUD LAYER (0 – 60 KM) ................................................................................... 8 2.2 MIDDLE ATMOSPHERE (60 – 110 KM) ........................................................................................................... 12 2.3 UPPER ATMOSPHERE (110 – 200 KM) ............................................................................................................ 13 2.4 PLASMA ENVIRONMENT AND ESCAPE PROCESSES ......................................................................................... 14 2.5 SURFACE AND SURFACE-ATMOSPHERE INTERACTION ................................................................................... 15 3. SCIENTIFIC PAYLOAD ................................................................................................................................. 17 3.1 ASPERA (ANALYZER OF SPACE PLASMAS AND ENERGETIC ATOMS) ......................................................... 17 3.2 PFS (HIGH RESOLUTION IR FOURIER SPECTROMETER) ................................................................................ 18 3.3 SPICAM (UV AND IR SPECTROMETER FOR SOLAR/STELLAR OCCULTATIONS AND NADIR OBSERVATIONS)20 3.4 VERA (VENUS RADIO SCIENCE).................................................................................................................... 22 3.5 VIRTIS (UV-VISIBLE-NEAR IR IMAGING SPECTROMETER) .......................................................................... 23 3.6 VENSIS (LOW FREQUENCY RADAR FOR SURFACE AND IONOSPHERIC STUDIES). ......................................... 25 3.7 VMC (VENUS MONITORING CAMERA) ......................................................................................................... 26 3.8 SYNERGY OF THE PAYLOAD. .......................................................................................................................... 27 3.9 PAYLOAD ACCOMMODATION ......................................................................................................................... 28 3.10 MISSION AND PAYLOAD SCHEDULE ............................................................................................................. 29 3.11 PAYLOAD TEAMS ......................................................................................................................................... 29 4 MISSION OVERVIEW...................................................................................................................................... 36 4.1 MISSION SCENARIO ........................................................................................................................................ 36 4.2 LAUNCH, DELTA-V, AND MASS BUDGETS ...................................................................................................... 37 4.3 OPERATIONAL ORBIT ..................................................................................................................................... 37 4.4 ORBITAL SCIENCE OPERATIONS ..................................................................................................................... 38 4.5 TELECOMMUNICATIONS ................................................................................................................................. 38 4.6 THERMAL CONTROL ....................................................................................................................................... 39 4.7 RADIATION REQUIREMENTS ........................................................................................................................... 39 4.8 GROUND SEGMENT IMPLEMENTATION AND OPERATIONS SUPPORT ............................................................... 39 4.9 MISCELLANEOUS ............................................................................................................................................ 40 5. SCIENCE OPERATIONS, DATA ANALYSIS, AND ARCHIVING ......................................................... 40 5.1 SCIENCE OPERATIONS CONCEPT ................................................................................................................... 40 5.2 PRINCIPAL INVESTIGATORS ........................................................................................................................... 40 5.3 INTERDISCIPLINARY SCIENTISTS (IDS) ......................................................................................................... 40 5.4 SCIENCE WORKING TEAM ............................................................................................................................. 40 5.6 SCIENCE OPERATION PLAN ............................................................................................................................ 41 5.7 DATA ANALYSIS ............................................................................................................................................. 41 5.8 SCIENCE MANAGEMENT PLAN ...................................................................................................................... 41 5.9 COMPLEMENTARY VENUS GROUND-BASED OBSERVATIONS ........................................................................ 41 6. PROGRAMMATIC VALIDITY ..................................................................................................................... 41 7. SCIENCE COMMUNICATION AND OUTREACH ................................................................................... 42 7.1 GOALS ............................................................................................................................................................ 42 7.2 SCIENTIFIC THEMES ....................................................................................................................................... 42 7.3 IMPLEMENTATION .......................................................................................................................................... 43 8. INTERNATIONAL COOPERATION............................................................................................................ 43 9. REFERENCES................................................................................................................................................... 45 10 ACKNOWLEDGMENTS ................................................................................................................................ 468 Venus Express Mission Definition Report ESA-SCI(2001)61. IntroductionSince the beginning of the space era, Venus has been an attractive target for planetary science. Our nearest planetary neighbour and, in size, the twin sister of Earth, Venus was expected to be very similar to our planet. However, the first phase of Venus spacecraft exploration (1962-1985) discovered an entirely different, exotic world hidden behind a curtain of dense clouds. The earlier exploration of Venus included a set of Soviet orbiters and descent probes, Veneras 4–16, the US Pioneer Venus mission, the Soviet Vega balloons, the Venera 15, 16 and Magellan radar orbiters, the Galileo and Cassini flybys, and a variety of ground-based observations. Despite all of this exploration by more than 20 spacecraft, the “morning star” remains a mysterious world. All these studies gave us a basic knowledge of the conditions on the planet, but generated many more questions concerning the atmospheric composition, chemistry, structure, dynamics, surface-atmosphere interactions, atmospheric and geological evolution, and the plasma environment. It is high time to proceed from the discovery phase to a thorough investigation and deep understanding of what lies behind Venus’ complex chemical, dynamical, and geological phenomena. The data from ground-based observations and previous space missions is very limited in space and time coverage, and, prior to the discovery of the near infrared spectral windows, lacked the capability to sound the lower atmosphere of Venus remotely and study the phenomena hidden behind the thick cloud deck from orbit. Thus a survey of the Venus atmosphere is long overdue. Pioneer Venus, Venera-15, -16, and Magellan provided global comprehensive radar mapping of the surface and investigated its properties. The use of penetrating radar can add a third dimension to the earlier investigations. While a fully comprehensive exploration of Venus will require, in the long term, in situ measurements from probes, balloons and sample return, so many key questions about Venus remain unanswered that even a relatively simple orbiter mission to the planet can bring a rich harvest of high quality scientific results. The re-use of the Mars Express bus with the payload based on the instruments available from the Mars Express and Rosetta projects is very appropriate in this regard. It offers an excellent opportunity to make major progress in the study of the planet.2. Mission science objectivesThe proposed Venus Express mission covers a broad range of scientific goals including atmospheric physics, subsurface and surface studies, investigation of the plasma environment and interaction of the solar wind with the atmosphere. For clarity we divided the atmosphere into three parts: lower atmosphere (0-60 km), middle atmosphere (60 – 110 km), and upper atmosphere (110 – 200 km). The physics, methods of investigation, and scientific goals are quite different for each atmospheric region. However they all can be studied by a multipurpose remote sensing and in situ payload in the framework of the proposed orbiter mission.2.1 Lower atmosphere and cloud layer (0 – 60 km)Structure. Existing observations of the lower atmosphere hidden below the clouds are limited to in situ measurements, acquired by 16 descent probes mostly in equatorial latitudes, by radiooccultations on previous orbiters (Venera 9, 10, 15, 16, Pioneer Venus, and Magellan), and brief glimpses provided by the Galileo and Cassini fly-bys. The descent probes showed that the temperature structure below 30 km is quite constant all over the planet (Fig. 2.1). However, the temperature structure in the lower scale height is virtually unknown. Mapping the regions of high elevation in sub-micron spectral “windows” at the nightside will determine the surface temperature as a function of altitude (Meadows and Crisp (1996)). Assuming this is equal to the near-surface air temperature, this will allow a determination of the thermal profile and lapse rate in the 0-10 km range and an investigation of its degree of static stability, constraining the dynamics and turbulence in this region. The thermal structure above 35 km altitude will be obtained from radiooccultations with high vertical resolution. Composition. The Venusian atmosphere consists mainly of CO2 and N2 with small amounts of trace gases (Fig. 2.1). Although there is very little observational data, the chemistry of the lower atmosphere is expected to be dominated by the thermal decomposition of sulfuric acid, and cycles that include sulfur and carbon compounds (SO2, CO, COS etc.) and water vapour.9 Venus Express Mission Definition Report ESA-SCI(2001)6The discovery of the near IR spectral “windows” (Allen and Crawford, 1984), through which thermal radiation from the lower atmosphere leaks to space, allows us to study the composition of the atmosphere below the clouds on the nightside of the planet. The windows at 2.3 and 1.74 µm sound the atmosphere in broad altitude regions centered at 30-35 km and 20 km respectively, while the windows shortward of 1.2 µm (0.85, 0.9, 1.01, 1.10,and 1.18 µm) probe the first scale height and the surface. The detailed appearance of the windows results from the combined effect of composition, cloud opacity, and thermal structure, including the surface temperature (Taylor et al., 1997). Highresolution observations covering all windows simultaneously, along with physical cloud models, should allow retrieval of all the variables.Figure 2.1 Structure and main parameters of the lower atmosphere of Venus.Water vapour is important not only for chemistry but also as a greenhouse gas. The few existing measurements of the H2O abundance in the deep atmosphere show no evidence for variability so far. By mapping simultaneously at several wavelengths, corresponding to radiation originating at different altitudes, it will be possible to probe the H2O profile below the clouds and to search for possible spatial variations, including those that might be the signature of volcanic activity. A precise inventory is also needed to better constrain the origin of the present atmospheric water. The H2O abundance at the surface has strong implications for the stability of some hydrated rocks. Carbon monoxide is very abundant in the upper atmosphere due to the dissociation of CO2 by solar ultraviolet radiation. It is much less common in the troposphere, but it does there show a definite trend of increasing from equator to pole. The source near the poles could be the downward branch of a Hadley cell transporting CO-rich air from the upper atmosphere, an important diagnostic of the mean meridional circulation. More detailed observations of CO at all levels, latitudes and times are needed to confirm this hypothesis and reveal details of the global-scale dynamics. CO is also a key player in the equilibrium between surface minerals and the atmosphere. The study of the lower atmosphere composition by means of spectroscopy in the near IR transparency “windows” is one of the main goals of the Venus Express mission. More specific objectives include abundance measurements of H2O, SO2, COS, CO, H2O, HCl, and HF and their horizontal and vertical (especially for H2O) variations, to significantly improve our understanding of the chemistry, dynamics, and radiative balance of the lower atmosphere, and to search for localized volcanic activity. Cloud layer. Venus is shrouded by a 20 km thick cloud layer whose opacity varies between 20 and 40 in the UV, visible and infrared (Fig. 2.1). The clouds are almost featureless in visible light but display prominent markings in the UV-blue spectral region (Fig. 2.2). Earlier observations showed that at least the upper cloud consists of micron size droplets of 75% H2SO4, which is produced by photochemical reactions at the cloud tops. The physical and chemical processes forming the lower clouds are virtually unknown, including major problems like (1) the nature of the UV-blue absorber which produces the features observed from space and absorbs half of the energy received by the10 Venus Express Mission Definition Report ESA-SCI(2001)6planet from the Sun, and (2) the origin of the large solid particles detected by the PioneerVenus probe. The remote sensing instruments on Venus Express will sound the structure, composition, dynamics, and variability of the cloud layer, including: • Cloud and haze structure and opacity variations; Distribution and nature of the UV• blue absorber; • Measurements of atmospheric composition which constrain models of cloud formation and evolution. Greenhouse effect. The high surface temperature of about 735 K results from the powerful greenhouse effect created by the presence of sulphuric acid clouds and certain Figure 2.2 Venus images in the violet filter taken gases (CO2, H2O, SO2) in the atmosphere by the Gallileo spacecraft (see Crisp and Titov, 1997). Less than 10% of the incoming solar radiation penetrates through the atmosphere and heats the surface, but thermal radiation from the surface and lower atmosphere has a lower probability of escape to space due to the strong absorption by gas and clouds. The result is about 500K difference between the surface temperature and that of the cloud tops, an absolute record among the terrestrial planets (Fig. 2.1). The measurements of outgoing fluxes over a broad spectral range, combined with temporarily and latitudinally resolved cloud mapping and high resolution spectroscopy in the near IR windows will give an insight into the roles of radiative and dynamical heat transport, and the various species, in the greenhouse mechanism. Atmospheric dynamics. The dynamics of the lower atmosphere of Venus is mysterious. Tracking of the UV markings, descent probes, and Vega balloons trajectories all showed that the atmosphere is involved in zonal retrograde super-rotation with wind velocities decreasing from ~100 m/s at the cloud tops to almost 0 at the surface (Fig. 2.3). At the same time, there appears to be a slower overturning of the atmosphere from equator to pole, with giant vortices at each pole recycling the air downwards. What is most puzzling about the regime represented by this scenario is how the atmosphere is accelerated to such high speeds on a slowly-rotating planet. Additional questions include (1) whether the meridional circulation is one enormous 'Hadley' cell extending from the upper atmosphere to the surface, or a stack of such cells, or something else altogether; (2) how the polar vortices couple the two main components of the global circulation and why they have such a complex shape and behaviour; and (3) what the observed (and observable) distributions of the minor constituents in Venus' atmosphere, including the clouds, are telling us about the motions (Fig.2.4). All attempts to model the zonal superrotation have been unsuccessful so far, indicating that the basic mechanisms of the phenomenon are unclear. There is an even Figure 2.3 Zonal winds in the Venus atmosphere。

observations中文翻译

observations中文翻译"Observations"的中文翻译可以是"观察"、"观测"或者"观察结果"。

以下是一些关于"observations"的中英文对照例句和用法：1. The scientist made detailed observations of the bird's behavior. 科学家对鸟的行为进行了详细的观察。

2. Her observations led to significant discoveries in the field of astronomy. 她的观测结果在天文学领域带来了重大的发现。

3. The teacher asked the students to write down their observations during the experiment. 老师要求学生们在实验过程中记录下观察结果。

4. Through careful observations, the researchers were able to identify a new species of insect. 通过仔细观察，研究人员成功鉴定了一种新的昆虫物种。

5. The police officer's observations were crucial in solving the crime. 警察的观察结果对破案起到了关键作用。

6. The book contains a collection of observations about human behavior. 这本书收集了关于人类行为的观察。

7. The scientist used a microscope to make magnified observations of the cells. 科学家使用显微镜对细胞进行放大观察。

Stellar Populations and Variable Stars in the Core of the Globular Cluster M5

a rXiv:as tr o-ph/9711152v113Nov1997STELLAR POPULATIONS AND V ARIABLE STARS IN THE CORE OF THE GLOBULAR CLUSTER M51Laurent Drissen D´e partement de Physique and Observatoire du Mont M´e gantic,Universit´e Laval,Qu´e bec,QC,G1K 7P4Electronic mail:ldrissen@phy.ulaval.ca and Michael M.Shara Space Telescope Science Institute,3700San Martin Drive,Baltimore,Maryland 21218Electronic mail:mshara@ ABSTRACT We report the discovery of a variable blue straggler in the core of the globular cluster M5,based on a 12-hour long series of images obtained with the Planetary Camera aboard the Hubble Space Telescope .In addition,we present the light curves of 28previously unknown or poorly studied large-amplitude variable stars (all but one are RR Lyrae)in the cluster core.A (V,U-I)color-magnitude diagram shows 24blue stragglers within 2core radii of the cluster center.The blue straggler population is signiﬁcantly more centrally concentrated than the horizontal branch and red giant stars.1.IntroductionGlobular cluster cores are being imaged intensively with the Hubble Space Telescope, and continue to yield surprises.The realizations that blue stragglers are commonplace,red giants are depleted,and that horizontal branch populations may depend on core properties has spurred on observers in the pastﬁve years.As part of our program to study the dis-tributions of blue stragglers and variable stars in globular cores,we have now imaged NGC 5904=M5.The globular cluster M5harbors one of the richest collections of RR Lyrae stars in the Galaxy.It is also home to one of only two known dwarf novae in Galactic globular clusters. Until now,however,not a single blue straggler candidate has been identiﬁed in M5.Is this because none exist,or because blue stragglers reside only in the(until now unobservable) core of M5?In section2we describe the observations and reductions;the CMD of the core of M5is presented in section3.The variable stars weﬁnd are described in section4while our results are summarized in section5.2.Observations and reductions2.1.Search for variable starsA series of twenty-two600-second exposures of M5’s central(r≤50′′)region,spanning11.5hours,was obtained on March21,1993with the Planetary Camera(PC)aboard the Hubble Space Telescope(HST)before the repair mission.The F336Wﬁlter,similar to the Johnson U bandpass(Harris et al.al.1991),was used for the observations.Standard cali-bration(bias and dark subtraction,ﬂatﬁeld correction)was performed with STScI software within IRAF/STSDAS.The detection of variable stars was performed as follows.First,the22individual images were combined with IRAF’s combine task(with the crreject option)to create a deep image. This image is shown in Figure1.The individual images were remarkably well aligned with each other,so no shift was necessary.DAOPHOT’s Daoﬁnd algorithm(Stetson1987)was then used to build a masterlist of3144stars visible in the deep image.In order to eliminate the numerous cosmic rays,which are very diﬃcult to remove on single frames,the22individual images were combined two by two(again with the combine task and the crreject option),with an overlap of1(image1+image2,image2+image3,...).Aperture photometry with an aperture radius of4pixels(0.17′′),and a sky annulus with inner and outer radii of10and15pixels was then performed on the21resulting images, using the masterlist of stars previously found.The standard deviation from the mean in the 21frames was then computed for all stars;this resulted in the discovery(or re-discovery)of 29variable stars,which will be discussed in section4.Note that since for any given star the conditions(PSF,ﬂatﬁeld,star location,aperture, background)are virtually identical from frame to frame(with the exception of faint stars near bright,large amplitude variables),the relative photometry from frame to frame is expected to be much more precise than the relative photometry among stars within the same frame (mostly because of PSF variations which induce position-dependent aperture corrections and overlapping PSFs in a crowdedﬁeld).While the relative error from one star to the next within a single frame can be as large as0.2mag(if simple aperture photometry is used), even for bright stars,the typical standard deviation from the mean of the21frames for a given non-variable star is less than0.05mag at U=17.5,and reaches0.1mag at the cluster main sequence turnoﬀ.2.2.The color-magnitude diagramIn order to study the stellar populations in M5,a70second F555W(equivalent of Johnson Vﬁlter;Harris et al.1991)and a70second F785LP(comparable to I)PC images were retrieved from the HST archives.Both images were obtained on December27,1991. Fortunately,the center of these frames is only∼8′′away from the center of our images (the totalﬁeld of view of the4PC CCDs is70′′),so most stars detected in our F336W images are also located in the archive frames;the area common to all three sets of images is∼1.1arcmin2.Stellar photometry was performed in the most simple way on these frames:aperture photometry(with the same parameters as above)was performed on the deep,combined F336W frame using the masterlist.After proper shift and rotation of the coordinates,the same masterlist was used to obtain aperture photometry of the stars in the F555W and F785LP images.Although PSF-ﬁtting techniques are known to improve the photometric accuracy(especially at the faint end of the luminosity function and near bright stars;see Guhathakurta et al.1992for a detailed discussion),simple core aperture photometry gives results which are reliable enough(typicallyσ∼0.2mag above the turnoﬀ) for our purpose.A total of2153stars have been included in the color-magnitude diagram discussed below.Aperture corrections and photometric zero-points determined by Hunter et al.(1992) were used to calibrate the magnitudes and colors of the stars.Moreover,the absolute sen-sitivity of the CCDs is known to decrease slowly with time following each decontamination (Ritchie&MacKenty1993);this eﬀect was taken into account.As a consistency check,the photometric calibration was compared with ground-based data.The average F555W and F336W magnitudes of the RR Lyrae stars are F555W RR= 15.2and F336W RR=15.55,while Buonanno et al(1981)ﬁnd V RR=15.13and Richer& Fahlman(1987)obtained U HB=15.6.The agreement is excellent.3.Stellar PopulationsThe color-magnitude diagram for the2153stars located in the area common to the F336W(U),F555W(V)and F785LP(I)frames is shown in Figure2.In this plot,variable stars(see next section)are identiﬁed with special symbols;seven of29variables found in the F336W frames are located outside the F555W and F785LPﬁeld of view,and are therefore not included in Figure2.Photometry is fairly complete down to∼0.5magnitude below the turnoﬀ.The large wavelength diﬀerence between the U and Iﬁlters compensates for the relatively poor photometric accuracy,and allows us to clearly deﬁne the stellar populations. Two characteristics of the CMD are worth noting:the signiﬁcant blue straggler population and the morphology of the horizontal branch.3.1.Blue StragglersThe boundaries of the BS region of the CMD have often been arbitrarily deﬁned,vary from author to author,and also depend on theﬁlters used.As emphasized by Guhathakurta et al.(1994),the(V,U-I)CMD is well suited to deﬁne the blue straggler population.As a working deﬁnition,we decided to include in the BS region of the(V,U-I)CMD all stars signiﬁcantly brighter(0.4mag)than the turnoﬀand bluer than the average main sequence at the turnoﬀlevel;twenty-four stars are included in this region of the CMD(surrounded by dotted lines in Figure2)and can be considered as blue stragglers.Such a signiﬁcant blue straggler population in the core of M5is in striking contrast to the outer regions of the cluster, where none have been found(Buonanno et al.1981,for2′≤r obs≤5.6′;Richer&Fahlman 1987,for3′≤r obs≤25′).Recent CCD observations of the central regions of M5(Brocato et al.(1995);Sandquist et al.(1996))also reveal some blue stragglers.The two-dimensional distribution of red giants,horizontal branch stars and blue stragglers is shown in Figures 3a-c.It is obvious from these plots that the BS population is preferentially concentrated in the very core of the cluster.This is quantiﬁed in Figure4a,which shows the cumulativedistribution of the diﬀerent stellar populations within the inner50′′,and in Figure4b,within one core radius(24′′).A simple K-S test showed that there is a99.5%probability that the blue stragglers in the core of M5are more centrally concentrated than the horizontal branch stars,and a97.5%probability that they are more centrally concentrated than the red giants.This tendency for blue stragglers to be more centrally concentrated than other cluster members has been noted for most globular clusters observed to date(see Sarajedini(1993), Yanny et al.1994and references therein),and is consistent with the hypothesis that BS are more massive than main sequence stars.The luminosity-inferred lifetime of the shortest-lived,most luminous blue straggler in the core of M5is∼5×108yrs,assuming it lies on the hydrogen-burning main sequence. This corresponds to the star with V=16.0,L∼25L⊙and M∼2.15M⊙.The relaxation time in the core of M5is T rc=2×108yrs(Djorgovski1993).Hence,all BS in the core of M5are expected to be dynamically relaxed.Thus,the radial distribution of the BS is, indeed,a direct probe of their masses.In order to compare the blue straggler population from cluster to cluster,Bolte,Hesser &Stetson(1993)have deﬁned the speciﬁc frequency,F BS,as the ratio of the number of blue stragglers to the total number of stars brighter than2magnitudes below the horizontal branch at the instability strip.In the case of the central region of M5(area in common to the U,V and I HST/PC frames),where V HB=15.2,24F BS=other clusters.He suggests that gaps may provide important constraints on mixing in earlier stages of stellar evolution.We see no evidence that the gap width changes between the inner and outer parts of the core.4.Variable StarsFigure5shows the standard deviation as a function of the average U magnitude for all the stars in the F336W frames.The usual problem with outliers in Figure5(due to mismatches in star lists)was almost completely avoided because(a)the same master list for all frames(see section2.1),and(b)all images were perfectly aligned with each other.Visual inspection of the few remaining outliers immediately showed them to be mismatches and they were eliminated from our photometry.Stars with RMS magnitude of variability higher than2sigma above the mean curve were considered possible variables and were examined more closely.Most of them were faint stars located close to bright,large-amplitude variables. Twenty-eight stars stand out as bright,large-amplitude variables in Figure5,as well as one fainter,low-amplitude variable star.Seven of these variable stars had never been identiﬁed previously,and two(HST-V20and V21)were considered as a single star.All but one of the large-amplitude variables have light curves typical of RR Lyrae stars,whereas the low-amplitude variable is a blue rmation on the variables,including cross-identiﬁcation with previous papers,is presented in Table1.We note that the cataclysmic variable V101is36′′North and282′′West of the center of M5and is therefore too distant to have been included in theﬁeld of view of the Planetary Camera(70′′×70′′).4.1.A Variable Blue StragglerOf24blue stragglers identiﬁed in Figure2,only one(HST-V28)shows evidence for variability above the noise level.Although only HST-V28showed up above the2-sigma variability level in Figure5,we have examined the light curve of every blue straggler and compared them with those of nearby stars of similar magnitude in order toﬁnd possible variations undetected by our technique;no new variable showed up.But because the noise level is still relatively high between V=17and V=18(the2σvariability level varies from0.06 to0.12,corresponding to amplitudes∼0.2-0.3mag),we cannot exclude the possibility that some blue stragglers are actually small amplitude variables.The color-magnitude diagram(Figure2)shows that HST-V28is the bluest,and one of the brightest blue stragglers in M5(with M V=+2.2).Figure6shows its light curve,along with light curves of3nearby comparison stars of the same magnitude.HST-V28is obviously variable,with an amplitude∆U≥0.15mag.Unfortunately,our data do not allow us to determine the period with any precision(or even to determine if the variations are periodic).Phase dispersion minimization algorithms favor a periodicity of the order of ∼15hours(in which case this star could be an eclipsing binary),but cannot completely exclude periods shorter than∼1.9hours(typical for pulsating blue stragglers in clusters; Mateo1993).Better photometric accuracy and temporal sampling are obviously necessary to determine the period and nature of HST-V28.Guhathakurta et al.(1994)recently discovered2variables among the28blue stragglers in the core of M3.Both have photometric amplitudes∼0.4mag and periods∼6-12hours. Guhathakurta et al.suggest that both stars are dwarf cepheids.4.2.RR Lyrae StarsAmong the97genuine variables listed in Sawyer-Hogg’s(1973)catalogue,93are RR Lyrae.Recently,Kalda et al.(1987)and Kravtsov(1988,1992)searched for new variables in the central,crowded region of the cluster and found30more.So far,the light curves of only two of these new variables have been published(Kravtsov1992).A recent review of the M5RR Lyrae population has been published by Reid(1996).The U-band light curves of all RR Lyrae stars found in the HST images are shown in Figure7.Tentative periods have been determined for the9type RRc stars with a phase dispersion minimization algorithm,and the results are presented in Table1.The periods of RRab stars are too long to be determined from our observations alone.4.3.HST-V1Eclipsing binary stars are common in the periphery of M5’s core(Reid1996,Yan&Reid 1996),but star HST-V1is unique among the variables found in the core of M5.Although our observations do not cover an entire cycle(P∼0.55d−0.65d),the light curve suggests that HST-V1is a contact(or semi-detached)binary.The secondary minimum is very asymmetric, somewhat reminiscent of the near-contact binary V361Lyrae(Kaluzny1990).The strong asymmetry of the light curve of V361Lyr,more pronounced at shorter wavelengths,is thought to be caused by the presence of a hot spot on the secondary star resulting from the high mass transfer rate from the primary star.Unfortunately,HST-V1lies outside the boundaries of the F555W and F785LP frames, so its color cannot be determined.But with an average magnitude of U=15.7,HST-V1is more than two magnitudes brighter than the turnoﬀ;if it is a cluster member,at least one of its components must be a giant.5.SummaryThe main results of our paper can be summarized as follows:(1)The core of M5contains a highly centrally concentrated population of blue stragglers, similar in size to that found in47Tuc(Paresce et al.1991).(2)Of24blue stragglers detected in the HST images,only one shows signiﬁcant vari-ability above the noise level.Since our data are not sensitive enough to detect variables of amplitude≤0.2mag in the V=17-18range,we cannot exclude the possibility that some blue stragglers may be variable below that level.A more sensitive search with the refurbished HST is highly desirable.(3)We conﬁrm the existence of a0.2mag gap in the color-magnitude distribution of the horizontal branch,ﬁrst noted by Brocato et al..The nature of this gap is still unknown.(4)We have presentedﬁnding charts and light curves for27RR Lyrae variables and one probable contact binary.Among those variables,seven were previously unknown and21 had no published light curve.Support for this work was provided by NASA through grant number GO-3872from the Space Telescope Science Institute,which is operated by the Association of Universities for Research in Astronomy,Inc.,under NASA contract NAS5-26555.REFERENCESBolte,M.,Hesser,J.E.,&Stetson,P.B.1993,ApJ,408,L89Brocato,E.,Castellani,V.,&Ripepi,V.1995,AJ,109,1670Buonanno,R.,Corsi,C.E.,&Fusi Pecci,F.1981,MNRAS,196,435Djorgovski,S.G.1993,in Structure and Dynamics of Globular Clusters,ASP Conf.Ser., Vol.50,S.G.Djorgovski and G.Meylan,eds.,p.373Guhathakurta,P.,Yanny,B.,Schneider,D.P.,&Bahcall,J.N.1992,AJ,104,1790Guhathakurta,P.,Yanny,B.,Bahcall,J.N.,&Schneider,D.P.1994,AJ,108,1786 Harris,H.C.,Baum,W.A.,Hunter,D.A.,&Kreidl,T.J.1991,AJ,101,677Hesser,J.E.1988,IAU Symposium No.126,eds.J.E.Grindlay and A.G.Davis Philip,p. 65Hunter,D.A.,Faber,S.M.,Light,R.,&Shaya,E.1992,in Wide Field/Planetary camera Final Orbital/Science veriﬁcation Report,ed.S.Faber(STScI,Baltimore),chap.12 Kaluzny,J.,1990,AJ,99,1207Kaluzny,J.,&Shara,M.M.1987,ApJ,314,585Kravtsov,V.V.,1988,Astron.Tsirk.,1526,6Kravtsov,V.V.,1992a,Sov.Astron.Lett.18(4),246Kravtsov,V.V.,1992b,Sov.Astron.Lett.17(6),455Kadla,Z.I.,Gerashchenko,A.N.,Jablokova,N.V.,&Irkaev,B.N.,Astron.Tsirk.,1502, 7Mateo,M.1993,in Blue Stragglers,ed.R.A.Saﬀer(ASP Conf.Ser.53),p.74 Paresce,F.,Meylan,G.,Shara,M.M.,Baxter,D.,&Greenﬁeld,P.1991,Nature,352,297 Reid,N.1996,MNRAS,278,367Richer,H.B.,&Fahlman,G.G.1987,ApJ,316,189Sarajedini,A.1993,in Blue Stragglers,ASP Conf.Ser.,vol.53,ed.R.E.Saﬀer,p.14 Sawyer-Hogg,H.,1973,D.D.O.Pub.,Vol3.,No.6Yan,L.&Reid,I.N.1996,MNRAS,279,751Yanny,B.,Guhathakurta,P.,Schneider,D.P.,&Bahcall,J.N1994,ApJ,435,L59Fig.1.—Full HST/PCﬁeld of view(70′′×70′′)of the central region of M5.This image is the average of twenty-two F336W(U-band)exposures.Variable stars and the cluster center are identiﬁed.-2-1012342019181716151413U-I Fig.2.—Color-magnitude diagram for the stars common to the U (F336W),V(F555W)and I(F785LP)frames.RR Lyrae stars,and the variable blue straggler are shown with special symbols.050010001500050010001500Fig. 3.—Distribution of the red giants,horizontal branch stars and blue stragglers in the V frame coordinate system.The location of the U images is shown.The cluster center is identiﬁed by a cross.The circle has a radius of 20′′(∼one core radius).050010001500050010001500Fig.3.—continued050010001500050010001500Fig.3.—continuedFig.4a.—(a)Cumulative distribution of the stellar populations (BS:Blue Stragglers;HB:Horizontal Branch stars;RG:Red Giants)in the inner 50′′region of M5;(b)same as (a),but within one core radiusFig.5.—The RMS magnitude of variability as a function of the F336W magnitudes for the stars in the21frame set.The line is the2σcutoﬀ,above which the stars were considered as candidate variables and examined more closely.Genuine variables are shown with specialsymbols.Fig.6.—Light curve of HST-V28,the variable blue straggler and of three nearby(∆d≤5′′)comparison stars of similar mean magnitudeFig.7.—Light curves(ﬁlter F336W∼U-band)of the large amplitude variable stars found in the core of M5.All but one(HST-V1)are RR Lyrae stars.Fig.7.—ContinuedFig.7.—ContinuedFig.7.—Continued。

国外知名财务学家（中文）-2-斯蒂芬罗斯

斯蒂芬·罗斯（Stephen A. Ross）教授斯蒂芬·罗斯(Stephen A. Ross)，因其创立了套利定价理论(Arbitrage Pricing Theory，简称APT)而举世闻名,是当今世界上最具影响力的金融学家之一。

斯蒂芬·罗斯生于1944年，1965年获加州理工学院物理学学士学位，1970年获哈佛大学经济学博士学位。

罗斯担任过许多投资银行的顾问，其中包括摩根保证信托银行、所罗门兄弟公司和高盛公司，并曾在许多大公司担任高级顾问，诸如AT＆T和通用汽车公司等；罗斯还曾被聘为案件的专业顾问，诸如AT＆T公司拆分案、邦克-赫伯特公司(Bunker and Herbert)陷入白银市场的诉讼案等；另外，罗斯担任过一些政府部门的顾问，其中包括美国财政部、商业部、国家税务局和进出口银行等；罗斯还曾任美国金融学会主席(1988年)、计量经济学会会员、宾夕法尼亚大学沃顿商学院经济与金融学教授、耶鲁大学经济与金融学Sterling讲座教授。

由于对金融理论的杰出贡献，罗斯获得了许多学术荣誉，包括国际金融工程学会(IAFE)最佳金融工程师奖、金融分析师联合会葛拉汉与杜德奖(Graham and Dodd Award)、芝加哥大学商学院给最优秀学者颁发的利奥·梅内姆奖(Leo Melamed Award)、期权研究领域的Pomerance奖；投资管理与研究学会(AIMR)授予罗斯的尼古拉斯-摩罗德乌斯基奖(Nicholas Molodvsky Awar d)，是一个奖励“改变了某专业的方向并使之达到更高领域所作出的杰出贡献”的奖项；1999年，罗斯在《金融与数量分析杂志》(JFQA)第三期发表的论文“额外风险：再论萨缪尔森的大数谬论”获得JFQA1999年度威廉·夏普奖(William Sharpe Award)(该奖项用于奖励那些在《金融与数量分析杂志》上发表文章、为金融理论作出杰出贡献的研究者)。

学术英语社科unit3 A翻译

1、失去一份工作可能是最痛楚的经济事件在一个人的生活。

大多数人们依托自己的劳动收入来维持他们的生活标准,许多人会从他们的工作取得的不仅是收入，还有自己的成绩感。

一个失去工作意味着此刻要定一个更低的生活标准,焦虑以后,并丧失自尊心。

这并非奇怪,因此,政治家竞选办公室常常谈论他们所提出的政策将帮忙制造就业机遇。

2、尽管必然程度的失业是不可幸免的，在一个复杂的经济与成千上万的企业和以百万计的工人，失业量的转变大致随着时刻的推移和席卷整个国家。

当一国维持其尽可能充分就业的工人，它实现了更高水平的国内生产总值会比留下了很多工人闲置更好。

3、失业问题一样分为两类，长期的问题和短时间的问题。

经济的自然失业率一般是指充分就业状态下的失业率。

周期性失业是指今年年失业率围绕其自然率的波动，它是紧密相关的经济活动的短时间起伏。

4、判定失业问题有何等严峻时，其中一个问题确实是要考虑是不是失业一般是一个短时间或长期的条件。

若是失业是短时间的，人们可能会得出结论，它不是一个大问题。

工人可能需要几个礼拜的工作之间找到最适合他们的口味和技术的开口。

但是，若是失业是长期的，人们可能会得出结论，这是一个严峻的问题。

许多个月的失业工人更易蒙受经济和心理上的困难。

5、经济引发一些失业的缘故之一是寻觅工作。

求职是工人与适合的职位相匹配的进程。

若是所有工人和所有工作一样，使所有工人，一样适用于所有作业，求职就可不能是一个问题。

下岗职工会专门快找到新的工作，超级适合他们。

可是，事实上，工人有不同的方式和技术,职位有不同的属性，在经济生活中众多的企业和家庭关于应聘者和职位空缺的信息缓慢传播。

6、摩擦性失业往往是在不同企业之间的劳动力需求转变的结果。

当消费者决定，他们更喜爱富士通而不是宏碁，富士通增加就业职位，宏碁就辞退工人。

前宏碁的工人必需寻觅新的就业机遇，而富士通必需决定招聘新工人开辟了各类作业。

这种转变的结果是一段时刻的失业。

7、一样，由于不同地域的国家生产不同的商品，在一个地区就业增加，在另一个减少。

甲泼尼龙联合吗啡缓解终末期肺癌呼吸困难的临床观察

- 126 -[16]严诚，黄健峰，张利军，等.基于工作站的CT-FFR 对评估冠状动脉功能性狭窄的临床初步探究[J].复旦学报（医学版），2021，48（3）：356-362.[17]丁熠璞，单冬凯，王玺，等.冠状动脉周围FAI 对CT-FFR诊断重度钙化患者冠脉血流动力学异常的增量价值[J].解放军医学杂志，2021，46（7）：666-672.[18]赵润涛，窦冠华，王凡，等.基于人工智能动态CT 心肌灌注成像分析技术的临床应用研究[J].国际医学放射学杂志，2021，44（5）：529-534.[19]祁冬，何兴义，姚木子，等.基于冠状动脉CT 血管成像的血流储备分数诊断心肌缺血的研究进展[J].江苏大学学报（医学版），2022，32（1）：88-92.[20]贾艳芳.血清NT-proBNP、Lp（a）水平与急性心肌梗死患者血管狭窄程度的关联性分析[J].河南医学研究，2021，30（17）：3225-3227.（收稿日期：2023-07-06）　（本文编辑：白雅茹）①泰州市中西医结合医院肿瘤科　江苏　泰州　225300通信作者：周建军甲泼尼龙联合吗啡缓解终末期肺癌呼吸困难的临床观察周建军①【摘要】　目的：比较甲泼尼龙联合吗啡与单用吗啡缓解终末期肺癌呼吸困难的临床效果。

方法：选取泰州市中西医结合医院肿瘤科2020年1月—2022年12月收治的80例终末期肺癌呼吸困难患者，根据不同用药方案将其分为对照组与观察组，每组40例。

对照组予以吗啡治疗，观察组予以甲泼尼龙联合吗啡治疗。

对比两组呼吸困难症状[视觉模拟评分法（VAS）评分]、呼吸困难控制起效时间与维持时间、生命体征（心率、呼吸频率）、血氧饱和度及不良反应（呼吸抑制、嗜睡）。

结果：治疗后，观察组的VAS 评分低于对照组，差异有统计学意义（P <0.05）。

观察组呼吸困难控制起效时间早于对照组，维持时间长于对照组，差异均有统计学意义（P <0.05）。

公共管理经典书目

公共管理经典书目（一）基础理论经典原著1、威尔逊：《行政学之研究》，《国外政治学》1987年第6期、1988年第1期。

2、古德诺：《政治与行政》，华夏出版社1987年版。

3、泰罗：《科学管理原理》，中国社会科学出版社1990年版。

4、法约尔：《工业管理与一般管理》，中国社会科学出版社1998年版。

5、马克斯·韦伯：《经济与社会》，商务印书馆1997年版。

6、怀特：《行政学概论》，上海商务印书馆1947年版。

7、西蒙：《管理行为》，北京经济学院出版社1988年版。

8、西蒙：《管理决策新科学》，中国社会科学出版社1982年版。

9、沃尔多：《行政国家：美国公共行政的政治理论研究》，纽约：罗纳德出版社1948年版。

10、林德布洛姆：《决策过程》，上海译文出版社1988年版。

11、德罗尔：《逆境中的政策制定》，上海远东出版社1996年版。

12、雷格斯：《行政生态学》，台湾商务印书馆1985年版。

13、弗雷德里克森：《新公共行政学》，美国亚拉巴马大学出版社1980版。

14、奥斯特罗姆：《美国公共行政的思想危机》上海三联书店1999年版。

15、尼斯坎南：《官僚制与公共经济学》，中国青年出版社2004年版。

16、詹姆斯·Q·威尔逊：《官僚机构：政府机构的作为及其原因》，三联书店2006年版。

17、奥斯特罗姆：《公共服务的制度建构》上海三联书店2000年版。

18、布坎南、塔洛克：《同意的计算：立宪民主的逻辑基础》，中国社会科学出版社2000年版。

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22、罗伯特•登哈特：《公共组织理论》，中国人民大学出版社2003年版。

23、沙夫里茨、海德：《公共行政学经典》，中国人民大学出版社2004年英文版。

The Upsilon Andromedae System Models and Stability

a r X i v :a s t r o -p h /0010279v 1 14 O c t 2000The Upsilon Andromedae System:Models and StabilityTomasz F.Stepinski(tom@ )Renu Malhotra (renu@ )andDavid C.Black (black@ )Lunar and Planetary Institute,3600Bay Area Blvd.,Houston,TX 77058ABSTRACT Radial velocity observations of the F8V star υAndromedae taken at Lick and at Whipple Observatories have revealed evidence of three periodicities in the line-of-sight velocity of the star.These periodicities have been interpreted as evidence for at least three low mass companions (LMCs)revolving around υAndromedae.The mass and orbital parameters inferred for these companions raise questions about the dynamical stability of the system.We report here results from our independent analysis of the published radial velocity data as well as new unpublished data taken at Lick Observatory.Our results conﬁrm the ﬁnding of three periods in the data.Our best ﬁts to the data,on the assumption that these periods arise from the gravitational perturbations of companions in keplerian orbits,is also generally in agreement,but with some diﬀerences,from the earlier ﬁndings.We ﬁnd that the available data do not constrain well the orbital eccentricity of the middle companion in a three-companion model of the data.We also ﬁnd that in order for our best-ﬁt model to the Lick data to bedynamically stable over the lifetime of the star (∼2billion years),the system must have a mean inclination to the plane of the sky greater than 13degrees.The corresponding minimum inclination for the best ﬁt to the Whipple data set is 19degrees.These values imply that the maximum mass for the outer companion can be no greater than about 20Jupiter masses.Our analysis of the stability of the putative systems also places constraints on the relative inclinations of the orbital planes of the companions.We comment on global versus local (i.e.,method of steepest descent)means of ﬁnding best-ﬁt orbits from radial velocity data sets.Subject headings:binaries:spectroscopic—planetary systems—stellar dynamics—stars:individual (υAndromedae)1.IntroductionRadial velocity observations of several hundred nearby main-sequence stars have resulted in the detection to date of roughly forty companions with minimum or projected masses(i.e.,m sin i) less than80M J,where M J is the mass of Jupiter(Marcy and Butler1998;Marcy et al.1999; Vogt et al.2000;Mayor et al.1997).Nearly thirty of these companions have m sin i∼<10M J.The evidence to date typically suggests only one companion per star;however,the data from some of the observational studies have suggested that other companions may be present in some cases but will require longer time bases for the observational record beforeﬁrm conclusions can be established (Cumming1999).Evidence for the presence of multiple low mass companions(LMCs)to a star would be signif-icant for several reasons.A key reason is that it would suggest,at least superﬁcially,a similarity of such a system to our planetary system,and by extension,planetary systems in general.Theﬁrst strong evidence for multiple LMCs to a single star,Upsilon Andromedae(υAnd), was reported recently by Butler et al.(1999)(hereafter referred to as B99).The data presented in that paper are from two independent studies,one conducted at the Lick Observatory and the other conducted at the Whipple Observatory using the Advanced Fiber-Optic Echelle(AFOE) Spectrograph.Earlier observations ofυAnd(Butler et al.1997)had detected a periodicity in the radial velocity data that indicated the presence of a companion with an orbital period of4.6days and a projected mass of∼0.7M J.Those authors noted that the data also contained“evidence for variability in the gamma velocity with timescale of about2yr.”The newer observations(B99) reveal additional periodicities,one in excess of1200days(1269days for the Lick data and1481 days for the AFOE data),as well as one with∼240days.B99have modeled these periodicities as arising from the presence of three LMCs in keplerian orbits aboutυAnd.The eccentricities of the orbits determined by B99are,in order of increasing orbital period,0.042,0.23,and0.36.This three-companion model for the observations raises interesting challenges in understanding the formation and evolution of that system and its possible relationship to systems such as the Solar System.Particular challenges relate to the dynamical stability of such a system and what constraints it might place on physically realizable companion systems,and to how a system consisting of at least three relatively massive objects could form around a star with the orbital structure that is suggested by the data.In an eﬀort to explore these challenges in more detail,we re-examine here the published radial velocity data onυAnd,as well as data taken subsequent to announcement of the results and kindly provided to us by G.Marcy.Section2summarizes the radial velocity data that are used in our analyses.Models for analyzing the radial velocity data are discussed in Section3.The methods that we used forﬁtting the data and the procedures for assessing the merit of thoseﬁts are described in Section4.The best-ﬁt models,assuming that the periodicities are due to companions(i.e.,thatthe model for describing the data is one comprised of a superposition of Keplerian motion)are presented in Section5.We examine the dynamical stability of candidate model systems in Section 6.A summary of our results and conclusions regarding the possible nature of theυAnd system are given in Section7.2.Radial velocity dataWe use three diﬀerent data sets to perform our analysis.Theﬁrst data set was collected at Lick.It contains89observations ofυAnd made between September1987and March1999as part of the Lick survey.We refer to this data set as the original Lick data.The second data set was collected by the AFOE planet search program and contains52observations ofυAnd made between September1994and February1999.We refer to this data set as the AFOE data.Original Lick data and AFOE data are published by B99.Details about these data sets can be found therein. The third data set,referred to as the new Lick data,has been provided to us by G.Marcy.This contains118observations ofυAnd collected at Lick and comprises29observations made between June and August of1999in addition to the original89observations.Note that in this data set the radial velocities for the original89observations have been revised to reﬂect improvement in the data reduction technique.All three data sets have the same form:each record is a triplet(t,V,σ),where t is the time of observation(in Julian days),V is an unaccounted for component of the star’s radial velocity (hereafter referred to as radial velocity)in(m s−1),andσis a measurement error in(m s−1).Bulk properties of radial velocities are consistent among the three data sets.The range of V is−177m s−1 to165m s−1,the mean value of V is−11m s−1to−5m s−1,and the standard deviation is71m s−1 to82m s−1.Measurement errors are of the order of10m s−1,generally smaller for the Lick data than for the AFOE data.It is useful to think about the radial velocity data fromυAnd as a time series,and to pretend that we have no a priori insight into the mechanism that produces it.Theﬁrst step is to calculate the signal’s frequency spectrum.Fig.1(left column)shows the frequency spectrum for all three data sets.Because the observations are not evenly spaced,the frequency spectrum cannot be obtained by means of the FFT,instead we used the Lomb-Scargle periodogram technique(Lomb 1976;Scargle1982;Black and Scargle1982)to obtain standard,zero mean periodograms.These spectra indicate the existence of periodic components in the radial velocity signal from υAnd.Spectral features common to all three data sets exist.The most prominent are peaks at ∼4.617d,∼500d,and∼1200–1500d.However,not all signiﬁcant peaks present in the frequency spectrum actually correspond to real periodicities.A simple test for the reality of periodicities indicated by the frequency spectrum is to fold the signal with suspected periods.Only folds with actual periodicities yield coherent patterns.The fold test provides deﬁnitive aﬃrmation,but,in the presence of multiple periodicities it does not necessarily provide deﬁnitive disaﬃingthe fold test we can conﬁrm the authenticity of the∼4.617d and∼1200–1500d periodicities.The ∼500d feature,which in fact can be shown to be an alias(e.g.B99),fails the fold test.These three features are the only signiﬁcant periodicities in the frequency spectrum of the original Lick data set.Additional signiﬁcant features are present in the periodogram of the new Lick data set.The most prominent are located at∼141d,∼14d,and∼230d.They all fail the fold test.The periodogram of the AFOE data set also shows additional signiﬁcant peaks.The most prominent peak is located at∼29d and is aﬃrmed by the fold test.In addition,peaks at ∼145d and∼245d,the locations close to those identiﬁed on the periodogram for the new Lick data set,are present,but they fail the fold test.This preliminary analysis of radial velocity signal fromυAnd indicates existence of two peri-odicities,one at∼4.617d,and another at∼1200to∼1500d.This conclusion holds for all three data sets.Therefore,we can conﬁdently postulate that the radial velocity signal fromυAnd is due to the motion of the star caused by the existence of two companions,having orbital periods of∼4.617d and∼1200−1500d.A model consisting of three companions cannot be conﬁdently postulated on the basis of the frequency spectra of the radial velocity signal.However,if such a model is postulated,the third companion should have a period of either∼145d or∼230–245d in order to be consistent with both the new Lick data and the AFOE data.In the AFOE data set,a periodicity of∼29d can be positively identiﬁed,but it is not detected in the other data sets;it would be interesting to understand its origin.3.ModelsAssume a model consisting of a single companion,labeled B,orbitingυAnd.Such a one-companion model predicts the radial velocity,V mod,B(t),at any given instant of time.The radial velocity signal due to the orbital motion of the star caused by gravitational interaction with a companion is given by the following expression,V mod,B=K[cos(f+ω)+e cosω],(1)where e is the eccentricity of the orbit,f is true anomaly,andωis its argument of the periastron. The semi-amplitude K is proportional to the projected mass of the companion,m sin i,where i is the angle between an observer’s line-of-sight to a star and the normal to the orbital plane of the companion.The true anomaly,f,can be expressed in terms of the eccentric anomaly,u,tan f1+e2.(2)In turn,eccentric anomaly,u,can be linked to time by means of Kepler’s equation,2πwhere P is the period of the companion’s orbit,and T peri is the time of periastron passage.Equations(1)to(3)completely deﬁne the one-companion model,giving the time dependence (albeit in an implicit form)of radial velocity.There areﬁve free parameters in this model:K,P, e,T peri,andω.If we assume two companions,labeled B and D,to orbitυAnd,then,in theﬁrst approximation,the two-companion model is simply given by V mod(t)=V mod,B(t)+V mod,D(t)with individual contributions given by(1).There are10free parameters in the two-companion model. The generalization to a model with an arbitrary number of companions is straightforward.Thus, presupposing that the radial velocity signal fromυAnd is mostly due to gravitational interactions with multiple companions,the N-companion model can be written as followsV mod(t)=Ni=1V mod,i(t)+R(t),(4)where R(t)encapsulates sources of radial velocity signal that cannot be attributed to the presence of companions,but instead are intrinsic to the star.They may,in principle,include pulsation and eﬀects due to the inhomogeneous and dynamic nature of the stellar convective and magnetic patterns.However,in the case ofυAnd,there are arguments against pulsations(B99),leaving convective inhomogeneities as the most likely source of R(t).The surface of a star having a convective zone is inhomogeneous in terms of magneticﬁeld, brightness,as well as vertical motion.These inhomogeneities occur on a variety of length scales and are transient.This phenomenon alone leads to variability of the radial velocity measured from the disk integrated light.Such a variability is referred to as a“jitter.”On short time scales the jitter is intrinsically stochastic.Observations and theoretical arguments can be used to estimate the magnitude of the short-term jitter,but not the actual form of R(t).On long time scales the jitter should be modulated by the dependence of stellar photospheric activity on possible cycles of the large-scale stellar magneticﬁeld.Thus,the long-term character of R(t)should be sinusoidal.ForυAnd,B99quote the magnitude of the short-term jitter to be∼10m s−1.This estimate is based on the work of Saar et al.(1998)who investigated the relationship between the variability of the radial velocity signal(i.e.,jitter,unless the star has companions)and various stellar properties for72stars in the Lick survey.They established empirical relations,deﬁned as the best power-law ﬁts,between the variability,σV,and quantities such as B−V color,stellar rotation period,v sin i, and the fractional Ca II H&Kﬂux.However,inspection ofﬁgures1and2of Saar et al.(1998) shows large scatter of actual data around the empirical relations.Thus,the value10m s−1is only a rough estimate ofυAnd’s jitter;values as large as∼20m s−1cannot be ruled out on the basis of Saar et al.’s diagrams.Keplerian models of the radial velocity signal are deﬁned by R(t)=0.Because the jitter is unavoidable,a keplerian model is always incomplete and does not reﬂect accurately the reality. Thus,we should not expect the keplerian model toﬁt the data accurately within the known in-strumental errors.The long-term modulation of the jitter,if present,should be picked up by thekeplerian model as a“companion”,provided that the period of such modulations is short enough and its amplitude is strong enough.4.Fitting methods and proceduresWe assume that the radial velocity signal fromυAnd is caused by the presence of companions and thus adopt a keplerian model given by(4)with R(t)=0.We useχ2as a merit function to determine values of best-ﬁt parameters:χ2=Mk=1 V k−V mod(t k;a1,···,a5N)the GA.Our typical run had a population size of70–100and evolved for5000–10000generations. We ran30–40separate experiments on each model–data set combination.5.Bestﬁt Keplerian models5.1.Two-companion modelsThe frequency spectra of the radial velocity signal fromυAnd(section2)indicates two periodic components suggesting a two-companion keplerian model.We label the two putative companions B and D,for consistency with B99.In our model each companion is characterized by5parameters, thus the two-companion model has10free parameters to beﬁxed by minimization ofχ2(Eqn.5).Table1summarizes the best-ﬁt two-companion solutions we have found for all three data sets.A description of each best-ﬁt solution is divided into three sections.Theﬁrst section gives the overall properties of theﬁt,the other two sections list values of the best-ﬁt parameters for B and D,respectively.For the sake of compactness,we don’t list values of uncertainties of estimated parameters.Uncertainties are generally about the same as those in B99because we tune all solutions using the LM method.In the properties section weﬁrst list the method used to obtain a given solution.The LM method uses a starting point with orbital periods as indicated by the respective frequency spectra. LM/GA stands for the solution found using the LM method and conﬁrmed using the GA method. In this context,“conﬁrmation”means that the GA method yields the solution“similar”to that obtained by the LM method.Moreover,using the GA solution as a starting point in the LM method recovers the original LM solution.Second,the value ofχ2is listed,together with the value ofχ2red=χ2/L,where L is the number of degrees of freedom(the number of observations,M, minus the number of parameters to beﬁtted);in the case of two-companion models L=M−10. Last,the standard deviation of residuals,labeled as“RMS of residuals”is given.The residuals are the values of V k−V mod(t k),k=1,···,M.Overall the best-ﬁt solutions are quite similar for all three data sets.The LM method failed toﬁnd the best-ﬁt,two-companion solution for the AFOE data.The GA method yields several solutions of comparable“ﬁtness”that can be grouped into two distinct categories.For the AFOE data,Table1lists theﬁttest solution in each category.There are some systematic diﬀerences betweenﬁts to Lick and AFOE data sets,especially with regard to companion D.Fig.2shows observed radial velocities together with their two-companion best-ﬁt models.For compactness, thisﬁgure as well as Figs.3–4cover the period between1992and2000,and do not showﬁve earlier Lick data points.However,all observations are used to obtain the best-ﬁt solutions.It is quite clear from even a visual inspection of Fig.2that the two-companion model does notﬁt the data well.It is expected that the value ofχ2red≈1for a goodﬁt.The values ofχ2red in Table1arein the range from6.41to23.66.This seems to suggest that the two-companion model oﬀers a badﬁt to the data.However,note that theχ2red≈1criterion for the goodness ofﬁt assumes completeness of the model.Any keplerian model is an incomplete model because the stellar jitter is not incorporated into it.Thus,the best-ﬁt solution should not be characterized byχ2red≈1, unless theσjitter≤σinst,whereσjitter andσinst are standard deviations of the jitter signal and an average instrumental error,respectively.The RMS of residuals is in the range from28.3m s−1to 35.07m s−1,much higher than∼10m s−1expected if the residuals were due to instrumental errors alone.This indicates a badﬁt unless the stellar jitter is about26–34m s−1.These are much higher values than10m s−1adopted by B99,but cannot be deﬁnitively excluded on the basis of empirical diagrams of Saar et al.(1998)as discussed in Sect.3.Fig.1(right column)shows the frequency spectrum of residuals left after subtracting the best-ﬁt,two-companion model from the signal.Spectral features common to all three data sets exist and indicate the existence of periodic components in the residuals.The prominent peaks are at∼145d and∼240d.Note that frequency spectrum of residuals left after subtracting the formal best-ﬁt model to the AFOE data shows no features and is inconsistent with Lick data sets results.On the other hand,the“good”ﬁt to the AFOE data leaves residuals with frequency spectra consistent with those produced by the bestﬁts to the Lick data sets,except for an additional periodicity at ∼29d present in the AFOE residuals.The apparent failure of two-companion models toﬁt well the data does not,by itself,necessarily point out to the existence of the third companion;instead,it may reﬂect a presence of the large but feasible jitter.It is the existence of periodic component(s)in the residuals of the two-companion model,rather than the large values of the residuals and ofχ2red,that suggests an additional com-panion(s).5.2.Three-companion modelsWe now consider the keplerian model with three companions labeled B,C,and D,from in-nermost to outermost.Such a model is characterized by15parameters.Table2summarizes the assorted three-companion solutions for all three data sets.Allﬁts were obtained by minimizingχ2 (Eqn.5)with respect to14parameters,the period of the innermost companion,P B,having been ﬁxed for reasons of computational eﬃciency.This is justiﬁed because the periodograms give the value of P B=4.6171d with high accuracy.For each data set four diﬀerent categories of solutions are listed.Theﬁrst is obtained by the LM method starting with P D given by the best-ﬁt,two-companion solution,and P C equal to240d as indicated by the highest peak on the periodogram of residuals left after subtracting the best-ﬁt, two-companion model from the data.Solutions in this category are the overall best-ﬁts.Hereafter we refer to them as the BF solutions.The second category(hereafter referred to as the PC145 solutions)is obtained by the LM method starting with P D given by the best-ﬁt,two-companionsolution,and P C equal to145days as indicated by the second highest peak on the periodogram of residuals left after subtracting the best-ﬁt,two-companion model from the data.The third category (labeled as the SE solutions)are the best-ﬁt solutions subject to the condition that eccentricities of all orbits are≤0.1,and the fourth category(labeled as the SEBC solutions)are the best-ﬁt solutions subject to the condition that eccentricities of B and C orbits are≤0.1.The latter two models,SE and SEBC,were motivated by dynamical stability considerations.The description of each solution in Table2is divided into four sections,theﬁrst section gives the properties of theﬁt, the remaining three sections list values of parameters for companions B,C and D.Fig.3shows the original Lick data together with the fourﬁts listed in Table2.Visual inspection of Fig.3suggests that BF,SEBC,and SE solutions oﬀer comparably goodﬁts to the data,whereas the PC145solution provides a slightly worseﬁt.This impression is conﬁrmed by the values ofχ2in Table2.The RMS of residuals is in the range from∼16.6m s−1for the BF solution,to∼21m s−1 for other solutions.Thus,the BF solution oﬀers a goodﬁt providing that the jitter is gaussian withσjitter≥13m s−1,and other solutions oﬀer a goodﬁt providing thatσjitter≥18.5m s−1.In this context,“goodﬁt”means thatχ2red,recalculated with weightsσk=The character of the solution in each category is consistent amongst all three data sets.In addition,the only signiﬁcant diﬀerence between the BF,SEBC,and SE solutions are the eccentric-ities.Theﬁts to the AFOE data systematically yield a longer period and a larger value of K for companion D than theﬁts to the Lick data.Our bestﬁt to the original Lick data is very similar to that published in B99,and our bestﬁt to the the AFOE data is virtually identical to that published in B99.The new Lick data suggests that future data will not support the PC145and SE models; the BF remains the best model and the SEBC remains a viable model.Three-companion models oﬀer goodﬁts to the data.The periods and amplitudes of all compan-ions,as well as eccentricities for companions B and D,are well constrained by the existing data. However,the eccentricity for companion C is not well constrained by the present data.6.Dynamical stabilityIn a Keplerian model,radial velocity data determineﬁve parameters for each companion, (K,P,e,T peri,ω).The amplitude K is related to the masses and orbital parameters as follows:K=m sin ia(1−e2)1/2,(6)where M⋆and m are the stellar and companion mass,respectively,G is the universal constant of gravitation,and a is the orbital semimajor axis(related to the orbital period P through Kepler’s third law).From these parameters,we can calculate m sin i and a for each companion,provided the stellar mass M⋆is known.The mass ofυAnd is estimated to be1.2—1.4M⊙(Ford1999);following B99, we adopt M⋆=1.3M⊙.From the best-ﬁt models for the new Lick observations and for the AFOE observations(Table2),the sets of parameters needed for orbital dynamics studies are given in Table3.Note that for each of the companions,two orbital parameters—the inclination and the longitude of ascending node—remain undetermined by the radial velocity data.Although the current estimated orbits of the companions are spatially well separated,the (minimum)masses of the companions and the orbital eccentricities of the two outer companions are suﬃciently large that signiﬁcant perturbation of the orbits can be expected due to the mutual gravitational forces amongst the companions.This is illustrated in Fig.6where we show the results of a numerical integration of the equations of motion for this4-body system including all the(point-mass,Newtonian)gravitational forces amongst them,for the best-ﬁt models to the Lick and the AFOE data.(We used a standard second order mixed variable symplectic integrator(Wisdom and Holman1991),with a step size of0.2days;the total energy error in this integration is quasiperiodic and bounded to a few parts in108.)In this integration,we assumed that the orbits are coplanar and edge-on to the line-of-sight.This assumption is not necessarily realistic but it provides a useful ﬁducial case for measuring the eﬀect of departures from coplanarity and edge-on orientation(whichwe explore further below).Theﬁgure shows that the orbital semimajor axes are little perturbed (not unexpected,as all the orbital periods are well separated).However,a remarkable feature of the evolution is that the orbital eccentricities of all companions are perturbed signiﬁcantly on relatively short timescales.The middle companion,C,exhibits the most dramatic perturbation,its eccentricity varying periodically from a maximum(∼0.35in the Lick best-ﬁt model,∼0.28in the AFOE best-ﬁt model)to a minimum near zero;companion D’s eccentricity exhibits a variation with the same period but much smaller amplitude.The period of these variations is about7000yr for the Lick model,and about3500yr for the AFOE model.These eccentricity variations(and corresponding apsidal variations)arise due to a secular interaction between the outer two companions.(See,for example,Brouwer and Clemence(1961).)This interaction can be described approximately as a superposition of two eigenmodes for the evolution of the“eccentricity vector”,(e cosω,e sinω),for each of the companions C and D.The outer companion D’s apsidal rate is dominated by the slowest frequency mode.For the middle companion C,the two modes have nearly equal amplitudes(so that the magnitude of the eccentricity nearly vanishes periodically),and its apsidal motion is limited to the range–90deg to+90deg relative to the apsidal line of companion D.In this context,it is noteworthy that the radial velocity data do not constrain very well the eccentricity of companion C; goodﬁts to the data include models with small values of e C(cf.discussion in the previous section). Interestingly,we have found that the large amplitude oscillation of the eccentricity of C persists in the“goodﬁt”(SEBC)model as well.In Fig.6,we see that in the Lick model the innermost companion,B,also suﬀers a dramatic eccentricity variation,albeit on a longer timescale;however,we consider that this is not“real”because the proximity of companion B to the star would subject it to general relativistic pre-cession that would dominate its secular evolution,suppressing the amplitude of the eccentricity perturbations(see Riviera and Lissauer(2000)).The outer two companions are the most strongly coupled and companion B provides only a very small perturbation to their orbital evolution.It is important to note that the mutual gravitational interactions of the outer two companions is sensitive to their unknown orbital inclinations and relative orientation of their lines of nodes,i.e.,i C,i D andΩD−ΩC.For given values of these,is given byparameters,the relative inclination of the two orbits,φCD=cos i C cos i D+sin i C sin i D cos(ΩD−ΩC).(7) cosφCDThe uncertainties in the other known parameters will also aﬀect the dynamics and stability of the system.Thus,in principle,there is a very large volume of parameter space that needs to be investigated for dynamical studies.Here we conﬁne our discussion to a subset of this parameter space related to the undetermined parameters only.As the long term dynamics and stability of the system is determined largely by the mutual gravitational interactions of the outer two companions,in the numerical investigations described below,we have neglected the presence of the innermost companion.This allows us to use larger。

海王星的简介英语作文

海王星的简介英语作文Neptune is the eighth and farthest planet from the Sun in our solar system. It is a gas giant, similar in composition to Uranus, and is often referred to as an "ice giant" due to its icy mantle and core. Here is an overview of Neptune:Discovery:Neptune was not known to ancient civilizations due to its dimness and slow orbit. It was discovered on September 23, 1846, by German astronomer Johann Gottfried Galle, who observed it based on calculations made by French mathematician Urbain Le Verrier and British mathematician John Couch Adams.Physical Characteristics:Neptune has a diameter of about 49,244 kilometers (30,598 miles), making it the fourth-largest planet bydiameter and the third-largest by mass. Its mass is approximately 17 times that of Earth, and it is slightly smaller than Uranus in diameter but more massive.Atmosphere:Neptune's atmosphere is composed primarily of hydrogen and helium, with traces of methane that give it its blue color. The methane in the atmosphere absorbs red light, giving Neptune its characteristic blue hue. Winds on Neptune are the fastest in the solar system, reaching speeds of up to 2,100 kilometers per hour (1,300 miles per hour) in its equatorial region.Weather and Storms:Neptune experiences some of the most severe weather conditions in the solar system. It has large storms similar to Jupiter's Great Red Spot, the most famous of which is the Great Dark Spot. However, this feature observed by the Voyager 2 spacecraft in 1989 has since disappeared, and other dark spots have been observed in its place. Thesestorms are believed to be driven by internal heat and energy, as well as interactions with Neptune's moons.Moons:Neptune has 14 known moons, the largest and most notable of which is Triton. Triton is unusual because it orbits Neptune in a retrograde direction, meaning it moves opposite to the planet's rotation. It is thought to be a captured Kuiper Belt object due to its retrograde orbit and icy composition. Triton is geologically active, with cryovolcanoes that spew out a mixture of water, ammonia, and nitrogen.Rings:Neptune has a faint ring system composed of dust and debris. Unlike the prominent rings of Saturn, Neptune's rings are much fainter and more difficult to observe. They were first discovered in 1984 during a stellar occultation, and subsequent observations have revealed five main rings named Galle, Leverrier, Lassell, Arago, and Adams.Exploration:Neptune has only been visited by one spacecraft, Voyager 2, which flew by the planet in 1989 as part of its grand tour of the outer planets. Voyager 2 providedvaluable data and images of Neptune and its moons, greatly expanding our understanding of this distant world.In conclusion, Neptune is a fascinating and mysterious planet, with its brilliant blue color, turbulent atmosphere, and intriguing moons and rings. Further exploration and study of Neptune will undoubtedly uncover even more secrets about this distant ice giant.。

observatory词根词缀

observatory词根词缀
【实用版】
目录
1.观测站的历史发展
2."observatory"的词根和词缀含义
3.观测站的功能和应用
正文
观测站，也称为天文台，是进行天文观测和研究的场所。

天文观测作为人类探索宇宙的一种方式，自古以来就有重要地位。

随着科技的发展，观测站的设备和技术也在不断更新，从而为人类提供了更多关于宇宙的宝贵信息。

"observatory"这个词汇来源于拉丁文"observatorius",意为"观察的"，它的词根是"observe"，意为"观察"，词缀是"-atory"，意为"场所"。

从这个词的构成上，我们可以看出，它是一个表示"观察场所"的词汇。

观测站的主要功能是进行天文观测。

天文学家们在这里使用专业的设备，如望远镜、测角仪等，观测天体的位置、运动、亮度等参数，从而研究宇宙的结构、运动规律等。

此外，观测站还进行气象、地球物理、空间科学等多领域的观测和研究。

观测站在科学研究和技术发展中具有重要地位。

它不仅为我们提供了关于宇宙的丰富知识，还推动了光学、电子技术、计算机科学等相关领域的发展。

同时，观测站也是普及科学知识、提高公众科学素养的重要场所。

总的来说，"observatory"这个词汇揭示了观测站的本质，即它是一个进行观察和研究的场所。

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好奇绘制星图的英语作文

Curiosity has always been a driving force behind human progress and exploration. The desire to understand the cosmos has led us to develop various tools and techniques to map the stars and planets in our universe.One such technique is the creation of star charts, which are visual representations of the night sky.A star chart is a map of the celestial sphere,showing the positions of stars and other celestial objects as seen from Earth.These charts are essential for astronomers and stargazers alike,as they provide a reference for identifying and locating celestial bodies. The process of creating a star chart involves several steps,each of which requires patience,precision,and a deep understanding of the night sky.Firstly,one must choose the appropriate time and location for star observation.The best time to create a star chart is during a clear night with minimal light pollution.The observer should also be familiar with the celestial coordinates,which are used to pinpoint the exact location of stars and other celestial objects.Once the observation conditions are set,the next step is to gather the necessary tools.A telescope or a pair of binoculars can be used to magnify the view of the night sky.A compass and a protractor are also essential for determining the direction and angle of the celestial objects.Additionally,a notebook or a digital device can be used to record the observations.The actual process of creating a star chart involves several stages.The observer should start by identifying the most prominent stars and constellations in the sky.These can be used as reference points for mapping the surrounding stars.The observer should then proceed to draw the outlines of the constellations,labeling each star with its name or a corresponding symbol.As the observer becomes more familiar with the night sky,they can start to include more details in their star chart.This may include the relative brightness of the stars,as well as the color and type of each celestial object.The observer can also add notes about any interesting phenomena they observe,such as meteor showers or the movement of planets.One of the most important aspects of creating a star chart is accuracy.The observer must ensure that the positions of the stars and constellations are accurately represented.This can be achieved by using a star chart template or a celestial atlas as a reference.The observer should also doublecheck their measurements and calculations to minimize errors.In addition to accuracy,the observer should also strive for consistency in their star chart. This means using the same symbols and labels throughout the chart,as well asmaintaining a consistent scale and level of detail.This will make the chart easier to read and interpret,both for the observer and for others who may use the chart in the future.Creating a star chart is not only a valuable skill for astronomers and stargazers but also a rewarding and educational experience.It allows individuals to develop a deeper understanding of the night sky and to appreciate the beauty and complexity of the cosmos. Moreover,it fosters a sense of wonder and curiosity,encouraging us to continue exploring and learning about the universe around us.In conclusion,the process of creating a star chart is a fascinating journey that combines observation,precision,and creativity.It requires patience,dedication,and a keen interest in the night sky.By following the steps outlined above,anyone can create their own star chart and embark on a personal exploration of the cosmos.。

考研英语阅读理解思路透析和真题揭秘（35）

2005年Text 2 Do you remember all those years when scientists argued that smoking would kill us but the doubters insisted that we didn’t know for sure? That the evidence was inconclusive, the science uncertain? That the antismoking lobby was out to destroy our way of life and the government should stay out of the way? Lots of Americans bought that nonsense, and over three decades, some 10 million smokers went to early graves. There are upsetting parallels today, as scientists in one wave after another try to awaken us to the growing threat of global warming. The latest was a panel from the National Academy of Sciences, enlisted by the White House, to tell us that the Earth’s atmosphere is definitely warming and that the problem is largely man-made. The clear message is that we should get moving to protect ourselves. The president of the National Academy, Bruce Albert, added this key point in the preface to the panel’s report "Science never has all the answers. But science does provide us with the best available guide to the future, and it is critical that our nation and the world base important policies on the best judgments that science can provide concerning the future consequences of present actions." Just as on smoking, voices now come from many quarters insisting that the science about global warming is incomplete, that it’s OK to keep pouring fumes into the air until we know for sure. This is a dangerous game: by the time 100 percent of the evidence is in, it may be too late. With the risks obvious and growing, a prudent people would take out an insurance policy now. Fortunately, the White House is starting to pay attention. But it’s obvious that a majority of the president’s advisers still don’t take global warming seriously. Instead of a plan of action, they continue to press for more research -- a classic case of "paralysis by analysis." To serve as responsible stewards of the planet, we must press forward on deeper atmospheric and oceanic research. But research alone is inadequate. If the Administration won’t take the legislative initiative, Congress should help to begin fashioning conservation measures. A bill by Democratic Senator Robert Byrd of West Virginia, which would offer financial incentives for private industry, is a promising start. Many see that the country is getting ready to build lots of new power plants to meet our energy needs. If we are ever going to protect the atmosphere, it is crucial that those new plants be environmentally sound. 26. An argument made by supporters of smoking was that [A] there was no scientific evidence of the correlation between smoking and death. [B] the number of early deaths of smokers in the past decades was insignificant. [C] people had the freedom to choose their own way of life. [D] antismoking people were usually talking nonsense. [答案] C [解题思路] 本题对应的是⽂章的第⼀段，⾸先要判断题⼲中提⾼的supporter就是第⼀句话中的doubter，因此才能正确判断supporter 的观点。

雅思听力必备词汇occupation

accountant: 会计actor: 男演员actress: 女演员airline representative: 地勤人员anchor: 新闻主播announcer: 广播员architect: 建筑师artist: 艺术家associate professor: 副教授astronaut: 宇航员. attendant: 服务员auditor: 审计员auto mechanic : 汽车技工baker: 烘培师barber: 理发师(男)baseball player: 棒球选手bell boy: 门童bellhop: 旅馆的行李员binman: 清洁工,垃圾工blacksmith: 铁匠boxer: 拳击手broker (agent) : 经纪人budgeteer: 预算编制者bus driver: 公车(巴士)司机butcher: 屠夫,肉商buyer: 采购员carpenter:木匠cartoonist: 漫画家cashier: 出纳员chef: 厨师chemist : 化学师clerk : 店员clown :小丑cobbler: 制(补)鞋匠computer programmer : 程序员construction worker : 建筑工人cook: 厨师cowboy :牛仔customs officer :海关官员dancer : 舞者dentist: 牙科医生designer: 设计师desk clerk: 接待员detective 侦探doctor: 医生door-to-door salesman: 推销员driver: 司机dustman: 清洁工editor : 编辑electrician :电工engineer:工程师farmer: 农夫fashion designer: 时装设计师fireman (firefighter): 消防员fisherman: 渔夫florist: 花商flyer: 飞行员Foreign minister : 外交部长gardener花匠(园丁)gas station attendant : 加油工geologist : 地质学家guard :警卫guide: 导游hiredresseer: 理发师,美容师(女) housekeeper : 管家housewife : 家庭主妇interpreter :口译员janitor : 清洁工journalist: 记者judge 法官lawyer :律师librarian: 图书管理员.life guard :救生员magician :魔术师masseur : 男按摩师masseuse : 女按摩师mathematician : 数学家mechanic: 机械师,机修工miner: 矿工model: 模特儿monk : 和尚,教士movie director: 导演movie star : 电影明星musician : 音乐家nun : 尼姑nurse: 护士office clerk : 职员office staff 上班族operator: 接线员parachutist: 跳伞人.personnel 职员pharmacist药剂师photographer:摄影师pilot: 飞行员planner: 计划员policeman: 警察postal clerk: 邮政人员postman :邮差President: 总统priest: 牧师professor: 教授real estate agent: 房地产经纪人receptionist :接待员repairman :修理工人reporter : 记者sailor: 船员，水手salesman/ selespeople/ salesperson: 售货员scientist: 科学家seamstress 女装裁缝师secretary: 秘书singer: 歌手soldiery: 士兵,军人statistician : 统计员surveyor: 测量技师tailor: 裁缝师taxi driver计程车司机teacher: 教师technician : 技术人员tour guide: 导游traffic warden: 交通管理员. translator: 翻译（笔译）TV producer: 电视制作人typist: 打字员vet: 兽医veterinarian兽医waiter: 侍者(服务生) waitress: 女侍者(服务生) welder : 焊接工writer: 作家。

基于先验与验后单位权中误差一致的控制网平差计算

基于先验与验后单位权中误差一致的控制网平差计算第21卷第2期湖南理T学院学报(自然科学版)V01.21NO.2Jun.20082008年6月JournalofHunanInstituteofScienceandTech—u—o——l基于先验与验后单位权中误差一致的控制网平差计算杨恒山(湖南理工学院土木建筑工程系,湖南岳阳414000)摘要:控制网平差计算最终目的是求出未知量和观测值的平差值并进行精度评定,对于同类独立等精度观测值控制网的平差计算平差结果与单位权中误差先验估值无关,对于观测值不等精度的测边网,传统的平差方法会导致单位权中误差先验值与验后值不一致,本文提出的一种新的平差方法可较好地解决此问题,该方法在高精度桥梁控制网的平差计算中有其实际应用价值关键词:单位权中误差;测边网;平差计算中图分类号:TU196文献标识码:A文章编号:1672—5298(2008)02—0071—03 AdjustmentofControlNetworkBasedontheSameofPrioriAndPosterioriEstimatingV alueofUnitWeightV arianceY ANGHeng—shan(DepartmentofCivilEngineering,HunnanInstituteofScienceandTechnology,Y ueyang414000,Chin a)Abstract:Theultimateaimofcontro1networkadjustmentistoderivetheadjustmentvalueofunknownq uantityandobservations,Analysisshowthatadjustmentresultsunrelatedtopriorestimatingvalueofunitweightvar ianceifindependentobservationsarethesameclassandprecision.Fortrilaterationa1networkwhichtheprecisionofobservat ionsarenotequa1.thetraditionalmethodwould1eadtothatposteriorestimatingvalueandpriorofunitweightarenotequa1,Th eauthorpresentsanewmethodwhichcanbettersolvethisproblem.andthemethodhasitsactua1valueinadjustmentofhigh—pr ecisionbridgecontro1network,Keywords:unitweightvariance;trilaterationanetwork;adjustment引言控制网的平差计算的目的一是求出观测值和未知数的平差值,二是对测量成果精度进行评定,平差计算所采用的模型,包括函数模型和随机模型,其中函数模型视具体问题不同可采用条件平差模型,间接平差模型,附有条件的间接平差模型,附有未知数的条件平差模型等,1990年於宗俦提出了概括平差摸型【¨,涵盖了上述所有模型,但在具体的平差计算问题中,考虑到编程的方便起见,一般采用间接平差模型随机模型可表示为E(△)=0,D(A)=croa:CroP～.平差计算的程序可用以下示意图表示:r}Tf三一1计算f满墨模型条件1求出f:肌+]按协因数传播律由{P=O}畀{按,PV:min}水田{},==>l起始数据jj【面丽}==>￡GLG0j按无偏性的要求p时=KQKQ=GQG,P(T0:——从示意图可以看出,权阵P的确定是测量平差计算非常关键的一步,如果观测值彼此独立,则权阵町简化一个对角阵,对角线上的元素值即权可用下列公式计算:P=cr02/m式中为单位权中误差, 收稿日期:2007.12-21作者简介:~Rth(1963一),男,湖南临湘人,硕士,湖南理]学院土木建筑1程系副教授.主要研究方向:测量数据处理和GIS数据质量控制和二=,●●●●,,L义定按72湖南理工学院学报(自然科学版)第21卷为观测值厶的中误差,一般根据控制网的精度等级或仪器标精度确定,但与实际估值会有差别.就独立不等精度观测值而言,单位权中误差的先验估值不同,平差计算结果也会不一样,目前参考文献讨论得比较多的是两类或多类观测值的方差分差估计,但对同类不等精度观测值的方差分量估计讨论还不够深人,本文在分析单位权中误差与平差计算结果文,￡,D撕,D关系的基础上,提出了依据单位权中误差先验值与验后值一致准则下的平差计算方法,并得出了一些有益的结论.1等精度独立观测值平差一般测角网和边长接近相等的测边网均可视为等精度独立观测值平差问题,其函数模型和随机模型分别为V=BX—;E(△)=0,D(A)=2P一考虑到观测值为独立等精度且假设单位权中误差先验值为m,观测值的中误差为m,则P:E(1)X=(BPB)一B(2)将(1)式代人(2)式则X=(BB)B(3)V=BX—,￡=+(4)2Pm0O”o_r,r考虑到m:,则有m:,而D=(BPB)BPD(A)PB(BPB)～=m(BB)一(5)D￡￡=mB(BB)B(6)分析公式(3),(4),(5),(6)不难发现若观测值为独立等精度,且依据单位中误差先验值与验后值一致准则,则平差计算所关心的结果X,￡,D肼,D￡￡与权阵,单位权中误差均无关,因此,在平差计算时,可不必考虑定权也毋需计算单位权中误差.2不等精度独立观测值平差测边网若边长不相等,则观测值的精度不同,水准网若路线长度不同,则高差值也是不等精度观测值,下面以测边网为例说明.测边网的边长观测值的先验精度一般根据仪器的标称精度来确定即:,=口+6或,=口+6S(7)式中a表示固定误差,单位rain,包括对中误差,仪器常数误差和测相误差与距离观测值无关,受气象环境的影响也很小;b为比例误差,包括测尺频率误差,真空光速误差和折射率误差,与观测距离有关,并受气象环境的影响.在实际测量时,一般可认为a与标称值的差异较小,但b随气象条件和气象元素观测值的精度而变化.与标称值比较可能有较大的差异,因此在平差计算时a取标称值,而b通过平差计算求得.假设测边网边长观测值为s1…,必要观测数为r,则多余观测数r=—t.为了便于对比分析,先简述传统的平差方法并指出其不足.传统的平差方法依据仪器标称精度根据式(7)可得,,rs=+S,并假设单位权中误差先验估值m,则有:P=m~diag(1/m,1/m,…,1/m)(k+1/(k+;),…,1/(k+:))(8)则P:m_.Z,D,将(8)式代人(2)式和(5)式可得又:(BrDB)-IBrDI,V=BXf,%=6(BrDB)～,=m~vrDv,=6B(BrB)一B.令2:2,则6:—V rD—V.考虑到b的计算式是非显式,无法直接求解,因此,一般不采用迭代法进行计算,迭代时b的初值根据仪器的标称精度确定,直至于b”=b时迭代终止.对于水准网而言,高差观测值的精度可由下式计算,戥mhIl站nl—_J式中指1km高差观测值中误差,站指一测站高差观测值中误差,S指路线长度,n.指测站数仿照测边网平差,此时:(1/.,l/:,…,1Is),或:(1/.,l/:,…,1In.),mlz(或):—V rD—V3算例算例选自文[2],有一桥梁控制网,A,B为己知点,其坐标为A:X=2000.O00m,=2000.O00m;X=2956.432m,=2000.O00m.用标称精度为5ram+5ppm的测距仪观测了网中7条边的边长,观测值见参考文献,试平差该测边网.为了比较两种平差方法,现将平差结果列入下表,参考文献中所采用的方法称为方法1,本文所提出的方法称为方法2,从平差值和成果精度两个方面进行比较.(11平差值比较表1(2)成果精度比较方法1所得坐标平差值的方差阵为:f9.450-2,0679,689-8.1280,l63—8.579f1.636—22262.268-0.1452.557D=l1.295-9,04l0,066-9.352l0.1l50.2949.7921.3790.470l1.143D=方法2所得坐标平差值的方差阵为:9758一1.9749,954-8.3340.1l8—8.7561.564-2.0982.173—0.1ll2.436l1.275-9.0770,053-9.39010.2770.2619,95l1.1440,400ll,230桥梁控制网平差的精度计算很重要的一个方面是要求出桥轴线的相对中误差,从而据此判断控制网(下转第77页)第2期付晓曙:坡体锚杆加固施T77定.(2)喷射混凝土接茬,应斜接搭接,搭接比度为喷射厚度的2倍以上.(3)喷射混凝土终凝后2h,应浇水养护,保持混凝土表面湿润,养护期不少于7天.5.5施工布置除在坡面分层搭设施工平台进行锚杆钻孔安装,张拉等_丁序以外,锚喷作为其它生产设备均布置在坡底的路面上,包括喷砼的搅拌机,喷射机,空压机,制浆机及锚筋加工等.5.6工程量鱼28预应力锚杆:40个420m;垒28普通锚杆:30个200m;喷水泥砂浆:lOOmm厚1343m2,50mm厚119m:排水孑L:700m;8钢筋网:3.55t;排水沟110m.5.7计划有效工作日45天完成6结论本方法锚杆受力明确,计算原理简单,施工易实施,工程现已竣工交付使用,工程总投资19.72万元,场内某段道路中类似的山坡防滑,采用的是钢筋砼护壁和片石挡土墙防滑,造价达到146万元之多,工期也要长一倍,两种不同的防滑方法其经济效益是非常明显的.参考文献[1]中华人民共和国国家标准,锚杆喷射混凝土支护技术规范GB50086—2O01,北京:中国计划出版社,2O01[2]中华人民共和围困家标准,建筑边坡工程技术规范[s].GB50330—2002,北京:中国建筑工业出版社,1901【3]3江正荣编着.实用建筑施工工程师手册【M】北京:中国建材工业H{版社,1995(上接第73页)(的精度是否符合桥梁工程施工的需要.现根据两种方法分别为出桥轴线的相对误差—结果如下:分析表1和表2可以看出,两种平差方法所解算出的基本一致,但精度成果存在差异,这种差异可能导致依据规范判断控制网是否符合精度要求时得出不正确的结果,因此时对于高精度的桥梁控制网平差建议采用严密方法.4结语表2本文针对只有一类观测值的控制网的平差进行了分析,分析表明:对于独立等精度观测值的控制网平差计算,平差结果,￡,D,D与单位中误差的先验值无关,因此平差计算毋需计算单位权中误差.对于独立不等精度观测值的测边网,由于需要确定观测值的先验精度,往往取仪器的标称精度值,这与实际情况存在差异,因此会导致单位权中误差验后优值与先验值不一致,从而影响到平差成果的精度,通过依据单位权中误差的先验值与验后值一致的准则.采用迭代计算可较好地解决此问题,本文所提出的平差方法在高精度的桥梁控制网的平差计算中有其实际应用价值.参考文献[1]於宗俦,陶本藻等.平差模型误差理论及其应用论文集】.北京:测绘出版社,1993[2】贺国宏桥隧控制测量[MI.北京:人民交通出版社,1999:73～79[3]崔希璋,於宗俦等.广义测量平差[M】.北京:测绘出版社,1992.[4]於宗俦,鲁林成.测量平差基础(增订本)[M].北京:测绘出版丰十,1983[5]崔希璋,於宗俦等-矩阵在测量中的应用】.北京:测绘出版社,1980。

observatory词根词缀

observatory词根词缀摘要：一、引言- 介绍observatory 词根词缀的来源和意义二、observatory 词根词缀的构成- 词根：observ- 词缀：-ory，表示“与...相关的”三、observatory 的意义和用法- 意义：观察、观测、监视- 用法：名词、形容词和动词四、observatory 在实际应用中的例子- 天文台（astronomical observatory）- 气象观测站（meteorological observatory）- 观察家（observer）- 观察（observe）正文：observatory 这个词根词缀源于拉丁语，由词根observ 和词缀-ory 组成。

词根observ 意为观察、观测或监视，词缀-ory 表示与...相关的。

因此，observatory 的整体意义为与观察、观测或监视相关的。

在英语中，observatory 主要用作名词，表示观察、观测或监视的场所或设施，例如天文台、气象观测站等。

此外，observatory 还可以作为形容词，表示具有观察、观测或监视性质的，如observatory telescope（天文望远镜）。

同时，observatory 还可以作为动词使用，表示进行观察、观测或监视，如observe（观察、观测）。

以天文台（astronomical observatory）为例，这个词是由词根observ 和后缀-ary（表示具有...性质的）组成的。

它表示一个专门用于观察、研究天体的设施，通常拥有先进的观测设备，如望远镜等。

天文台对于天文学的发展具有重要意义，许多重要的天文发现都源自于天文台的观测数据。

另一个例子是气象观测站（meteorological observatory），这个词是由词根observ 和词缀-orial（表示与...相关的）组成的。

它表示一个用于观察、记录气象现象的设施，可以收集温度、湿度、风力等气象数据。

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Hawaii under contract to the National Aeronautics and Space Administration.
3Also at Lowell Observatory, Flagstaff, AZ 86001-4499. 4Now at Department of Physics, 133 Hofstra University, Hempstead, NY
provided some information on Saturn's atmospheric shape at a pressure level of 250 mbar (Nicholson et al. 1995). The analysis of the total 28 Sgr occultation data set by H97 has shown evidence for the existence of the bulge produced by the high zonal winds at the microbar level. In order to constrain the planetary figure to a higher accuracy, it is necessary that observations be made over a large range of latitudes so that the isopycs (surfaces of constant number density) can be mapped over the entire planet. None of the prior occultation observations, neither visible nor radio, probed Saturn at latitudes higher than 36.3 degrees in the northern hemisphere and 74.2 degrees in the southern hemisphere. In this paper our goals are to obtain the thermal structure of the north polar region and explore the possible latitudinal temperature variations. The half-light radius and corresponding pressure of this high-latitude region can be used to constrain the shape of Saturn at the microbar level.
11550-1090
ABSTRACT
We have observed a stellar occultation of GSC5249-01240 by Saturn's north polar region on November 20, 1995 from NASA's Infrared Telescope Facility (IRTF). This is the first recorded occultation by the polar region of a giant planet. The occulted region extends 88 km in vertical height and 660 km in horizontal length, over a region from 82.5 to 85 degrees in planetocentric latitude and from 20 to 30 degrees in planetocentric longitude. Based on isothermal model fits to the light curve, we find an equivalent isothermal temperature of 130 ± 10 K at a pressure level of 1.6 ± 0.1 µbar, which corresponds to a half-light latitude of 83.2 ± 0.2 degrees and longitude of 24.1 ± 0.5 degrees. Using numerical inversion procedures, we have retrieved the temperature profile of the occulted region, which suggests an increase in temperature (with radius) of 14.5 K between 6 and 10 µbar. We also find temperature fluctuations of 1 to 5 K along the path probed by the occultation; if the observed temperature gradients of these fluctuations apply to the vertical direction only, then this region is super-adiabatic. More likely these thermal gradients are due to a combination of diffractive scintillations and horizontal temperature variations. Given that isothermal model fits and numerical inversions cannot separate individual contributions to observed temperature gradients, such as from vertical variations, horizontal variations, and scintillations, this occultation requires a further study.
Keywords: Atmosphere Dynamics; Atmosphere Structure; Occultations; Saturn Atmosphere
I. INTRODUCTION
Most of our knowledge of Saturn's vertical temperature structure has come from (i) a series of radio (RSS) occultations, below a radius of 60600 km at a pressure level of 1 bar (Lindal et al. 1985), and (ii) ultraviolet (UVS) occultations above a radius of 61200 km at pressures below the microbar level (Smith et al. 1983) observed with instruments on the Pioneer 11, Voyager 1, and Voyager 2 spacecraft near Saturn. In recent years ground-based stellar occultations have measured Saturn's temperature structure at the microbar level through observations of the 28 Sgr occultation by Saturn in 1989 (Hubbard et al. 1997, hereinafter H97), observations of the central flashes during the 28 Sgr occultation (central flashes probe at much higher pressures—Nicholson et al. 1995), and a series of Hubble Space Telescope (HST) Guide Star Catalog (GSC) occultations by Saturn (Bosh and McDonald 1992) during the years 1994-1996. One of these events is described here, with more information given by Cooray (1997). Even though Saturn's equatorial region has been well studied by spacecraft instruments, less is known about its north polar latitudes. This region has been observed recently with HST for the purposes of studying haze distributions (Karkoschka and Tomasko 1993), the polar hexagon (Sanchez-Lavega et al. 1996), and auroral activity (Trauger et al. 1994). For Saturn, the existence of two features near the north polar region—the hexagonal wave structure (Allison et al. 1990; Sanchez-Lavega et al. 1993) and the north polar spot (Sanchez-Lavega et al. 1997)—makes it interesting to study the surrounding regions in order to learn about the dynamics associated with them. The atmospheric temperature variations may provide clues to some of the dynamical processes associated with the atmospheric structures. Rapid rotation with a period of 10.65667 hr (Desch and Kaiser 1981) causes Saturn's atmosphere to be extremely oblate with an oblateness of 0.098 ± 0.001 at the 1-bar level (Lindal et al. 1985). Due to the very high zonal winds, the rotation is not uniform and currently the shape is constrained at the 1-bar level by radio occultation observations with various spacecraft (Lindal et al. 1985). Central-flash observations at infrared wavelengths during the 28 Sgr occultation have