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Register a new userApplication of Time Transfer Functions to Gaias global astrometry - Validation on DPAC simulated Gaia-like observations
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A key objective of the ESA Gaia satellite is the realization of a quasi-inertial reference frame at visual wavelengths by means of global astrometric techniques. This requires an accurate mathematical and numerical modeling of relativistic light propagation, as well as double-blind-like procedures for the internal validation of the results, before they are released to the scientific community at large. Aim of this work is to specialize the Time Transfer Functions (TTF) formalism to the case of the Gaia observer and prove its applicability to the task of Global Sphere Reconstruction (GSR), in anticipation of its inclusion in the GSR system, already featuring the suite of RAMOD models, as an additional semi-external validation of the forthcoming Gaia baseline astrometric solutions. We extend the current GSR framework and software infrastructure (GSR2) to include TTF relativistic observation equations compatible with Gaias operations. We use simulated data generated by the Gaia Data Reduction and Analysis Consortium (DPAC) to obtain different least-squares estimations of the full stellar spheres and gauge results. These are compared to analogous solutions obtained with the current RAMOD model in GSR2 and to the catalog generated with GREM, the model baselined for Gaia and used to generate the DPAC synthetic data. Linearized least-squares TTF solutions are based on spheres of about 132,000 primary stars uniformly distributed on the sky and simulated observations spanning the entire 5-yr range of Gaias nominal operational lifetime. The statistical properties of the results compare well with those of GREM. Finally, comparisons to RAMOD@GSR2 solutions confirmed the known lower accuracy of that model and allowed us to establish firm limits on the quality of the linearization point outside of which an iteration for non-linearity is required for its proper convergence.
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Gaia is the next astrometry mission of the European Space Agency (ESA), following up on the success of the Hipparcos mission. With a focal plane containing 106 CCD detectors, Gaia will survey the entire sky and repeatedly observe the brightest 1,000 million objects, down to 20th magnitude, during its 5-year lifetime. Gaias science data comprises absolute astrometry, broad-band photometry, and low-resolution spectro-photometry. Spectroscopic data with a resolving power of 11,500 will be obtained for the brightest 150 million sources, down to 17th magnitude. The thermo-mechanical stability of the spacecraft, combined with the selection of the L2 Lissajous point of the Sun-Earth/Moon system for operations, allows stellar parallaxes to be measured with standard errors less than 10 micro-arcsecond (muas) for stars brighter than 12th magnitude, 25 muas for stars at 15th magnitude, and 300 muas at magnitude 20. Photometric standard errors are in the milli-magnitude regime. The spectroscopic data allows the measurement of radial velocities with errors of 15 km/s at magnitude 17. Gaias primary science goal is to unravel the kinematical, dynamical, and chemical structure and evolution of the Milky Way. In addition, Gaias data will touch many other areas of science, e.g., stellar physics, solar-system bodies, fundamental physics, and exo-planets. The Gaia spacecraft is currently in the qualification and production phase. With a launch in 2013, the final catalogue is expected in 2021. The science community in Europe, organised in the Data Processing and Analysis Consortium (DPAC), is responsible for the processing of the data.
Before the publication of the Gaia Catalogue, the contents of the first data release have undergone multiple dedicated validation tests. These tests aim at analysing in-depth the Catalogue content to detect anomalies, individual problems in specific objects or in overall statistical properties, either to filter them before the public release, or to describe the different caveats of the release for an optimal exploitation of the data. Dedicated methods using either Gaia internal data, external catalogues or models have been developed for the validation processes. They are testing normal stars as well as various populations like open or globular clusters, double stars, variable stars, quasars. Properties of coverage, accuracy and precision of the data are provided by the numerous tests presented here and jointly analysed to assess the data release content. This independent validation confirms the quality of the published data, Gaia DR1 being the most precise all-sky astrometric and photometric catalogue to-date. However, several limitations in terms of completeness, astrometric and photometric quality are identified and described. Figures describing the relevant properties of the release are shown and the testing activities carried out validating the user interfaces are also described. A particular emphasis is made on the statistical use of the data in scientific exploitation.
Context: The unprecedented astrometric precision of the Gaia mission relies on accurate estimates of the locations of sources in the Gaia data stream. This is ultimately performed by point spread function (PSF) fitting, which in turn requires an accurate reconstruction of the PSF. Gaia Early Data Release 3 (EDR3) will, for the first time, use a PSF calibration that models several of the strongest dependences, leading to signficantly reduced systematic errors. Aims: We describe the PSF model and calibration pipeline implemented for Gaia EDR3, including an analysis of the calibration results over the 34 months of data. We include a discussion of the limitations of the current pipeline and directions for future releases. This will be of use both to users of Gaia data and as a reference for other precision astrometry missions. Methods: We develop models of the 1D line spread function (LSF) and 2D PSF profiles based on a linear combination of basis components. We fit the models to selected primary sources in independent time ranges, using simple parameterisations for the colour and other dependences. Variation in time is smoothed by merging the independent calibrations in a square root information filter, with resets at certain mission events that induce a discontinuous change in the PSF. Results: The PSF calibration shows strong time and colour dependences that accurately reproduce the varying state of the Gaia astrometric instrument. Analysis of the residuals reveals both the performance and the limitations of the current models and calibration pipeline, and indicates the directions for future development. Conclusions: The PSF modelling and calibration carried out for Gaia EDR3 represents a major step forwards in the data processing and will lead to reduced systematic errors in the core mission data products. Further significant improvements are expected in the future data releases.
In various fields of physics and astronomy, access to experimental facilities or to telescopes is becoming more and more competitive and limited. It becomes therefore important to optimize the type of measurements and their scheduling to reach a given scientific objective and to increase the chances of success of a scientific project. In this communication, extending the work of Ford (2008) and of Loredo et al. (2012), we present an efficient adaptive scheduling tool aimed at prioritzing measurements in order to reach a scientific goal. The algorithm, based on the Fisher matrix, can be applied to a wide class of measurements. We present this algorithm in detail and discuss some practicalities such as systematic errors or measurements losses due to contigencies (such as weather, experimental failure, ...). As an illustration, we consider measurements of the short-period star S0-2 in our Galactic Center. We show that the radial velocity measurements at the two turning points of the radial velocity curve are more powerful for detecting the gravitational redshift than measurements at the maximal relativistic signal. We also explicitly present the methodology that was used to plan measurements in order to detect the relativistic redshift considering systematics and possible measurements losses. For the future, we identify the astrometric turning points to be highly sensitive to the relativistic advance of the periastron. Finally, we also identify measurements particularly sensitive to the distance to our Galactic Center: the radial velocities around periastron and the astrometric measurements just before closest approach and at the maximal right ascension astrometric turning point.
High-precision astrometry requires accurate point-spread function modeling and accurate geometric-distortion corrections. This paper demonstrates that it is possible to achieve both requirements with data collected at the high acuity wide-field K-band imager (HAWK-I), a wide-field imager installed at the Nasmyth focus of UT4/VLT ESO 8m telescope. Our final astrometric precision reaches ~3 mas per coordinate for a well-exposed star in a single image with a systematic error less than 0.1 mas. We constructed calibrated astro-photometric catalogs and atlases of seven fields: the Baades Window, NGC 6656, NGC 6121, NGC 6822, NGC 6388, NGC 104, and the James Webb Space Telescope calibration field in the Large Magellanic Cloud. We make these catalogs and images electronically available to the community. Furthermore, as a demonstration of the efficacy of our approach, we combined archival material taken with the optical wide-field imager at the MPI/ESO 2.2m with HAWK-I observations. We showed that we are able to achieve an excellent separation between cluster members and field objects for NGC 6656 and NGC 6121 with a time base-line of about 8 years. Using both HST and HAWK-I data, we also study the radial distribution of the SGB populations in NGC 6656 and conclude that the radial trend is flat within our uncertainty. We also provide membership probabilities for most of the stars in NGC 6656 and NGC 6121 catalogs and estimate membership for the published variable stars in these two fields.
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