Gaia Early Data Release 3
Documentation release 1.1
Executive summary
The early installment of the third Gaia data release, Gaia EDR3, encompasses astrometry and photometry, complemented with radial velocities copied from Gaia DR2 after removal of a small number of spurious entries. The basic number statistics of the contents of Gaia EDR3 is as follows:
Data product or source type | Number of sources |
Total | |
Five-parameter astrometry (position, parallax, proper motion) | |
Six-parameter astrometry (position, parallax, proper motion, pseudo-colour) | |
Two-parameter astrometry (position only) | |
Gaia-CRF3 extra-galactic sources (optical reference frame) | |
ICRF3 sources (for frame orientation) | |
Gaia-CRF3 sources (for frame spin) | |
-band (330–1050 nm) | |
-band (330–680 nm) | |
-band (630–1050 nm) | |
Median radial velocity over 22 months (Gaia DR2) |
The basic quality statistics of the contents of Gaia EDR3 are as follows (where the astrometric uncertainties as well as the Gaia-CRF3 alignment and rotation (spin) limits refer to epoch J2016.0 TCB):
Data product or source type | Typical uncertainty |
Five-parameter astrometry (position) | – mas at |
mas at | |
mas at | |
mas at | |
Five-parameter astrometry (parallax) | – mas at |
mas at | |
mas at | |
mas at | |
Five-parameter astrometry (proper motion) | – mas yr at |
mas yr at | |
mas yr at | |
mas yr at | |
Six-parameter astrometry (position) | – mas at |
mas at | |
mas at | |
mas at | |
Six-parameter astrometry (parallax) | – mas at |
mas at | |
mas at | |
mas at | |
Six-parameter astrometry (proper motion) | – mas yr at |
mas yr at | |
mas yr at | |
mas yr at | |
Two-parameter astrometry (position only) | – mas |
Systematic astrometric errors (sky averaged) | mas |
Gaia-CRF3 alignment with ICRF | mas at |
Gaia-CRF3 rotation with respect to ICRF | mas yr at |
Mean -band photometry | mmag at |
mmag at | |
mmag at | |
Mean -band photometry | mmag at |
mmag at | |
mmag at | |
Mean -band photometry | mmag at |
mmag at | |
mmag at | |
Median radial velocity over 22 months | km s at |
km s at | |
km s at | |
Systematic radial velocity errors | km s at |
km s at |
The Gaia EDR3 parallaxes show evidence for a global zero point, in the sense Gaia ‘true’, of about mas, which has not been ‘corrected’ in the data (for details, see Lindegren et al. 2020).
The data collected between 25 July 2014 and 28 May 2017 – during the first 34 months of the nominal, five-year mission – have been processed by the Gaia Data Processing and Analysis Consortium (DPAC), resulting into this third data release. A summary of the release properties is provided in Gaia Collaboration et al. (2020a). The overall scientific validation of the data is described in Fabricius et al. (2021). These papers are considered ‘must-read’ material for any user of Gaia EDR3 data. Background information on the Gaia mission and the spacecraft can be found in Gaia Collaboration et al. (2016b), with a more detailed presentation of the Radial Velocity Spectrometer (RVS) in Cropper et al. (2018). In addition, Gaia EDR3 is accompanied by dedicated papers, all part of a Special Issue of A&A, that describe the processing and validation of the various data products: Lindegren et al. (2021) for the Gaia EDR3 astrometry, Riello et al. (2020) for the Gaia EDR3 photometry, Seabroke et al. (2020) for the radial velocities published in Gaia EDR3, and Klioner et al. (2020) for the celestial reference frame. Four more papers present a glimpse of the scientific value, richness, and potential of the data in the areas of the kinematics of the Milky Way towards the Galactic anti-centre (Gaia Collaboration et al. 2021), the properties of the complete sample of nearby stars (Gaia Collaboration et al. 2020d, , the Gaia Catalogue of Nearby Stars), the structure and properties of the Magellanic Clouds (Gaia Collaboration et al. 2020c), and the acceleration of the solar-system barycentre with respect to distant quasars (Gaia Collaboration et al. 2020b). In addition to the set of references mentioned above, this documentation provides a detailed, complete overview of the processing and validation of the Gaia EDR3 data.
Data from and Gaia EDR3, as well as from Gaia DR1 and Gaia DR2, can be retrieved from the Gaia ESA Archive (GEA), which is accessible from https://archives.esac.esa.int/gaia. The archive also provides various tutorials on data access and data queries plus an integrated data model (i.e., description of the various fields in the data tables). In addition, Luri et al. (2018) provide concrete advice on how to deal with Gaia astrometry, with recommendations on how best to estimate distances from parallaxes. The Gaia archive features a visualisation service which can be used for quick initial explorations of the entire Gaia EDR3 data set. Carefully validated, pre-computed cross matches between Gaia EDR3 and a selected of large surveys is provided, with details described in Marrese et al. (2019, 2021). Finally, Gaia EDR3 contains the (intended) pointing of the Gaia telescopes as a function of time (commanded_scan_law table) and simulated Gaia catalogues (gaia_universe_model and gaia_source_simulation tables).
Gaia EDR3 represents a major advance with respect to Gaia DR2 in terms of astrometric and photometric precision and accuracy as well as in survey homogeneity across colour, magnitude, and celestial position. For the first time, the astrometric solution has benefited from an iterative step between the determination of image locations and fluxes and the astrometric calibrations. Further notable improvements include:
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Enhancements in the creation of the source list that make it more robust with respect to variable stars, high proper motion stars, and the disturbing effects of spurious on-board detections – caused, among others, by diffraction spikes of bright stars, galactic cosmic rays, or planets in the solar system transiting the fied of view – and partially resolved sources (Torra et al. 2020);
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A more sophisticated modelling, including temporal and source-colour dependencies, of the line and point spread functions of the astrometric instrument in the image parameter determination (Rowell et al. 2020);
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An improved and extended astrometric calibration model, to better handle saturated images and to cope with the effects of radiation-induced charge transfer inefficiency, imperfections in the point and line spread function models that cause residual effects at the sub-pixel level, and the variable rate with which sources move across the focal plane in the direction perpendicular to the scan direction;
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An improved and extended photometric calibration model, leading to a better treatment of saturated images and a more precise and fine-grained determination of the background flux – either due to stray light or due to astronomical sources – in each observation window. Gaia EDR3 also uses an improved set of external photometric calibrators that are more evenly distributed in colour and in magnitude than for Gaia DR2. As a consequence, and in contrast to Gaia DR2, a single passband for each of the photometric bands , , and can now be used over the entire magnitude and colour range, with systematics remaining below 1%.
Gaia EDR3 provides an updated materialisation of the celestial reference frame at optical wavelengths. The so-called Gaia-CRF3, which is based solely on extragalactic sources, is aligned with the International Celestial Reference Frame (ICRF) and details are provided in Klioner et al. (2020). An ad-hoc correction has been introduced to ensure that the bright-star reference frame has no net spin with respect to the reference frame defined by (faint) quasars. The tables agn_cross_id and frame_rotator_source provide the source IDs of the Gaia-CRF3 sources.
Several limitations and best practices for the use of the Gaia EDR3 data exist (as described in Gaia Collaboration et al. 2020a) and we summarise here the most important ones that users of Gaia EDR3 should be aware of:
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The validation of Gaia EDR3 was done in various stages and led to the decision to filter out small parts of the available data before publication (see also Fabricius et al. 2021). The applied filters are summarised in Gaia Collaboration et al. (2020a) and details can be found in the data processing papers listed above and in this documentation.
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The survey represented by Gaia EDR3 is essentially complete between and mag. At the bright end ( mag), the completeness has essentially remained unchanged compared to Gaia DR2 while it has slightly improved at the faint end. More details on the survey completeness can be found in the papers listed above and in Chapter 8. No attempt has been made at deriving a selection function for Gaia EDR3.
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During the data processing for this release (and all earlier releases), all sources have been treated as single stars. This means that, for binary and multiple stellar systems, the astrometry – as well as the median radial velocity – is less accurate since the astrometric parameters may refer to either component or to the photocentre of the system such that, for instance, the proper motion may represent the mean motion of either component or of the photocentre over the 34 months of data included in the Gaia EDR3 solution. Sources that are not single stars are not marked as such in the catalogue.
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In the astrometric processing, the colour of each source has been included in the form of the effective wave number. This wave number has preferentially been derived from the flux as a function of wavelength in the BP and RP prism spectra, leading to classical 5-parameter astrometric solutions, or has been estimated as pseudo-colour along with the astrometric parameters in the astrometric processing, leading to 6-parameter astrometric solutions. The resulting two solution types have globally different uncertainties and systematics, with 6-parameter astrometry in general being less precise. For 5-parameter solutions, the published astrometric uncertainties are underestimated by 5% at the faint end ( mag) and by up to 30% at the bright end ( mag). For 6-parameter solutions, these numbers are 20% and up to 40%, respectively. As shown in Lindegren et al. (2021), the underestimation of the published uncertainties increases in crowded areas, such as the Magellanic Clouds, and for sources that have indications that they may have companions or be part of a partially resolved double.
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For sources that are separated on the sky by – arcsec, such that they are only occasionally resolved in the Gaia transits, ambiguity in the observation-to-source matching can lead to spurious parallax values that are very large (positive or negative) and appear highly significant. Such sources tend to be faint and located in crowded regions. Guidance on how to clean samples from spurious astrometry based on the renormalised unit weight error (RUWE) diagnostic, that is part of Gaia EDR3, is provided in Lindegren et al. (2021).
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The spatial resolution of Gaia EDR3 has improved with respect to Gaia DR2 and incompleteness in close pairs of stars starts below separations of 1.5 arcsec. Below 0.7 arcsec, the completeness in close source pairs decreases very rapidly. Nonetheless, the treatment of such sources has been improved and close pairs with separations between 0.18 and 0.4 arcsec which were erroneously considered duplicate sources in Gaia DR2 appear as two sources in Gaia EDR3 (although such pairs may still represent spurious solutions). New quality indicators in Gaia EDR3 that are related to the image parameter determination step provide useful indications whether, for instance, a source is one of a close pair (and possibly a binary) or whether it suffers from nearby disturbing sources. Fabricius et al. (2021) shows, for instance, that the parameter ipd_gof_harmonic_amplitude is useful for identifying spurious solutions of resolved doubles, which are not correctly handled in the Gaia EDR3 astrometric processing.
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Systematic errors in the parallaxes are estimated to be below the mas level (Lindegren et al. 2021). As in Gaia DR2, there is an overall parallax zero point which, from an examination of QSO parallaxes, is estimated to be mas (in the sense of the Gaia EDR3 parallaxes being too small). The parallax zero point depends on the sample of sources examined and varies as a function of magnitude, colour, and celestial position. A tentative correction recipe, treating sources with 5- and 6-parameter astrometry separately, to remove the parallax bias as a function of source magnitude, colour, and ecliptic latitude is presented in Lindegren et al. (2020). In addition to a global zero point, there are also regional systematic errors as well as source-to-source correlations in the errors (which also affect the other astrometric parameters). More information is provided in Lindegren et al. (2021), Lindegren et al. (2020), Fabricius et al. (2021), and Chapter 8.
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Due to background estimation inaccuracies, source colours for faint stars, in crowded regions, and in the surroundings of bright stars can be unreliable. One should treat colour-magnitude diagrams constructed for these cases with care. For faint red sources, the flux in the BP band is typically overestimated which causes such sources to appear much bluer in than they should be. When studying the lower main sequence, using as colour index is recommended.
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The Gaia EDR3 catalogue contains a field, phot_bp_rp_excess_factor, which can be used to judge the extent to which the photometry of a given source is compromised. Compared to Gaia DR2, the flux excess factor in Gaia EDR3 is more representative of astrophysical inconsistencies between the fluxes in BP/RP and , for example due to the extended nature of a source or a non-standard (non-stellar) spectral energy distribution. In contrast to Gaia DR2, no filtering on the flux excess factor has been done in Gaia EDR3. Users are recommended to apply a suitable filter themselves, following the guidelines defined in Riello et al. (2020). This paper also presents a corrected version of the flux excess factor which is recommended for use instead of the ‘raw’ phot_bp_rp_excess_factor value published in Gaia EDR3. Two new photometric data quality indicators are included in Gaia EDR3 (phot_bp_n_blended_transits and phot_bp_n_contaminated_transits, and similar for RP). These allow filtering of sources according to the probability that their photometry is affected by crowding. Details can be found in Riello et al. (2020) and in Chapter 8 of this documentation.
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The published magnitudes of bright stars should be corrected for saturation effects (bright means mag for photometry and mag for and photometry). Users are also advised to correct the published -band photometry for sources fainter than mag with 6-parameter astrometric solutions (field astrometric_params_solved) to bring them onto the photometric system of the 5-parameter sources. Details are provided in Riello et al. (2020).
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Gaia EDR3 does not contain new radial velocities but essentially contains copies of the Gaia DR2 values (see Katz et al. 2019)). Details are explained in Seabroke et al. (2020), where it is clarified that a careful tracing of Gaia DR2 sources to their Gaia EDR3 counterparts and a filtering of spurious values (mostly in the extreme tails of the distribution) has been implemented, resulting in entries (with 97% of the Gaia EDR3 sources with a radial velocity having the same source ID as in Gaia DR2).
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Gaia EDR3 should be treated as an independent catalogue from Gaia DR2. In particular the photometric systems of the two catalogues differ (see Riello et al. 2020) and the source list has changed (see Torra et al. 2020). Although changes in the source list are modest (affecting less than 3% of the sources), tracing sources from Gaia DR2 to Gaia EDR3 should not be done by blindly matching source IDs but through us of the dr2_neighbourhood match table from Gaia DR2 to Gaia EDR3 (see Marrese et al. 2021, and Section 13.3).
Summary of miscellaneous links:
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Gaia archive (data access);
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Gaia EDR3 Chapter 13 Datamodel description (table and field descriptions);
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Gaia mission home page (news, user forum, images, publications, outreach material, etc.);
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Contents:
- I Introduction to Gaia Early Data Release 3
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II Gaia data processing
- 2 Simulated data
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3 Pre-processing
- 3.1 Introduction
- 3.2 Properties of the input data
- 3.3 Calibration models
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3.4 Processing steps
- 3.4.1 Overview
- 3.4.2 Daily and cyclic processing
- 3.4.3 Raw data reconstruction
- 3.4.4 Basic angle variation determination
- 3.4.5 On-ground attitude reconstruction (IOGA, OGA1, OGA2 and SDMOGA)
- 3.4.6 Barycentric radial velocity correction (BVC)
- 3.4.7 CCD bias and non-uniformity
- 3.4.8 CCD health, charge injections and release
- 3.4.9 Low-resolution background
- 3.4.10 Line and Point Spread Functions
- 3.4.11 Astrometric Image Parameters determination
- 3.4.12 Spectro-Photometric Image Parameters determination
- 3.4.13 Cross-match processing
- 3.5 Quality assessment and validation
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4 Astrometric data
- 4.1 Introduction
- 4.2 Properties of the input data
- 4.3 Calibration models
- 4.4 Processing steps
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4.5 Quality assessment and validation
- 4.5.1 Overview
- 4.5.2 Properties of the astrometric data
- 4.5.3 Source verification
- 4.5.4 Attitude verification
- 4.5.5 Geometric calibration verification
- 4.5.6 Comparisons of alternative solutions
- 4.5.7 Correlations in the Gaia data
- 4.5.8 Comparisons with space-based astrometry
- 4.5.9 Comparisons with ground-based astrometry
- 4.5.10 Astronomical checks of the data
- 4.5.11 Conclusions
- 5 Photometric data
- 6 Spectroscopy
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III Gaia catalogue
- 7 Consolidation
- 8 Validation
- 9 Cross-match with external catalogues
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10 Cross-match with Gaia DR2
- 10.1 Motivation
- 10.2 Table generation
- 10.3 Quick inspection
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10.4 ADQL queries
- 10.4.1 Gaia DR2 neighbourhood table generation
- 10.4.2 General statistics
- 10.4.3 Closest Gaia EDR3 neighbour to each Gaia DR2 source
- 10.4.4 Gaia DR2 source_id within and without Gaia EDR3 distance histogram
- 10.4.5 G magnitude difference for neighbours within 100 mas
- 10.4.6 High proper motion stars: distance vs proper motion
- 10.4.7 High proper motion stars: angular distance and magnitude difference histograms
- 11 Catalogue statistics and plots
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IV Gaia archive
- 12 ESA Gaia Archive
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13 Datamodel description
- 13.1 Main tables
- 13.2 External catalogues
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13.3 Crossmatches
- 13.3.1 allwise_best_neighbour
- 13.3.2 allwise_neighbourhood
- 13.3.3 apassdr9_best_neighbour
- 13.3.4 apassdr9_neighbourhood
- 13.3.5 apassdr9_join
- 13.3.6 gsc23_best_neighbour
- 13.3.7 gsc23_join
- 13.3.8 gsc23_neighbourhood
- 13.3.9 hipparcos2_best_neighbour
- 13.3.10 hipparcos2_neighbourhood
- 13.3.11 panstarrs1_best_neighbour
- 13.3.12 panstarrs1_join
- 13.3.13 panstarrs1_neighbourhood
- 13.3.14 ravedr5_best_neighbour
- 13.3.15 ravedr5_join
- 13.3.16 ravedr5_neighbourhood
- 13.3.17 sdssdr13_best_neighbour
- 13.3.18 sdssdr13_join
- 13.3.19 sdssdr13_neighbourhood
- 13.3.20 skymapperdr2_best_neighbour
- 13.3.21 skymapperdr2_join
- 13.3.22 skymapperdr2_neighbourhood
- 13.3.23 tmass_psc_xsc_best_neighbour
- 13.3.24 tmass_psc_xsc_join
- 13.3.25 tmass_psc_xsc_neighbourhood
- 13.3.26 tycho2tdsc_merge_best_neighbour
- 13.3.27 tycho2tdsc_merge_neighbourhood
- 13.3.28 urat1_best_neighbour
- 13.3.29 urat1_neighbourhood
- 13.4 Auxiliary tables
- 13.5 Simulation tables
- 13.6 Differences between the Gaia EDR3 and DR2 data models
- Miscellaneous
- Bibliography
List of Figures:
- 1.1 Payload overview
- 1.2 Focal-plane layout
- 1.3 Sampling classes
- 1.4 CCD detector layout
- 1.5 Science data rate
- 1.6 Basic-angle-monitor overview
- 1.7 Service-module overview
- 1.8 Scanning-law overview
- 1.9 Non-accessible regions for Solar-system-object detections
- 1.10 DPAC organigramme
- 1.11 Data flow
- 1.12 Focus evolution as function of time
- 1.13 Focus evolution over the field-of-views
- 1.14 Evolution of the telescope transmission
- 1.15 Single-star detection efficiency
- 1.16 Focal-plane temperature
- 1.17 Examples of prompt-particle events
- 1.18 Prompt-particle-event telemetry data
- 1.19 Comparison of prompt-particle-event fluxes measured in space
- 1.20 Solar activity
- 1.21 Fractional-charge-loss results
- 1.22 Predicted first-pixel response for May 2020
- 1.23 Example across-scan charge-injection profiles
- 1.24 Example evolution of a serial CTI curve
- 2.1 GUMS Scuti amplitude-period relation
- 3.1 Video chain offset versus measured total detection noise
- 3.2 Video chain total detection noise as measured from prescan sample fluctuations
- 3.3 Electronic offset level in AF2 on row 4 of the Gaia FPA
- 3.4 Detail of variation in electronic bias in device AF2 on row 4
- 3.5 Example of hot column evolution
- 3.6 Example across-scan charge injection profiles
- 3.7 Example charge release curves
- 3.8 Average background levels over the focal plane
- 3.9 Examples of background calibration methods
- 3.10 The S-spline
- 3.11 IDU, AGIS, and PhotPipe system operation
- 3.12 Schematic overview of the attitude processing modules and products
- 3.13 Schematic overview of the SDMOGA attitude processing
- 3.14 Baseline offset stability for CCDs in row 1
- 3.15 Reference systems used in cross-match
- 3.16 Density map of on-board detections around bright objects
- 3.17 Spurious detections of two scans of Sirius
- 3.18 Spurious detections from several Saturn transits
- 3.19 Cat’s Eye Planetary Nebula (NGC 6543)
- 3.20 Detection grouping in the cross-match
- 3.21 Cross-match solution around Luyten’s star (HIP 36208)
- 3.22 Sky region checks in daily pre-processing
- 3.23 Photometric checks in daily pre-processing
- 3.24 Attitude and motion checks in daily pre-processing
- 3.25 Attitude correction checks in daily pre-processing
- 3.26 Attitude rate checks in daily pre-processing
- 3.27 Monitoring of readout noise per CCD
- 3.28 Monitoring of astrophysical background per CCD
- 3.29 Astrometric image parameter checks in daily pre-processing
- 3.30 Preliminary cross-match checks in daily pre-processing
- 4.1 Overview of the astrometric processing
- 4.2 Global astrometric model
- 4.3 Definition of the heliotropic spin phase
- 4.4 Schematic view of the BAM CCD with acquisition windows
- 4.5 Organization of the cross-correlations of the BAM data
- 4.6 Fringe shifts derived from BAM data
- 4.7 Fringe shifts derived from BAM data (zoom)
- 4.8 RMS residuals of the model fit to BAM data
- 4.9 Model fit to a jump in BAM data
- 4.10 Pseudo-colour versus effective wavelength
- 4.11 Definition of observation lines in field angles
- 4.12 Time axes for the geometric instrument calibration
- 4.13 Quantities derived from the observation index
- 4.14 Psi functions for the calibration–reference frame degeneracy
- 4.15 Spin of the primary AGIS solution
- 4.16 Observation lines in local plane coordinates
- 4.17 Chromaticity and the locations of images in the the pixel stream
- 4.18 Overall outer AGIS-PhotPipe-IDU iteration scheme
- 4.19 Cross-match validation: error histograms
- 4.20 Residual distribution of the primary AGIS solution
- 4.21 Residuals of the primary AGIS solution versus magnitude
- 4.22 Cross-validation of parallaxesversus magnitude
- 4.23 Cross-validation of parallaxes versus position
- 4.24 Large-scale geometric calibration
- 4.25 Chromaticity calibration
- 4.26 Chromaticity calibration for sources with default colour
- 5.1 Photometric calibration summary
- 5.2 Definition of SSC bands
- 5.3 SSC dependency with colour
- 5.4 Initialization of photometric reference system
- 5.5 Examples of stray light maps
- 5.6 Examples of residual background correction
- 5.7 Epoch spectra for a SPSS source
- 5.8 Epoch spectra for an emission line source
- 5.9 Residuals between Gaia DR3 and synthetic magnitudes (preliminary passbands)
- 5.10 Correction in the G photometry
- 5.11 Colour-colour diagram of high galactic latitude sources
- 5.12 Residuals between Gaia DR3 and synthetic magnitudes (final passbands)
- 5.13 Gaia EDR3 , BP and RP passbands
- 5.14 Residuals between Gaia DR3 and synthetic magnitudes for SPSS and PVL
- 5.15 Gaia EDR3 photometric uncertainties
- 5.16 Excess Flux
- 5.17 Excess Flux Simulations
- 5.18 Residuals between Gaia DR3 and synthetic magnitudes for a selected sample
- 5.19 residuals for SPSS and PVL
- 5.20 Hipparcos diagrams
- 5.21 Tycho-2 diagrams
- 5.22 SDSS diagrams
- 5.23 SDSS diagrams
- 5.24 Relationships between Johnson-Cousins and Gaia systems
- 5.25 Relationships between Johnson-Cousins and Gaia systems
- 5.26 Relationships between 2MASS and Gaia systems
- 5.27 Relationships between 2MASS and Gaia systems
- 5.28 Relationships between GSC2.3 and Gaia systems
- 5.29 Relationships between GSC2.3 and Gaia systems
- 5.30 Relationships between GSC2.3 and Gaia systems
- 5.31 Absolute colour-magnitude diagram of the SPSS and PVL samples
- 6.1 Trending Epochs
- 6.2 Pipeline workflows overview
- 6.3 Straylight map
- 6.4 RVS spectrum of a wavelength calibration star
- 6.5 STA flowchart
- 6.6 Barycentric velocity correction
- 6.7 Wavelength-calibration model
- 6.8 Radial velocities accuracy
- 6.9 Radial velocities precision
- 6.10 Six spectral types
- 8.1 Source separation histogram in dense area.
- 8.2 Source separation histogram in sparse area.
- 8.3 Holes in the sky.
- 8.4 Bright star artefacts.
- 8.5 Astrometric GoF vs magnitude
- 8.6 Excess Flux
- 8.7 SSC quotients for faint sources
- 8.8 Effect of photometric filtering
- 8.9 Star counts
- 8.10 Average star counts
- 8.11 Median of parallaxes
- 8.12 Average parallax per magnitude
- 8.13 Median of proper motions
- 8.14 Median of proper motions
- 8.15 Average proper motions
- 8.16 Median of radial velocities
- 8.17 Average radial velocities
- 8.18 Median of
- 8.19 Difference of colour as a function of magnitude
- 8.20 2d KLD comparison: edr3int3 and Gaia DR2.
- 8.21 2d KLD 10% deviation: edr3int3 and Gaia DR2.
- 8.22 Example subspace where KLD increases in edr3int3: NObs.
- 8.23 Example subspace where KLD increases in edr3int3: errors.
- 8.24 Example subspace where KLD decreases in edr3int3
- 8.25 2D KLD comparison: edr3int3 and edr3int3-subsets
- 8.26 3D KLD comparison: edr3int3 and Gaia DR2.
- 8.27 phot_g_mean_flux_error vs. ra and dec.
- 8.28 pmra_error vs. ra and dec.
- 8.29 Comparison between mean magnitudes provided in the Gaia DR2 and Gaia EDR3 catalogues for candidate RR Lyrae stars.
- 8.30 Parallax trends for NGC2437
- 8.31 Difference between Gaia EDR3 parallaxes for single stars and the median parallax of the cluster
- 8.32 Proper motion distribution in magnitude and color for the cluster NGC 7099
- 8.33 Color magnitude diagram of M4
- 8.34 The scaled dispersion of the pms in M4
- 8.35 Color magnitude diagram of NGC2516
- 8.36 CMDs in the inner (blue) and outer (black) regions of NGC5986
- 8.37 Difference between -
- 8.38 Global Completeness as a function of for the whole sample of globulars
- 8.39 Inner / outer region completeness for NGC 2298
- 8.40 Inner / outer region completeness for NGC 5053
- 8.41 Inner / outer region completeness for NGC 5286
- 8.42 Stars in NGC 6809 with astrometry, but not photometry
- 8.43 Percentage of stars in NGC 6913 with astrometry, but not photometry
- 10.1 Closest Gaia EDR3 neighbour to each Gaia DR2 source
- 10.2 Gaia DR2 source_id within and without Gaia EDR3 distance histogram
- 10.3 G magnitude difference for neighbours within 100 mas
- 10.4 High proper motion stars: distance vs proper motion
- 10.5 High proper motion stars: angular distance and magnitude difference histograms
- 11.1 HEALPix map of density count for all sources, 5p and 6p solutions in galactic coordinates
- 11.2 HEALPix map of density count for all sources, 5p and 6p solutions in ecliptic coordinates
- 11.3 HEALPix map of median , and magnitudes
- 11.4 HEALPix map of median , and colours
- 11.5 HEALPix map of median signal-to-noise ratio for G, and
- 11.6 Histograms of the number of sources as a function of , , and .
- 11.7 Median Signal-to-noise ratio in the colour-magnitude plane for G, and , respectively.
- 11.8 Sky distribution and 2D histograms of the excess factor as a function of and colour.
- 11.9 HEALPix maps of the median right ascension error for 2p, 5p and 6p solutions
- 11.10 HEALPix maps of the median declination error for 2p, 5p and 6p solutions
- 11.11 2D histogram for right ascension error as a function of for 2p, 5p and 6p solutions
- 11.12 2D histogram for declination error as a function of for 2p, 5p and 6p solutions
- 11.13 HEALPix map of the median parallax for 5p and 6p solutions. Histogram of parallax.
- 11.14 HEALPix map of the median parallax error for 5p and 6p solutions. Histogram of parallax error.
- 11.15 2D Histogram of parallax error as a function of for 5p and 6p solutions
- 11.16 HEALPix maps of median proper motion for all, 5p and 6p solutions
- 11.17 Histograms of pmra and pmdec error for all, 5p and 6p solutions
- 11.18 HEALPix maps of median pmra_error for all, 5p and 6p solutions
- 11.19 HEALPix maps of median pmdec_error for all, 5p and 6p solutions
- 11.20 HEALPix maps of median pm error for all, 5p and 6p solutions
- 11.21 pm error as a function of magnitude for all sources, 5p and 6p solutions
- 11.22 Histogram of , , ,
- 11.23 Histogram of , ,
- 11.24 Histogram of , ,
- 11.25 HEALPix maps of the median of , , ,
- 11.26 HEALPix maps of the median of , ,
- 11.27 HEALPix maps of the median of , ,
- 11.28 HEALPix maps of the median of astrometric_n_good_obs_al for all sources, 5p and 6p solutions.
- 11.29 HEALPix maps of median astrometric_matched_transits for all, 5p and 6p solutions.
- 11.30 Number of astrometric_n_good_obs_al as a function of for all sources, 5p and 6p solutions.
- 11.31 Number of astrometric_matched_transits as a function of for all sources, 5p and 6p solutions.
- 11.32 phot_g_n_obs as a function of for all sources, 5p and 6p solutions.
- 11.33 phot_bp_n_obs as a function of for all sources, 5p and 6p solutions.
- 11.34 phot_rp_n_obs as a function of for all sources, 5p and 6p solutions.
- 11.35 dr2_rv_nb_transits as a function of for all sources, 5p and 6p solutions.
- 11.36 HEALPix map of dr2_rv_nb_transits per source and sources with
- 11.37 HEALPix map, histogram 2D of median as function of mangitude and histogram of
- 11.38 HEALPix map, histogram 2D of median error by mangitude and histogram of error in
- 11.39 HEALPix map of median , and [Fe/H] from the RVS templates
- 11.40 HEALPix maps of median ruwe for all sources, 5p and 6p solutions.
- 11.41 Histogram of ruwe for 5p and 6p, ruwe by parallax error all sources, median visibility_periods_used
- 11.42 HEALPix map of median astrometric pseudocolour and pseudocolour_error for 6p solution
- 11.43 HEALPix map of median visibility_periods_used and distribution of the astrometric_gof_al as a function of visibility_periods_used and of parallax_error
- 11.44 1D histogram of the ipd_frac_multi_peak and its distribution by magnitude and parallax
- 12.1 Access to external TAP services
- 12.2 Selection of associated datalink products to query results
List of Tables:
- 1.1 Calibration faint stars
- 1.2 Sampling classes
- 1.3 CCD TDI gates
- 1.4 Dense areas with special sky-mapper imaging data
- 1.5 Transit variations over the sky
- 1.6 Coordination units in DPAC
- 1.7 Time coverage of Gaia Early Data Release 3
- 1.8 Scanning laws used in Gaia Early Data Release 3
- 1.9 Orbit-maintenance manoeuvres
- 1.10 Decontamination and re-focus operations
- 1.11 Data deletion on board
- 1.12 Serial-CTI-calibration runs
- 1.13 Flat-band-voltage-shift-calibration operations
- 1.14 Non-uniformity-calibration runs
- 2.1 GUMS population evolution
- 2.2 GUMS stellar density laws
- 2.3 GUMS warp parameters
- 2.4 GUMS bar parameters
- 2.5 GUMS spiral arms parameters
- 2.6 GUMS abundances
- 2.7 GUMS velocity dispersions
- 2.8 GUMS regular and semi-regular variable characteristics
- 2.9 GOG RVS performance parameters
- 3.1 Total detection noise
- 3.2 Fitted parameters and 2D spline configuration for 1D LSF calibrations
- 3.3 Fitted parameters and 3D spline configuration for 2D PSF long gate (11, 12, 0) calibrations
- 3.4 Fitted parameters and 2D spline configuration for 2D PSF short gate (4-10) calibrations
- 3.5 Main daily and cyclic pre-processing steps
- 4.1 Main astronomical and physical constants (TCB-compatible values) used in INPOP10e
- 4.2 Gaps in the BAM data not bridged by the cross-correlation method
- 4.3 Source with radial velocities from literature for perspective acceleration
- 4.4 Summary statistics on sources with 5-parameters solutions
- 4.5 Summary statistics on sources with 6-parameters solutions
- 4.6 Summary statistics on sources with position-only solutions
- 5.1 Wavelength boundaries for SSC bands
- 5.2 VEGAMAG Zeropoints
- 5.3 Flux calibration factors
- 5.4 Filters applied to fit the photometric relationships
- 5.5 Filters applied to fit the photometric relationships (cont)
- 5.6 Coefficients of the photometric transformations.
- 5.7 Coefficients of the photometric transformations.
- 5.8 Range of applicability for the relationships
- 6.1 Spectroscopic data
- 6.2 The 28 model spectra of the restricted library.
- 6.3 The external radial velocity catalogues
- 7.1 Origin of the sources
- 7.2 Distribution of updates from AGIS-03
- 7.3 Distribution of position origins
- 7.4 Distribution of proper motion origins
- 11.1 Statistics on the main Catalogue fields