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2012, Astronomy & Astrophysics
Context. To use the data in the future Gaia catalogue it is important to have accurate estimates of the statistical uncertainties and correlations of the errors in the astrometric data given in the catalogue. Aims. In a previous paper we derived a mathematical model for computing the covariances of the astrometric data based on series expansions and a simplified attitude description. The aim of the present paper is to determine to what extent this model provides an accurate representation of the expected random errors in the astrometric solution for Gaia. Methods. We simulate the astrometric core solution by making least-squares solutions of the astrometric parameters for one million stars and the attitude parameters for a five-year mission, using nearly one billion simulated elementary observations for a total of 26 million unknowns. Two cases are considered: one in which all stars have the same magnitude, and another with 30% brighter and 70% fainter stars. The resulting astrometric errors are statistically compared with the model predictions.
Eas Publications Series, 2011
Accurate characterization of the errors in the global astrometric solution for Gaia is essential for making optimal use of the catalogue data. We investigate the structure of the covariance between the estimated astrometric parameters by studying the properties of the astrometric least squares solution. We find that astrometric errors can be separated in a star and an attitude part, due
Proceedings of the International Astronomical Union, 2009
Accurate characterization of the astrometric errors in the forthcoming Gaia catalogue is essential for making optimal use of the data. Using small-scale numerical simulations of the astrometric solution, we investigate the expected spatial correlation between the astrometric errors of stars as function of their angular separation. Extrapolating to the full-scale solution for the final Gaia catalogue, we find that the expected correlations are generally very small, but could reach some fraction of a percent for angular separations smaller than about one degree. The spatial correlation length is related to the size of the field of view of Gaia, while the maximum correlation coefficient is related to the mean number of stars present in the field at any time. Our scalable simulation tool (AGISLab) makes it possible to characterize the astrometric errors and correlations, e.g., as functions of position and magnitude.
Gaia's astrometric solution aims to determine at least five parameters for each star, together with appropriate estimates of their uncertainties and correlations. This requires at least five distinct observations per star. In the early data reductions the number of observations may be insufficient for a five-parameter solution, and even after the full mission many stars will remain under-observed, including faint stars at the detection limit and transient objects. In such cases it is reasonable to determine only the two position parameters. Their formal uncertainties would however grossly underestimate the actual errors, due to the neglected parallax and proper motion. We aim to develop a recipe to calculate sensible formal uncertainties that can be used in all cases of under-observed stars. Prior information about the typical ranges of stellar parallaxes and proper motions is incorporated in the astrometric solution by means of Bayes' rule. Numerical simulations based on th...
Astronomy & Astrophysics, 2016
Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues-a realisation of the Tycho-Gaia Astrometric Solution (TGAS)-and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr −1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr −1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.
Astronomy & Astrophysics, 2012
Context. The Gaia satellite will observe about one billion stars and other point-like sources. The astrometric core solution will determine the astrometric parameters (position, parallax, and proper motion) for a subset of these sources, using a global solution approach which must also include a large number of parameters for the satellite attitude and optical instrument. The accurate and efficient implementation of this solution is an extremely demanding task, but crucial for the outcome of the mission. Aims. We aim to provide a comprehensive overview of the mathematical and physical models applicable to this solution, as well as its numerical and algorithmic framework. Methods. The astrometric core solution is a simultaneous least-squares estimation of about half a billion parameters, including the astrometric parameters for some 100 million well-behaved so-called primary sources. The global nature of the solution requires an iterative approach, which can be broken down into a small number of distinct processing blocks (source, attitude, calibration and global updating) and auxiliary processes (including the frame rotator and selection of primary sources). We describe each of these processes in some detail, formulate the underlying models, from which the observation equations are derived, and outline the adopted numerical solution methods with due consideration of robustness and the structure of the resulting system of equations. Appendices provide brief introductions to some important mathematical tools (quaternions and B-splines for the attitude representation, and a modified Cholesky algorithm for positive semidefinite problems) and discuss some complications expected in the real mission data. Results. A complete software system called AGIS (Astrometric Global Iterative Solution) is being built according to the methods described in the paper. Based on simulated data for 2 million primary sources we present some initial results, demonstrating the basic mathematical and numerical validity of the approach and, by a reasonable extrapolation, its practical feasibility in terms of data management and computations for the real mission.
Astronomy & Astrophysics, 2013
The Gaia satellite will survey the entire celestial sphere down to 20th magnitude, obtaining astrometry, photometry, and low resolution spectrophotometry on one billion astronomical sources, plus radial velocities for over one hundred million stars. Its main objective is to take a census of the stellar content of our Galaxy, with the goal of revealing its formation and evolution. Gaia's unique feature is the measurement of parallaxes and proper motions with hitherto unparalleled accuracy for many objects. As a survey, the physical properties of most of these objects are unknown. Here we describe the data analysis system put together by the Gaia consortium to classify these objects and to infer their astrophysical properties using the satellite's data. This system covers single stars, (unresolved) binary stars, quasars, and galaxies, all covering a wide parameter space. Multiple methods are used for many types of stars, producing multiple results for the end user according to different models and assumptions. Prior to its application to real Gaia data the accuracy of these methods cannot be assessed definitively. But as an example of the current performance, we can attain internal accuracies (RMS residuals) on F,G,K,M dwarfs and giants at G = 15 (V = 15-17) for a wide range of metallicites and interstellar extinctions of around 100 K in effective temperature (T eff ), 0.1 mag in extinction (A0), 0.2 dex in metallicity ([Fe/H]), and 0.25 dex in surface gravity (log g). The accuracy is a strong function of the parameters themselves, varying by a factor of more than two up or down over this parameter range. After its launch in November 2013, Gaia will nominally observe for five years, during which the system we describe will continue to evolve in light of experience with the real data.
Astrostatistics and Data Mining, 2012
For users of the Gaia astrometric catalogue it will be essential to have access to the covariance between any pair of astrometric parameters when computing quantities that combine multiple catalogue parameters. The computation and storage of the full covariance matrix for the expected 5 × 10 9 astrometric parameters (∼10 8 TeraByte) is, however, expected to be infeasible considering nearfuture storage and floating-point capabilities. In this paper we describe (without going into the mathematical details) how the covariance of arbitrary functions of the astrometric parameters can be estimated in a computationally efficient way from a reduced amount of data (∼2 TeraByte). We also include two examples, explaining how to practically compute the covariance for the average parallax of a star cluster and the acceleration of the solar system barycentre in a cosmological frame.
Proceedings of the International Astronomical Union, 2009
The scientific objectives of the Gaia mission cover areas of galactic structure and evolution, stellar astrophysics, exoplanets, solar system physics, and fundamental physics. Astrometrically, its main contribution will be the determination of millions of absolute stellar parallaxes and the establishment of a very accurate, dense and faint non-rotating optical reference frame. With a planned launch in spring 2012, the project is in its advanced implementation phase. In parallel, preparations for the scientific data processing are well under way within the Gaia Data Processing and Analysis Consortium. Final mission results are expected around 2021, but early releases of preliminary data are expected. This review summarizes the main science goals and overall organisation of the project, the measurement principle and core astrometric solution, and provide an updated overview of the expected astrometric performance.
In two years, the European Space Agency (ESA) will launch the Gaia mission.Gaia will observe all point-like sources in the sky between magnitude 6 and20, a total of more than a thousand million stars and planets. For thebrightest sources we will obtain parallaxes and yearly proper motions witha precision of 10 microarcseconds, while the precision will degrade to300 microarcseconds for thefaintest stars. The reduction of the astrometric data is a very complex andextensive task, which only can be undertaken in a collaboration betweenmany groups within the ESA member states.We describe the role of Spain and of the national supercomputing centre(CNS-BSC) in this work, and describe some of the most critical points inmodelling the instrument and in the observations.We describe the initial data treatment which must be carried out dailyduring the mission, and the process of repeated improvement of theintermediate data which is carried out several times, before reaching thefinal values. The ...
… Data Analysis Software …, 2010
Gaia is ESA's space astrometry mission with a foreseen launch date in early 2012. Its main objective is to perform a stellar census of the 1000 Million brightest objects in our galaxy (completeness to V= 20 mag) from which an astrometric catalog of micro-arcsec ...
Monthly Notices of the Royal Astronomical Society, 2010
A tool for representation of the one-dimensional astrometric signal of Gaia is described and investigated in terms of fit discrepancy and astrometric performance with respect to number of parameters required. The proposed basis function is based on the aberration free response of the ideal telescope and its derivatives, weighted by the source spectral distribution. The influence of relative position of the detector pixel array with respect to the optical image is analysed, as well as the variation induced by the source spectral emission. The number of parameters required for micro-arcsec level consistency of the reconstructed function with the detected signal is found to be 11. Some considerations are devoted to the issue of calibration of the instrument response representation, taking into account the relevant aspects of source spectrum and focal plane sampling. Additional investigations and other applications are also suggested.
Adaptive Optics Systems IV, 2014
We measure the long-term systematic component of the astrometric error in the GeMS MCAO system as a function of field radius and Ks magnitude. The experiment uses two epochs of observations of NGC 1851 separated by one month. The systematic component is estimated for each of three field of view cases (15'' radius, 30'' radius, and full field) and each of three distortion correction schemes: 8 DOF/chip + local distortion correction (LDC), 8 DOF/chip with no LDC, and 4 DOF/chip with no LDC. For bright, unsaturated stars with 13 < Ks < 16, the systematic component is < 0.2, 0.3, and 0.4 mas, respectively, for the 15'' radius, 30'' radius, and full field cases, provided that an 8 DOF/chip distortion correction with LDC (for the full-field case) is used to correct distortions. An 8 DOF/chip distortion-correction model always outperforms a 4 DOF/chip model, at all field positions and magnitudes and for all field-of-view cases, indicating the presence of high-order distortion changes. Given the order of the models needed to correct these distortions (~8 DOF/chip or 32 degrees of freedom total), it is expected that at least 25 stars per square arcminute would be needed to keep systematic errors at less than 0.3 milliarcseconds for multi-year programs. We also estimate the short-term astrometric precision of the newly upgraded Shane AO system with undithered M92 observations. Using a 6-parameter linear transformation to register images, the system delivers ~0.3 mas astrometric error over short-term observations of 2-3 minutes. Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/30/2015 Terms of Use: http://spiedl.org/terms Proc. of SPIE Vol. 9148 91481J-2 Proc. of SPIE Vol. 9148 91481J-7 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/30/2015 Terms of Use: http://spiedl.org/terms
Astronomical Society of …, 2009
Abstract. Gaia is ESA's ambitious space astrometry mission with a foreseen launch date in late 2011. Its main objective is to perform a stellar census of the 1,000 million brightest objects in our galaxy (completeness to V = 20 mag) from which an astrometric catalog of ...
2010
Gaia is ESA's ambitious space astrometry mission with a foreseen launch date in early 2012. Its main objective is to perform a stellar census of the 1000 Million brightest objects in our galaxy (completeness to V=20 mag) from which an astrometric catalog of micro-arcsec level accuracy will be constructed. A key element in this endeavor is the Astrometric Global Iterative Solution (AGIS) - the mathematical and numerical framework for combining the ≈80 available observations per star obtained during Gaia's 5yr lifetime into a single global astrometric solution. At last year's ADASS XVIII we presented (O4.1) in detail the fundamental working principles of AGIS, its development status, and selected results obtained by running the system on processing hardware at ESAC, Madrid with large-scale simulated data sets. We present here the latest developments around AGIS highlighting in particular a much improved algebraic solving method that has recently been implemented. This C...
Open Astronomy, 1999
This note shortly presents the statistical results for several fields observed along different directions of the Galaxy which are used to calibrate a new version of the HRD-Galactic Software Telescope (HRD-GST) developed in Padova. Also, the extinction vs. distance dependence is given for some directions in the galactic plane.
Astronomy & Astrophysics, 2014
Aims. An effort has been made to simulate the expected Gaia Catalogue, including the effect of observational errors. We statistically analyse this simulated Gaia data to better understand what can be obtained from the Gaia astrometric mission. This catalogue is used to investigate the potential yield in astrometric, photometric, and spectroscopic information and the extent and effect of observational errors on the true Gaia Catalogue. This article is a follow-up to previous work, where the expected Gaia Catalogue content was reviewed but without the simulation of observational errors. Methods. We analysed the Gaia Object Generator (GOG) catalogue using the Gaia Analysis Tool (GAT), thereby producing a number of statistics about the catalogue. Results. A simulated catalogue of one billion objects is presented, with detailed information on the 523 million individual single stars it contains. Detailed information is provided for the expected errors in parallax, position, proper motion, radial velocity, and the photometry in the four Gaia bands. Information is also given on the expected performance of physical parameter determination, including temperature, metallicity, and line-of-sight extinction.
Astronomy & Astrophysics, 2015
Context. The first release of astrometric data from Gaia will contain the mean stellar positions and magnitudes from the first year of observations, and proper motions from the combination of Gaia data with Hipparcos prior information (HTPM). Aims. We study the potential of using the positions from the Tycho-2 Catalogue as additional information for a joint solution with early Gaia data. We call this the Tycho-Gaia astrometric solution (TGAS). Methods. We adapt Gaia's Astrometric Global Iterative Solution (AGIS) to incorporate Tycho information, and use simulated Gaia observations to demonstrate the feasibility of TGAS and to estimate its performance. Results. Using six to twelve months of Gaia data, TGAS could deliver positions, parallaxes and annual proper motions for the 2.5 million Tycho-2 stars, with sub-milliarcsecond accuracy. TGAS overcomes some of the limitations of the HTPM project and allows its execution half a year earlier. Furthermore, if the parallaxes from Hipparcos are not incorporated in the solution, they can be used as a consistency check of the TGAS/HTPM solution.
arXiv (Cornell University), 2022
Context. Gaia Data Release 3 (DR3) provides a wealth of new data products for the astronomical community to exploit, including astrophysical parameters for a half billion stars. In this work we demonstrate the high quality of these data products and illustrate their use in different astrophysical contexts. Aims. We produce homogeneous samples of stars with high quality astrophysical parameters by exploiting Gaia DR3 while focusing on many regimes across the Hertzsprung-Russell (HR) diagram; spectral types OBA, FGKM, and ultra-cool dwarfs (UCDs). We also focus on specific sub-samples which are of particular interest to the community: solar analogues, carbon stars, and the Spectro Photometric Standard Stars (SPSS). Methods. We query the astrophysical parameter tables along with other tables in Gaia DR3 to derive the samples of the stars of interest. We validate our results by using the Gaia catalogue itself and by comparison with external data. Results. We have produced six homogeneous samples of stars with high quality astrophysical parameters across the HR diagram for the community to exploit. We first focus on three samples that span a large parameter space: young massive disk stars (OBA, ∼3M), FGKM spectral type stars (∼3M), and UCDs (∼20 K). We provide these sources along with additional information (either a flag or complementary parameters) as tables that are made available in the Gaia archive. We furthermore identify 15 740 bone fide carbon stars, 5 863 solar-analogues, and provide the first homogeneous set of stellar parameters of the SPSS sample. We demonstrate some applications of these samples in different astrophysical contexts. We use a subset of the OBA sample to illustrate its usefulness to analyse the Milky Way rotation curve. We then use the properties of the FGKM stars to analyse known exoplanet systems. We also analyse the ages of some unseen UCD-companions to the FGKM stars. We additionally predict the colours of the Sun in various passbands (Gaia, 2MASS, WISE) using the solar-analogue sample. Conclusions. Gaia DR3 contains a wealth of new high quality astrophysical parameters for the community to exploit.
The Astronomical Journal
We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space-and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.
Astronomy & Astrophysics, 2018
Context. The Gaia ESA mission will estimate the astrometric and physical data of more than one billion objects, providing the largest and most precise catalog of absolute astrometry in the history of astronomy. The core of this process, the so-called global sphere reconstruction, is represented by the reduction of a subset of these objects which will be used to define the celestial reference frame. As the Hipparcos mission showed, and as is inherent to all kinds of absolute measurements, possible errors in the data reduction can hardly be identified from the catalog, thus potentially introducing systematic errors in all derived work. Aims. Following up on the lessons learned from Hipparcos, our aim is thus to develop an independent sphere reconstruction method that contributes to guarantee the quality of the astrometric results without fully reproducing the main processing chain. Methods. Indeed, given the unfeasibility of a complete replica of the data reduction pipeline, an astrometric verification unit (AVU) was instituted by the Gaia Data Processing and Analysis Consortium (DPAC). One of its jobs is to implement and operate an independent global sphere reconstruction (GSR), parallel to the baseline one (AGIS, namely Astrometric Global Iterative Solution) but limited to the primary stars and for validation purposes, to compare the two results, and to report on any significant differences. Results. Tests performed on simulated data show that GSR is able to reproduce at the sub-µas level the results of the AGIS demonstration run. Conclusions. Further development is ongoing to improve on the treatment of real data and on the software modules that compare the AGIS and GSR solutions to identify possible discrepancies above the tolerance level set by the accuracy of the Gaia catalog.
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