20.1.1 gaia_source
This table has an entry for every Gaia observed source as published with this data release. It contains the basic source parameters, in their final state as processed by the Gaia Data Processing and Analysis Consortium from the raw data coming from the spacecraft. The table is complemented with others containing information specific to certain kinds of objects (e.g. Solar–system objects, non–single stars, variables etc.) and value–added processing (e.g. astrophysical parameters etc.). Further array data types (spectra, epoch measurements) are presented separately via ‘Datalink’ resources.
Columns description:
All Gaia data processed by the Data Processing and Analysis Consortium comes tagged with a solution identifier. This is a numeric field attached to each table row that can be used to unequivocally identify the version of all the subsystems that were used in the generation of the data as well as the input data used. It is mainly for internal DPAC use but is included in the published data releases to enable end users to examine the provenance of processed data products. To decode a given solution ID visit https://gaia.esac.esa.int/decoder/solnDecoder.jsp
A source designation, unique across all Gaia Data Releases, that is constructed from the prefix ‘Gaia DRx ’ followed by a string of digits corresponding to source_id (3 space–separated words in total). Note that the integer source identifier source_id is not guaranteed to be unique across Data Releases; moreover it is not guaranteed that the same astronomical source will always have the same source_id in different Data Releases. Hence the only safe way to compare source records between different Data Releases in general is to check the records of proximal source(s) in the same small part of the sky.
A unique numerical identifier of the source, encoding the approximate position of the source (roughly to the nearest arcmin), the provenance (data processing centre where it was created), a running number, and a component number.
The approximate equatorial (ICRS) position is encoded using the nested HEALPix scheme at level 12 (Nside = 4096), which divides the sky into $\simeq 200$ million pixels of about 0.7 arcmin${}^{2}$.
The source ID consists of a 64bit integer, least significant bit = 1 and most significant bit = 64, comprising:

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a HEALPix index number (sky pixel) in bits 36  63; by definition the smallest HEALPix index number is zero.

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a 3bit Data Processing Centre code in bits 33  35; for example MOD(source_id / 4294967296, 8) can be used to distinguish between sources initialised via the Initial Gaia Source List (Smart and Nicastro 2014) by the Torino DPC (code = 0) and sources otherwise detected and assigned by Gaia observations (code $>0$)

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a 25bit plus 7 bit sequence number within the HEALPix pixel in bits 1  32 split into:

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a 25 bit running number in bits 8 – 32; the running numbers are defined to be positive, i.e. never zero

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a 7bit component number in bits 1 – 7

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This means that the HEALPix index at level 12 of a given source is contained in the most significant bits. HEALPix index of level 12 and lower can thus be retrieved as follows:

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HEALPix index at level 12 = source_id / 34359738368

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HEALPix index at level 11 = source_id / 137438953472

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HEALPix index level 10 = source_id / 549755813888

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HEALPix index at level $n$ = source_id / $({2}^{35}\times {4}^{(12n)})$ = source_id / ${2}^{(592n)}$
Additional details can be found in Bastian and Portell (2020).
A random index which can be used to select smaller subsets of the data that are still representative. The column contains a random permutation of the numbers from 0 to $N1$, where $N$ is the number of sources in the table.
The random index can be useful for validation (testing on 10 different random subsets), visualization (displaying 1% of the data), and statistical exploration of the data, without the need to download all the data.
Reference epoch to which the astrometric source parameters are referred, expressed as a Julian Year in TCB.
Barycentric right ascension $\alpha $ of the source in ICRS at the reference epoch ref_epoch
Standard error ${\sigma}_{\alpha *}\equiv {\sigma}_{\alpha}\mathrm{cos}\delta $ of the right ascension of the source in ICRS at the reference epoch ref_epoch.
Barycentric declination $\delta $ of the source in ICRS at the reference epoch ref_epoch
Standard error ${\sigma}_{\delta}$ of the declination of the source in ICRS at the reference epoch ref_epoch
Absolute stellar parallax $\varpi $ of the source at the reference epoch ref_epoch
Standard error ${\sigma}_{\varpi}$ of the stellar parallax at the reference epoch ref_epoch
Parallax divided by its standard error
The total proper motion calculated as the magnitude of the resultant vector of the proper motion component vectors pmra and pmdec, i.e. ${\text{\U0001d699\U0001d696}}^{2}={\text{\U0001d699\U0001d696\U0001d69b\U0001d68a}}^{2}+{\text{\U0001d699\U0001d696\U0001d68d\U0001d68e\U0001d68c}}^{2}$.
Proper motion in right ascension ${\mu}_{\alpha *}\equiv {\mu}_{\alpha}\mathrm{cos}\delta $ of the source in ICRS at the reference epoch ref_epoch. This is the local tangent plane projection of the proper motion vector in the direction of increasing right ascension.
pmra_error : Standard error of proper motion in right ascension direction (float, Angular Velocity[mas yr${}^{1}$] )
Standard error ${\sigma}_{\mu \alpha *}$ of the local tangent plane projection of the proper motion vector in the direction of increasing right ascension at the reference epoch ref_epoch
Proper motion in declination ${\mu}_{\delta}$ of the source at the reference epoch ref_epoch. This is the projection of the proper motion vector in the direction of increasing declination.
pmdec_error : Standard error of proper motion in declination direction (float, Angular Velocity[mas yr${}^{1}$] )
Standard error ${\sigma}_{\mu \delta}$ of the proper motion component in declination at the reference epoch ref_epoch
Correlation coefficient $\rho (\alpha ,\delta )$ between right ascension and declination. This is a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\alpha ,\varpi )$ between right ascension and parallax, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\alpha ,{\mu}_{\alpha *})$ between right ascension and proper motion in right ascension, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\alpha ,{\mu}_{\delta})$ between right ascension and proper motion in declination, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\delta ,\varpi )$ between declination and parallax, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\delta ,{\mu}_{\alpha *})$ between declination and proper motion in right ascension, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\delta ,{\mu}_{\delta})$ between declination and proper motion in declination, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\varpi ,{\mu}_{\alpha *})$ between parallax and proper motion in right ascension, a dimensionless quantity in the range [1,+1].
Correlation coefficient $\rho (\varpi ,{\mu}_{\delta})$ between parallax and proper motion in declination, a dimensionless quantity in the range [1,+1].
pmra_pmdec_corr : Correlation between proper motion in right ascension and proper motion in declination (float)
Correlation coefficient $\rho ({\mu}_{\alpha *},{\mu}_{\delta})$ between proper motion in right ascension and proper motion in declination, a dimensionless quantity in the range [1,+1].
Total number of AL observations (= CCD transits) used in the astrometric solution of the source, independent of their weight. Note that some observations may be strongly downweighted (see astrometric_n_bad_obs_al).
Total number of AC observations (= CCD transits) used in the astrometric solution of the source, independent of their weight (note that some observations may be strongly downweighted). Nearly all sources having G $$ will have AC observations from 2d windows, while fainter than that limit only $\sim 1$% of transit observations (the so–called ‘calibration faint stars’) are assigned 2d windows resulting in AC observations.
Number of AL observations (= CCD transits) that were not strongly downweighted in the astrometric solution of the source. Strongly downweighted observations (with downweighting factor $$) are instead counted in astrometric_n_bad_obs_al. The sum of astrometric_n_good_obs_al and astrometric_n_bad_obs_al equals astrometric_n_obs_al, the total number of AL observations used in the astrometric solution of the source.
Number of AL observations (= CCD transits) that were strongly downweighted in the astrometric solution of the source, and therefore contributed little to the determination of the astrometric parameters. An observation is considered to be strongly downweighted if its downweighting factor $$, which means that the absolute value of the astrometric residual exceeds 4.83 times the total uncertainty of the observation, calculated as the quadratic sum of the centroiding uncertainty, excess source noise, and excess attitude noise.
Goodnessoffit statistic of the astrometric solution for the source in the alongscan direction. This is the ‘gaussianized chisquare’, which for good fits should approximately follow a normal distribution with zero mean value and unit standard deviation. Values exceeding, say, $+3$ thus indicate a bad fit to the data.
This statistic is computed according to the formula
$\mathtt{\text{astrometric\_gof\_al}}={(9\nu /2)}^{1/2}[{\text{\U0001d69b\U0001d69e\U0001d6a0\U0001d68e}}^{2/3}+2/(9\nu )1]$
where ruwe is the renormalised unit weight error and
$\nu =\mathtt{\text{astrometric\_n\_good\_obs\_al}}N$
is the number of degrees of freedom for a source update. Here $N=5$ for 2parameter and 5parameter solutions (respectively astrometric_params_solved = 3 or 31) and 6 for 6parameter solutions (astrometric_params_solved = 95).
Note that only ‘good’ (i.e. not strongly downweighted) observations are included in $\nu $. For further details please see Lindegren et al. (2021b).
Astrometric goodnessoffit (${\chi}^{2}$) in the AL direction.
${\chi}^{2}$ values were computed for the ‘good’ AL observations of the source, without taking into account the astrometric_excess_noise (if any) of the source. They do however take into account the attitude excess noise (if any) of each observation.
This is the excess noise ${\u03f5}_{i}$ of the source. It measures the disagreement, expressed as an angle, between the observations of a source and the bestfitting standard astrometric model (using five astrometric parameters). The assumed observational noise in each observation is quadratically increased by ${\u03f5}_{i}$ in order to statistically match the residuals in the astrometric solution. A value of 0 signifies that the source is astrometrically wellbehaved, i.e. that the residuals of the fit statistically agree with the assumed observational noise. A positive value signifies that the residuals are statistically larger than expected.
The significance of ${\u03f5}_{i}$ is given by astrometric_excess_noise_sig ($D$). If $D\le 2$ then ${\u03f5}_{i}$ is probably not significant, and the source may be astrometrically wellbehaved even if ${\u03f5}_{i}$ is large.
The excess noise ${\u03f5}_{i}$ may absorb all kinds of modelling errors that are not accounted for by the observational noise (image centroiding error) or the excess attitude noise. Such modelling errors include LSF and PSF calibration errors, geometric instrument calibration errors, and part of the highfrequency attitude noise. These modelling errors are particularly important in the early data releases, but should decrease as the astrometric modelling of the instrument and attitude improves over the years.
Additionally, sources that deviate from the standard fiveparameter astrometric model (e.g. unresolved binaries, exoplanet systems, etc.) may have positive ${\u03f5}_{i}$. Given the many other possible contributions to the excess noise, the user must study the empirical distributions of ${\u03f5}_{i}$ and $D$ to make sensible cutoffs before filtering out sources for their particular application.
The excess source noise is further explained in Sections 3.6 and 5.1.2 of
Lindegren et al. (2012).
A dimensionless measure ($D$) of the significance of the calculated astrometric_excess_noise (${\u03f5}_{i}$). A value $D>2$ indicates that the given ${\u03f5}_{i}$ is probably significant.
For good fits in the limit of a large number of observations, $D$ should be zero in half of the cases and approximately follow the positive half of a normal distribution with zero mean and unit standard deviation for the other half. Consequently, $D$ is expected to be greater than 2 for only a few percent of the sources with wellbehaved astrometric solutions.
In the early data releases ${\u03f5}_{i}$ will however include instrument and attitude modelling errors that are statistically significant and could result in large values of ${\u03f5}_{i}$ and $D$. The user must study the empirical distributions of these statistics and make sensible cutoffs before filtering out sources for their particular application.
The excess noise significance is further explained in Section 5.1.2 of
Lindegren et al. (2012).
The seven bits of astrometric_params_solved indicate which parameters have been estimated in AGIS for this source. A set bit means the parameter was updated, an unset bit means the parameter was not updated. The leastsignificant bit corresponds to ra. The table below shows the values of astrometric_params_solved for relevant combinations of the parameters.
The radial proper motion (${\mu}_{r}$) is formally considered to be one of the astrometric parameters of a source, and the sixth bit is therefore reserved for it. It is also in principle updatable in AGIS, but in practice it will always be computed from a spectroscopic radial velocity and the estimated parallax, in which case the bit is not set.
$C$ is the pseudocolour of the source, i.e. the astrometrically estimated effective wavenumber.
astrometric_params_solved  ra  dec  parallax  pmra  pmdec  ${\mu}_{r}$  $C$ 
${0000011}_{2}=3$  ✓  ✓  
${0000111}_{2}=7$  ✓  ✓  ✓  
${0011011}_{2}=27$  ✓  ✓  ✓  ✓  
${0011111}_{2}=31$  ✓  ✓  ✓  ✓  ✓  
${0111111}_{2}=63$  ✓  ✓  ✓  ✓  ✓  ✓  
${1011111}_{2}=95$  ✓  ✓  ✓  ✓  ✓  ✓ 
In practice all the sources in DR3 have only values of 3, 31 or 95 for the $\mathrm{\U0001d68a\U0001d69c\U0001d69d\U0001d69b\U0001d698\U0001d696\U0001d68e\U0001d69d\U0001d69b\U0001d692\U0001d68c}\mathrm{\_}\mathrm{\U0001d699\U0001d68a\U0001d69b\U0001d68a\U0001d696\U0001d69c}\mathrm{\_}\mathrm{\U0001d69c\U0001d698\U0001d695\U0001d69f\U0001d68e\U0001d68d}$, corresponding to twoparameter (position), fiveparameter (position, parallax, and proper motion) and sixparameter (position, parallax, proper motion and astrometrically estimated effective wavenumber) solutions.
Flag indicating if this source was used as a primary source (true) or secondary source (false). Only primary sources contribute to the estimation of attitude, calibration, and global parameters. The estimation of source parameters is otherwise done in exactly the same way for primary and secondary sources.
nu_eff_used_in_astrometry : Effective wavenumber of the source used in the astrometric solution (float, Misc[$\mu {m}^{1}$])
Effective wavenumber of the source, ${\nu}_{\text{eff}}$, in $\mu $m${}^{1}$.
This ${\nu}_{\text{eff}}$ is the value used in the image parameter determination and in the astrometric calibration if reliable mean BP and RP photometry were available. It is the photonflux weighted inverse wavelength, as estimated from the BP and RP bands. The field is provided for astrometric solutions with five parameters but is empty for those with two or six parameters.
Due to cyclic processing of the astrometry and the photometry, this effective wavenumber might be different from the one computed using the latest available photometry. Moreover, if no reliable photometry was available at the time of the astrometric processing, this field is empty and an astrometrically estimated value of the effective wavenumber may instead be given in the pseudocolour field.
Effective wavenumber of the source estimated in the final astrometric processing.
The pseudocolour is the astrometrically estimated effective wavenumber of the photon flux distribution in the astrometric ($G$) band, measured in $\mu $m${}^{1}$. The value in this field was estimated from the chromatic displacements of image centroids, calibrated by means of the photometrically determined effective wavenumbers (${\nu}_{\text{eff}}$) of primary sources.
The field is empty when chromaticity was instead taken into account using the photometrically determined ${\nu}_{\text{eff}}$ given in the field nu_eff_used_in_astrometry.
Standard error ${\sigma}_{\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b}}$ of the astrometrically determined pseudocolour of the source.
Correlation coefficient $\rho (\alpha ,\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b})$ between right ascension ra and pseudocolour, a dimensionless quantity in the range [1,+1]
Correlation coefficient $\rho (\delta ,\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b})$ between declination dec and pseudocolour, a dimensionless quantity in the range [1,+1]
Correlation coefficient $\rho (\varpi ,\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b})$ between parallax and pseudocolour, a dimensionless quantity in the range [1,+1]
pmra_pseudocolour_corr : Correlation between proper motion in right asension and pseudocolour (float)
Correlation coefficient $\rho ({\mu}_{\alpha *},\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b})$ between proper motion in right ascension pmra and pseudocolour, a dimensionless quantity in the range [1,+1]
Correlation coefficient $\rho ({\mu}_{\delta},\mathrm{\U0001d699\U0001d69c\U0001d68e\U0001d69e\U0001d68d\U0001d698\U0001d68c\U0001d698\U0001d695\U0001d698\U0001d69e\U0001d69b})$ between proper motion in declination pmdec and pseudocolour, a dimensionless quantity in the range [1,+1]
The number of field–of–view transits matched to this source, counting only the transits containing CCD observations actually used to compute the astrometric solution.
This number will always be equal to or smaller than matched_transits, the difference being the FOV transits that were not used in the astrometric solution because of bad data or excluded time intervals.
Number of visibility periods used in the astrometric solution.
A visibility period is a group of observations separated from other groups by a gap of at least 4 days. A source may have from one to tens of field–of–view transits in a visibility period, but with a small spread in time, direction of scanning, and parallax factor. From one visibility period to the next these variables have usually changed significantly. A high number of visibility periods is therefore a better indicator of an astrometrically well–observed source than a large number of field–of–view transits (matched_transits or astrometric_matched_transits) or CCD observations (astrometric_n_obs_al). A small value (e.g. less than 10) indicates that the calculated parallax could be more vulnerable to errors, e.g. from the calibration model, not reflected in the formal uncertainties. See Lindegren et al. (2018) for a discussion of this and other astrometric quality indicators.
astrometric_sigma5d_max : The longest semimajor axis of the 5d error ellipsoid (float, Angle[mas])
The longest principal axis in the 5dimensional error ellipsoid.
This is a 5dimensional equivalent to the semimajor axis of the position error ellipse and is therefore useful for filtering out cases where one of the five parameters, or some linear combination of several parameters, is particularly illdetermined. It is measured in mas and computed as the square root of the largest singular value of the scaled $5\times 5$ covariance matrix of the astrometric parameters. The matrix is scaled so as to put the five parameters on a comparable scale, taking into account the maximum alongscan parallax factor for the parallax and the time coverage of the observations for the proper motion components. If $C$ is the unscaled covariance matrix, the scaled matrix is $SCS$, where $S=\text{diag}(1,1,\mathrm{sin}\xi ,T/2,T/2)$, $\xi ={45}^{\circ}$ is the solar aspect angle in the nominal scanning law, and $T$ the time coverage of the data used in the solution.
astrometric_sigma5d_max is given for all the solutions, as its size is one of the criteria for accepting or rejecting the 5 or 6parameter solution. In case of a 2 parameter solution (astrometric_params_solved = 3) it gives the value for the rejected 5 or 6parameter solution, and can then be arbitrarily large.
The total number of field–of–view transits matched to this source.
new_matched_transits : The number of transits newly incorporated into an existing source in the current cycle (short)
Individual field–of–view transits are crossmatched into unique sources at the start of each reprocessing cycle taking the source list from the previous cycle as a starting point. During that process a combination of appending, merging and splitting operations is performed to create a more complete and reliable map of unique sources given the available information. Existing individual sources may accrete further transits, may be merged into fewer unique sources, or may split into two or more new, unique sources as more measurements are accumulated. Field new_matched_transits logs the number of transits newly appended to an existing source during the most recent cyclic reprocessing crossmatch. It refers exclusively to the source_id.
matched_transits_removed : The number of transits removed from an existing source in the current cycle (short)
Individual field–of–view transits are crossmatched into unique sources at the start of each reprocessing cycle taking the source list from the previous cycle as a starting point. During that process a combination of appending, merging and splitting operations is performed to create a more complete and reliable map of unique sources given the available information. Existing individual sources may accrete further transits, may be merged into fewer unique sources, or may split into two or more new, unique sources as more measurements are accumulated. Field matched_transits_removed logs the number of transits removed during the most recent cyclic reprocessing crossmatch from those allocated to an existing source during all previous cycles. It refers exclusively to the source_id.
This statistic measures the amplitude of the variation of the Image Parameter Determination (IPD) goodness–of–fit (GoF; reduced chisquare) as function of the position angle of the scan direction. A large amplitude indicates that the source has some nonisotropic spatial structure, for example a binary or galaxy, that is at least partially resolved by Gaia. The phase of the variation is given by the parameter ipd_gof_harmonic_phase.
Let $\psi $ be the position angle of the scan direction. The following expression is fitted to the IPD GoF for the accepted AF observations of the source:
$$\mathrm{ln}(\mathrm{GoF})={c}_{0}+{c}_{2}\mathrm{cos}(2\psi )+{s}_{2}\mathrm{sin}(2\psi )$$ 
The amplitude and phase of the variation are calculated as
$$\mathtt{\text{ipd\_gof\_harmonic\_amplitude}}=\sqrt{{c}_{2}^{2}+{s}_{2}^{2}}$$ 
$$\mathtt{\text{ipd\_gof\_harmonic\_phase}}=\frac{1}{2}\mathrm{atan2}({s}_{2},{c}_{2})\mathit{\hspace{1em}}(+{180}^{\circ})$$ 
where atan2 returns the angle in degrees. In the last expression 180 is added for negative values, so that ipd_gof_harmonic_phase is always between 0 and 180${}^{\circ}$. Only the AF observations accepted by the astrometric solution are used to compute the amplitude and phase, thus for example outliers and observations in the early Ecliptic Pole Scanning Law phase are not used.
The GoF variation is modelled as a periodic function of $2\psi $ because a source with fixed structure is normally expected to give fits of similar quality when scanned in opposite directions ($\psi $ differing by 180${}^{\circ}$). See ipd_gof_harmonic_phase for the interpretation of the phase.
This statistic measures the phase of the variation of the IPD GoF (reduced chisquare) as function of the position angle of the scan direction. See the description of ipd_gof_harmonic_amplitude for details on the computation of the phase.
The interpretation of this parameter is nontrivial because of the complex interaction between the source structure and the IPD. At least the following different scenarios could occur:

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For a binary with separation $\lesssim 0.1$ arcsec the GoF is expected to be higher when the scan is along the arc joining the components than in the perpendicular direction, in which case ipd_gof_harmonic_phase should indicate the position angle of the binary modulo 180${}^{\circ}$. Such a binary will normally have negligible ipd_frac_multi_peak (less than a few per cent).

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For a resolved binary the GoF may instead have a minimum when the scan is along the arc joining the two components, in which case ipd_gof_harmonic_phase differs from the position angle of the binary (modulo 180${}^{\circ}$) by approximately $\pm {90}^{\circ}$. Such a binary will normally have a large ipd_frac_multi_peak.

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For a bright binary ($G\lesssim 13$) the GoF refers to the fitting of a twodimensional PSF, which could further complicate the intrepretation.

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For a galaxy with elongated intensity distribution, the IPD may give a smaller GoF when the scan is along the major axis of the image, resulting in an offset of approximately $\pm {90}^{\circ}$ between the ipd_gof_harmonic_phase and the position angle of the major axis (modulo 180${}^{\circ}$).
This field provides information on the raw windows used for the astrometric processing of this source coming from the Image Parameters Determination (IPD) module in the core processing. It provides the fraction of windows (having a successful IPD result), as percentage (from 0 to 100), for which the IPD algorithm has identified a double peak, meaning that the detection may be a visually resolved double star (either just visual double or real binary). The quantity was computed using all transits where the IPD was successful.
This field is calculated during AGIS and provides information on the raw windows used for the astrometric processing of this source. It provides the fraction (as a percentage, from 0 to 100) of transits having either truncation or multiple gates flagged in one or more windows. Such a situation invariably means that the onboard video processing unit (VPU) detected some nearby source (which may be just a spurious detection, but typically could be some real nearby source — having another distinct transit and most probably assigned to a different source). So in general a non–zero fraction indicates that this source may be contaminated by another nearby source. The quantity was computed using all transits where the IPD was successful.
The Renormalised Unit Weight Error is computed as
$$\text{\U0001d69b\U0001d69e\U0001d6a0\U0001d68e}=\frac{\sqrt{\mathtt{\text{astrometric\_chi2\_al}}/(\mathtt{\text{astrometric\_n\_good\_obs\_al}}m)}}{f(G,{G}_{\text{BP}}{G}_{\text{RP}})}$$ 
where $m$ is the number of parameters solved (the number of set bits in astrometric_params_solved) and $f$ is a renormalising function.
In practice $f$ is determined in an offline statistical analysis of the secondary solutions — see for example ‘Renormalising the astrometric chisquare in Gaia DR2’ (Lindegren 2018b). Also note that this value is set to null for sources with only a twoparameter solution, since this value would be difficult to interpret in such cases.
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 quantify the distribution of AL scan directions across the source. scan_direction_strength_k1 (and similarly 2,3,4) are the absolute value of the trigonometric moments ${m}_{k}=\u27e8\mathrm{exp}(ik\theta )\u27e9$ for $k=1,2,3,4$ where $\theta $ is the position angle of the scan and the mean value is taken over the astrometric_n_good_obs_al observations contributing to the astrometric parameters of the source. $\theta $ is defined in the usual astronomical sense: $\theta =0$ when the FoV is moving towards local North, and $\theta ={90}^{\circ}$ towards local East.
N.B. When astrometric_n_obs_ac $>0$ the scan direction attributes are not provided at Gaia DR3. Hence for all sources brighter than G $\approx 13$, and for a tiny fraction of fainter sources ($\approx 1$%), these 8 scan direction fields will be NULL.
The scan_direction_strength_k1…4 are numbers between 0 and 1, where 0 means that the scan directions are well spread out in different directions, while 1 means that they are concentrated in a single direction (given by the corresponding scan_direction_mean_k1…4).
The different orders $k$ are statistics of the scan directions modulo ${360}^{\circ}/k$. For example, at first order ($k=1$), $\theta ={10}^{\circ}$ and $\theta ={190}^{\circ}$ count as different directions, but at second order ($k=2$) they are the same. Thus, scan_direction_strength_k1 is the degree of concentration when the sense of direction is taken into account, while scan_direction_strength_k2 is the degree of concentration without regard to the sense of direction. A large value of scan_direction_strength_k4 indicates that the scans are concentrated in two nearly orthogonal directions.
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_strength_k1 for further details.
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_strength_k1 for further details.
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_strength_k1 for further details.
scan_direction_mean_k1 : Mean position angle of scan directions across the source (float, Angle[deg])
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source. scan_direction_mean_k1 (and similarly for $k=2,3,4$) is $1/k$ times the argument of the trigonometric moments ${m}_{k}=\u27e8\mathrm{exp}(ik\theta )\u27e9$, where $\theta $ is the position angle of the scan and the mean value is taken over the astrometric_n_good_obs_al observations contributing to the astrometric parameters of the source. $\theta $ is defined in the usual astronomical sense: $\theta =0$ when the FoV is moving towards local North, and $\theta ={90}^{\circ}$ towards local East.
N.B. When astrometric_n_obs_ac $>0$ the scan direction attributes are not provided at Gaia DR3. Hence for all sources brighter than G $\approx 13$, and for a tiny fraction of fainter sources ($\approx 1$%), these 8 scan direction fields will be NULL.
scan_direction_mean_k1 (and similarly for $k=2,3,4$) is an angle between ${180}^{\circ}/k$ and $+{180}^{\circ}/k$, giving the mean position angle of the scans at order $k$.
The different orders $k$ are statistics of the scan directions modulo ${360}^{\circ}/k$. For example, at first order ($k=1$), $\theta ={10}^{\circ}$ and $\theta ={190}^{\circ}$ count as different directions, but at second order ($k=2$) they are the same. Thus, scan_direction_mean_k1 is the mean direction when the sense of direction is taken into account, while scan_direction_mean_k2 is the mean direction without regard to the sense of the direction. For example, scan_direction_mean_k1 = 0 means that the scans preferentially go towards North, while scan_direction_mean_k2 = 0 means that they preferentially go in the NorthSouth direction, and scan_direction_mean_k4 = 0 that they preferentially go either in the NorthSouth or in the EastWest direction.
scan_direction_mean_k2 : Mean position angle of scan directions across the source (float, Angle[deg])
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_mean_k1 for further details.
scan_direction_mean_k3 : Mean position angle of scan directions across the source (float, Angle[deg])
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_mean_k1 for further details.
scan_direction_mean_k4 : Mean position angle of scan directions across the source (float, Angle[deg])
The scan_direction_strength_k1…4 and scan_direction_mean_k1…4 attributes quantify the distribution of AL scan directions across the source.
See the description for attribute scan_direction_mean_k1 for further details.
During data processing, this source happened to be duplicated and only one source identifier has been kept. Observations assigned to the discarded source identifier(s) were not used. This may indicate observational, crossmatching or processing problems, or stellar multiplicity, and probable astrometric or photometric problems in all cases. The duplicity criterion used for Gaia E/DR3 is an angular distance of
0.18 arcsec, while a limit of 0.4 arcsec was used for Gaia DR2.
Number of observations (CCD transits) that contributed to the G mean flux (phot_g_mean_flux) and mean flux error (phot_g_mean_flux_error).
Mean flux in the Gband.
Standard deviation of the Gband fluxes divided by the square root of the number of observations (phot_g_n_obs).
Mean flux in the Gband phot_g_mean_flux divided by its error phot_g_mean_flux_error.
Mean magnitude in the G band. This is computed from the Gband mean flux (phot_g_mean_flux ) applying the magnitude zeropoint in the Vega scale (see Section 5.4.1).
No error is provided for this quantity as the error distribution is only symmetric in flux space. This converts to an asymmetric error distribution in magnitude space which cannot be represented by a single error value.
Number of observations (CCD transits) that contributed to the integrated BP mean flux (phot_bp_mean_flux) and its mean flux error (phot_bp_mean_flux_error).
Mean flux in the integrated blue photometer (BP) band (see Chapter 5).
Error on the mean flux in the integrated BP band phot_bp_mean_flux (errors are computed from the dispersion about the weighted mean of input calibrated photometry).
Integrated BP mean flux phot_bp_mean_flux divided by its error phot_bp_mean_flux_error.
Mean magnitude in the integrated BP band. This is computed from the BPband mean flux (phot_bp_mean_flux) applying the magnitude zeropoint in the Vega scale.
No error is provided for this quantity as the error distribution is only symmetric in flux space. This converts to an asymmetric error distribution in magnitude space which cannot be represented by a single error value.
Number of observations (CCD transits) that contributed to the integrated RP mean flux (phot_rp_mean_flux) and mean flux error (phot_rp_mean_flux_error).
Mean flux in the integrated red photometer (RP) band (see Chapter 5).
Error on the mean flux in the integrated RP band phot_rp_mean_flux (errors are computed from the dispersion about the weighted mean of input calibrated photometry).
Integrated RP mean flux phot_rp_mean_flux divided by its error phot_rp_mean_flux_error.
Mean magnitude in the integrated RP band. This is computed from the RPband mean flux (phot_rp_mean_flux) applying the magnitude zeropoint in the Vega scale.
No error is provided for this quantity as the error distribution is only symmetric in flux space. This converts to an asymmetric error distribution in magnitude space which cannot be represented by a single error value.
BP/RP excess factor estimated from the comparison of the sum of integrated BP and RP fluxes with respect to the flux in the G band. This measures the excess of flux in the BP and RP integrated photometry with respect to the G band. A deviation from the norm means that there is a consistency issue between the fluxes. This could generally imply a problem with the G, BP or RP measurements. More details on how to best interpret this metric can be found in Riello et al. (2021).
Number of BP transits that contributed to the mean photometry and were considered to be contaminated by one or more nearby sources. The contaminating sources may come from the other field of view.
Number of BP transits that contributed to the mean photometry and were flagged to be blends of more than one source (i.e. more than one source is present in the observing window). The blended sources may come from different fields of view.
Number of RP transits that contributed to the mean photometry and were considered to be contaminated by one or more nearby sources. The contaminating sources may come from the other field of view.
Number of RP transits that contributed to the mean photometry and were flagged to be blends of more than one source (i.e. more than one source is present in the observing window). The blended sources may come from different fields of view.
This flag indicates the photometric calibration process used for the source. The process is determined by the availability of colour information derived from the internally calibrated mean BP and RP source spectra. The following values are defined for Gaia DR3:

•
0: this corresponds to the ‘gold’ photometric dataset. Sources in this dataset have complete colour information.

•
1: this corresponds to the ‘silver’ photometric dataset. Sources in this dataset have incomplete colour information and therefore were calibrated using an iterative process that estimated the missing colour information from the source mean G and either BP or RP photometry (depending on which band had full colour information available) using empirical relationships derived from the gold dataset.

•
2: this corresponds to the ‘bronze’ photometric dataset. Sources in this dataset had insufficient colour information and therefore were calibrated using default colour information derived from the gold dataset.
Because the process of generating the mean BP and RP spectra and the process of producing mean BP and RP integrated photometry are very different and have different requirements it is possible for gold sources to be missing any of the bands, i.e. gold does not imply anything about the availability of mean G, BP and RP photometry. Similarly for silver and bronze sources it is possible to have photometry available in any bands (and possible combinations).
More details about the different calibration procedures are available in Chapter 5 of the Gaia DR3 online documentation and in
Riello et al. (2021)
BP$$RP colour (phot_bp_mean_mag – phot_rp_mean_mag).
BP$$G colour (phot_bp_mean_mag – phot_g_mean_mag).
G$$RP colour (phot_g_mean_mag – phot_rp_mean_mag).
Spectroscopic radial velocity in the Solar system barycentric reference frame.
The radial_velocity is the multiepoch (or multitransit) value obtained by combining the epoch (transit) data of these stars. The total number of epochs used is stored in rv_nb_transits. Both nonblended and deblended spectra are used, and the number of epochs having deblended spectra is stored in rv_nb_deblended_transits.
Two methods are used to obtain radial_velocity, depending on the magnitude grvs_mag of the star. The information on which method has been used is stored in rv_method_used.
For the bright stars (grvs_mag $\le $12), radial_velocity is the median value of the epoch radial velocities. For the faint stars, for which the epoch radial velocities are imprecise, the epoch crosscorrelation functions (obtained by comparing the RVS and the associated template spectrum) are combined and the radial_velocity is derived. The information on which of the two methods has been used is stored in rv_method_used.
See Section 6.1.1 for the complete list of the parameters containing information on the radial_velocity measurements.
In Gaia DR3, radial_velocity is provided for about 33.8 million of stars. See Katz et al. (2022) for a description of the validation of the radial_velocity measurements, and Blomme et al. (2022b) for the specific treatments to obtain the hot star radial velocities and their validation.
The uncertainty associated with radial_velocity.
Two methods are used to obtain radial_velocity and radial_velocity_error, depending on the magnitude grvs_mag of the star. The information on which method has been used is stored in rv_method_used.
For the bright stars (rv_method_used= 1), radial_velocity_error is the uncertainty on the median of the epoch radial velocities (${\sigma}_{\mathrm{med}}$), to which a constant shift of 0.11 km s${}^{1}$ was added to take into account a calibration floor contribution:
$$\mathrm{\U0001d69b\U0001d68a\U0001d68d\U0001d692\U0001d68a\U0001d695}\mathrm{\_}\mathrm{\U0001d69f\U0001d68e\U0001d695\U0001d698\U0001d68c\U0001d692\U0001d69d\U0001d6a2}\mathrm{\_}\mathrm{\U0001d68e\U0001d69b\U0001d69b\U0001d698\U0001d69b}=\sqrt{{\sigma}_{med}^{2}+{0.11}^{2}}$$ 
$${\sigma}_{\mathrm{med}}=\sqrt{\frac{\pi}{2}}.\frac{\sigma ({V}_{j})}{\sqrt{\mathtt{\text{rv\_nb\_transits}}}}$$ 
where $\sigma ({V}_{j})$ is the standard deviation of the epoch radial velocity measurements and rv_nb_transits the number of transits for which an epoch radial velocity, ${V}_{j}$, has been obtained.
For the faint stars (rv_method_used = 2), the radial_velocity_error is derived from the combined crosscorrelation functions:
$$\mathrm{\U0001d69b\U0001d68a\U0001d68d\U0001d692\U0001d68a\U0001d695}\mathrm{\_}\mathrm{\U0001d69f\U0001d68e\U0001d695\U0001d698\U0001d68c\U0001d692\U0001d69d\U0001d6a2}\mathrm{\_}{\mathrm{\U0001d68e\U0001d69b\U0001d69b\U0001d698\U0001d69b}}^{2}=\frac{1{C}^{2}}{MN{C}^{\mathrm{\prime \prime}}C}$$ 
where $C$ and ${C}^{\mathrm{\prime \prime}}$ are the values of the crosscorrelation function and of its second derivative at the maximum. $N$ is the number of bins of the input spectrum. $M$ is the number of transits rv_nb_transits (see Zucker (2003), Sec.2.3).
rv_method_used contains the information on the method used to obtain the radial_velocity and the associated uncertainty radial_velocity_error.
Two methods are used:

•
rv_method_used = 1: This is the method used for the bright stars (in general grvs_mag $\le 12$). The radial_velocity is the median of the epoch radial velocities, and the associated uncertainty radial_velocity_error is the uncertainty on the median, to which a constant of 0.11 km s${}^{1}$ is added.

•
rv_method_used = 2 : This is the method used for the faint stars (grvs_mag $>12$), but also for few bright stars not having grvs_mag information (grvs_mag is not estimated when the available transits are all deblended or reblended). The crosscorrelation functions obtained at each epoch are combined to obtain a combined crosscorrelation function which is used to estimate radial_velocity and radial_velocity_error.
The total number of epochs (transits) used to compute radial_velocity. In general, one transit in the RVS fieldofview includes 3 RVS CCD observations.
The number of epochs (transits) among rv_nb_transits for which at least one of the 3 RVS CCD spectra has undergone deblending. The deblending of the spectra is decribed in Seabroke et al. (2022).
rv_visibility_periods_used : Number of visibility periods used to estimate the radial velocity (short)
Number of visibility periods used to obtain radial_velocity. A visibility period is a group of transits separated from other groups by a gap of at least 4 days.
rv_expected_sig_to_noise : Expected signal to noise ratio in the combination of the spectra used to obtain the radial velocity (float)
The expected signal to noise ratio is obtained by combining the information from the CCD spectra used for estimating radial_velocity:
$$\mathrm{\U0001d69b\U0001d69f}\mathrm{\_}\mathrm{\U0001d68e\U0001d6a1\U0001d699\U0001d68e\U0001d68c\U0001d69d\U0001d68e\U0001d68d}\mathrm{\_}\mathrm{\U0001d69c\U0001d692\U0001d690}\mathrm{\_}\mathrm{\U0001d69d\U0001d698}\mathrm{\_}\mathrm{\U0001d697\U0001d698\U0001d692\U0001d69c\U0001d68e}=\frac{S}{\sqrt{S+BCK+RN}}$$ 
where:
$$S=\frac{medianFlux\times {N}_{ValidStrips}\times \mathrm{EXP}\mathrm{\_}\mathrm{TIME}\times \mathrm{PIXEL}\mathrm{\_}\mathrm{WIDTH}\mathrm{\_}\mathrm{AL}}{\mathrm{BAND}\mathrm{\_}\mathrm{WIDTH}}$$ 
$$BCK=medianBackground\times {N}_{ValidStrips}\times {N}_{ACpixels}$$ 
$$RN=RO{N}^{2}\times {N}_{ValidStrips}\times {N}_{ACsamples}$$ 
where:
$\bullet $ $medianFlux$ = the median of the integrated flux of the CCD spectra used to obtain the radial velocity [e${}^{}$s${}^{1}$]
$\bullet $ ${N}_{ValidStrips}$ = the total number of CCD spectra used to obtain the radial_velocity (in general there are 3 CCD spectra per transit)
$\bullet $ BAND_WIDTH = 870  846 [nm]
$\bullet $ EXP_TIME = 4.4167032 [s]
$\bullet $ PIXEL_WIDTH_AL = 0.02453 [nm]
$\bullet $ $medianBackground$ = the median background in one exposure of the CCD spectra used to obtain the radial_velocity [e${}^{}$pixel${}^{1}$]
$\bullet $ ${N}_{ACpixels}$ = 10 is the number of pixels in the AC direction of the nontruncated RVS window
$\bullet $ ${N}_{ACsamples}$ is the size in the AC direction of the nontruncated RVS window. ${N}_{ACsamples}=10$ for the 2D RVS windows (Window Class=0) and ${N}_{ACsamples}=1$ for the 1D windows (Window Class=1)
$\bullet $ $RON$ (Read Out Noise) = 3.2 [e${}^{}$]
The SNR of the spectra combination used for vbroad determination can be estimated from:
$\mathrm{\U0001d69b\U0001d69f}\mathrm{\_}\mathrm{\U0001d68e\U0001d6a1\U0001d699\U0001d68e\U0001d68c\U0001d69d\U0001d68e\U0001d68d}\mathrm{\_}\mathrm{\U0001d69c\U0001d692\U0001d690}\mathrm{\_}\mathrm{\U0001d69d\U0001d698}\mathrm{\_}\mathrm{\U0001d697\U0001d698\U0001d692\U0001d69c\U0001d68e}\sqrt{{\displaystyle \frac{\mathrm{\U0001d69f\U0001d68b\U0001d69b\U0001d698\U0001d68a\U0001d68d}\mathrm{\_}\mathrm{\U0001d697\U0001d68b}\mathrm{\_}\mathrm{\U0001d69d\U0001d69b\U0001d68a\U0001d697\U0001d69c\U0001d692\U0001d69d\U0001d69c}}{\mathrm{\U0001d69b\U0001d69f}\mathrm{\_}\mathrm{\U0001d697\U0001d68b}\mathrm{\_}\mathrm{\U0001d69d\U0001d69b\U0001d68a\U0001d697\U0001d69c\U0001d692\U0001d69d\U0001d69c}}}}$, and similarly for grvs_mag from:
$\mathrm{\U0001d69b\U0001d69f}\mathrm{\_}\mathrm{\U0001d68e\U0001d6a1\U0001d699\U0001d68e\U0001d68c\U0001d69d\U0001d68e\U0001d68d}\mathrm{\_}\mathrm{\U0001d69c\U0001d692\U0001d690}\mathrm{\_}\mathrm{\U0001d69d\U0001d698}\mathrm{\_}\mathrm{\U0001d697\U0001d698\U0001d692\U0001d69c\U0001d68e}\sqrt{{\displaystyle \frac{\mathrm{\U0001d690\U0001d69b\U0001d69f\U0001d69c}\mathrm{\_}\mathrm{\U0001d696\U0001d68a\U0001d690}\mathrm{\_}\mathrm{\U0001d697\U0001d68b}\mathrm{\_}\mathrm{\U0001d69d\U0001d69b\U0001d68a\U0001d697\U0001d69c\U0001d692\U0001d69d\U0001d69c}}{\mathrm{\U0001d69b\U0001d69f}\mathrm{\_}\mathrm{\U0001d697\U0001d68b}\mathrm{\_}\mathrm{\U0001d69d\U0001d69b\U0001d68a\U0001d697\U0001d69c\U0001d692\U0001d69d\U0001d69c}}}}$
The renormalised goodness of fit (see Perryman 1997, p. 112) is an empirical value computed using this source and all the other sources having rv_template_teff and grvs_mag in a given range. The scatter of the source epoch radial velocities is compared to the typical epoch uncertainty for the appropriate grvs_mag and rv_template_teff range.
$$\mathtt{\text{rv\_renormalised\_gof}}=\sqrt{4.5\nu}\left(RUW{E}^{2/3}+\frac{2}{9\nu}1\right)$$ 
where:
$$\nu =\mathtt{\text{rv\_nb\_transits}}1$$ 
$$RUWE=\frac{UWE}{\mathrm{mode}(UWE)}$$ 
$$UWE=\sqrt{\frac{1}{\nu}\sum _{j}{\left(\frac{{V}_{j}\mathrm{\U0001d69b\U0001d68a\U0001d68d\U0001d692\U0001d68a\U0001d695}\mathrm{\_}\mathrm{\U0001d69f\U0001d68e\U0001d695\U0001d698\U0001d68c\U0001d692\U0001d69d\U0001d6a2}}{{\u03f5}_{j}}\right)}^{2}}$$ 
$\bullet $ radial_velocity is the median of the epoch radial velocities ${V}_{j}$ (rv_method_used=1);
$\bullet $ ${V}_{j}$ are the epoch radial velocities;
$\bullet $ ${\u03f5}_{j}$ is the uncertainty on ${V}_{j}$;
$\bullet $ mode($UWE$) is the mode of the $UWE$ distribution in the appropriate bin of the $UWE$(rv_template_teff,grvs_mag) look up table obtained by an offline analysis (see Section 6.5.2);
$\bullet $ $RUWE$: Renormalised Unit Weight Error, $UWE$: Unit Weight Error.
rv_renormalised_gof is provided for the bright stars with $5.5\le \mathtt{\text{grvs\_mag}}\le 12$ and rv_template_teff $$ 14 500K. It is empty for the stars with grvs_mag outside this range.
To find potential radial velocity variable stars we suggest to take into account also rv_nb_transits and rv_chisq_pvalue and the following selection is suggested:
rvChiSqPValue $$ and rv_renormalised_gof $>4$ and rv_nb_transits $\ge 10$.
rv_chisq_pvalue is the Pvalue for radial velocity constancy. It is defined as the probability that the ${\chi}^{2}$ value of the radial velocity time series will exceed the expected value from the chisquare probability distribution function with significance level $\alpha $ and having $k=N$ $$ 1 degrees of freedom. P takes values between [0,1] assuming known radial velocity uncertainties that are normally distributed. It ranges from 0 (zero) for very low probability of radial velocity constancy to 1 (one) for very strong probability of radial velocity constancy. ${V}_{j}$ is the time series of size $N$, with $N$ $>$ 1 of valid epoch radial velocity values for which the large statistical outliers are excluded (see below). The radial velocity values have uncertainties ${\u03f5}_{j}$ and weights ${w}_{j}\equiv 1/{({\u03f5}_{j})}^{2}$. The weighted chisquared test statistic value ${\chi}^{2}$ is then defined as:
$${\chi}^{2}=\frac{1}{N1}\frac{W{\sum}_{j=1}^{N}{w}_{j}{V}_{j}^{2}{\left({\sum}_{j=1}^{N}{w}_{j}{V}_{j}\right)}^{2}}{W}$$ 
where $W\equiv {\sum}_{j=1}^{N}{w}_{j}$ is the sum of weights. The Pvalue is defined as the cumulative probability of ${\chi}^{2}$ from the chisquare probability distribution function with $k$ degrees of freedom:
$$P\equiv P({\chi}^{2},k)=1\frac{{2}^{k/2}}{\mathrm{\Gamma}(k/2)}{\int}_{0}^{{\chi}^{2}}{t}^{k/21}\mathrm{exp}(t/2)\mathit{d}t$$ 
where $\mathrm{\Gamma}(k/2)$ is the gamma function which has closedform values for integer $k$.
The Pvalue is a probabilitybased statistic with respect to the null hypothesis that the source is constant in radial velocity. It assumes that ${\u03f5}_{j}$ are normally distributed uncertainties (that may not always be known or available).
If one selects for example all sources having $$ from the sample (i.e., $\alpha $ is set equal to 0.05), this will yield $\sim $5% of radial velocity constant sources that can still contaminate the selected subset of radial velocity variable sources. In case one wants a subset of radial velocity variables less contaminated with constant sources, choose a smaller value of $\alpha $, but which will also decrease the size of the selected subset of variables.
The large statistical outliers are defined as the radial velocity values in the time series with ${V}_{j}$ smaller than Q1 $$ 3 $\times $ IQR or larger than Q3 + 3 $\times $ IQR. Q1 and Q3 are the 25th and 75th percentiles, respectively, and the interquartile range IQR = Q3 $$ Q1. Note the radial velocity statistical outliers fall outside of the lower and upper time series fences, and are being disregarded for calculating rv_chisq_pvalue. For the statistical outlier calculations, the fences are placed at Q1 $$ 3 $\times $ IQR and Q3 + 3 $\times $ IQR commonly used for detecting large statistical outliers, or also called the probable outliers. To find potential radial velocity variable stars we suggest using also rv_nb_transits and rv_renormalised_gof. The following selection is suggested:
rv_chisq_pvalue $$ and rv_renormalised_gof $>4$ and rv_nb_transits $\ge 10$.
Note: rv_chisq_pvalue is provided in DR3 for all bright stars of grvs_mag $\le 12$ and rv_method_used = 1. It is empty for fainter stars having rv_method_used = 2.
The difference between the first and last transit mean observing time. The transits are those used to compute radial_velocity, and their number is rv_nb_transits.
rv_amplitude_robust : Total amplitude in the radial velocity time series after outlier removal (float, Velocity[km s${}^{1}$])
The total amplitude (maxRobust$$minRobust) in the radial velocity time series after outlier removal.
The statistical outliers are the valid transits in the timeseries having RVvalues smaller than Q1  3 x IQR or larger than Q3 + 3 x IQR, where Q1 and Q3 are the 25th and 75th percentiles, and where IQR= Q3  Q1. The outlying values fall outside of the lower and upper ‘fences’, and are being disregarded for calculating the socalled ‘Robust’ statistical parameters.
For the outlier calculations the fences are placed at Q1  3 x IQR and Q3 + 3 x IQR which are commonly used for detecting ‘large’ outliers, or also called the ‘probable outliers’.
This field is provided for the bright stars for which rv_method_used = 1 and rv_nb_transits $>2$ and it is empty otherwise.
Effective temperature of the synthetic spectrum template used to determine radial_velocity and vbroad. N.B. the purpose of this parameter is to provide information on the synthetic template spectrum used, not to provide an estimate of the stellar effective temperature of this source. The available synthetic spectra are listed in Section 6.2.3.
rv_template_logg : Logg of the template used to compute the radial velocity (float, GravitySurface[log cgs])
Surface gravity $\mathrm{log}g$ of the synthetic spectrum template used to determine radial_velocity and vbroad. N.B. the purpose of this parameter is to provide information on the synthetic template spectrum used, not to provide an estimate of the surface gravity of this source. The available synthetic spectra are listed in Section 6.2.3.
rv_template_fe_h : [Fe/H] of the template used to compute the radial velocityy (float, Abundances[dex])
Metallicity (compared to solar) [Fe/H] of the synthetic spectrum template used to determine radial_velocity and vbroad. N.B. the purpose of this parameter is to provide information on the synthetic template spectrum used, not to provide an estimate of the metallicity of this source. The available synthetic spectra are listed in Section 6.2.3.
rv_atm_param_origin contains the information on the origin of the template atmospheric parameters (APs) in the following order: origin of rv_template_teff, origin of rv_template_logg and origin of rv_template_fe_h.
The possible origins of each template atmospheric parameter are:
$\bullet $ 0 : default. The template APs are set to their default value when no information is available on the star APs and no attempt to estimate the APs is done in the spectroscopic pipeline. The default APs are:
Teff = 5500K (solar); $\mathrm{log}g=4.5$ dex (solar); [Fe/H] = 0 dex (solar) or $=2$ dex (in the few cases when Teff origin=1)
$\bullet $ 1 : GspPhot. The template APs are the closest to the star APs obtained by a preliminary version of the atmospheric parameter pipeline GspPhot (Section 11.3.3);
$\bullet $ 2 : Ground based. The template parameters are the closest to the star APs taken from ground based observations (Section 6.2.3);
$\bullet $ 3 : DetermineAP. The template parameters are obtained using the spectroscopic pipeline internal method ‘DetermineAP’ (Section 6.4.5);
$\bullet $ 4 : GspSpec. The template parameters are the closest to the star parameters computed by a preliminary version of the atmospheric parameter pipleine GspSpec (Section 11.3.4);
$\bullet $ 5 : ReDetermineApHotStars. The template parameters are the closest to the star APs obtained using the spectroscopic pipeline internal method ReDetermineApHotStars. This method is described in Blomme et al. (2022b) and is used to determine the APs of the hot stars.
The possible values of rv_atm_param_origin are:

•
000 (The three parameters have their default value: Teff = 5500K, $\mathrm{log}g$ = 4.5 and [Fe/H] = 0);

•
111 (The origin of the three parameters is GspPhot)

•
110 (The origin of Teff and $\mathrm{log}g$ is GspPhot, default [Fe/H] = 2)

•
101 (The origin of Teff and [Fe/H] is GspPhot; default $\mathrm{log}g$ = 4.5)

•
100 (The origin of Teff is GspPhot; default $\mathrm{log}g$= 4.5; default [Fe/H]= 2)

•
222 (The origin of the three parameters is ground based)

•
333 (The origin of the three parameters is DetermineAP)

•
444 (The origin of the three parameters is GspSpec)

•
440 (The origin of Teff and $\mathrm{log}g$ is GspSpec; default [Fe/H] = 0)

•
555 (The origin of the three parameters is RedetermineApHotStars)
The spectral line broadening parameter. It is measured using a rotational broadening kernel; its value therefore includes $v\mathrm{sin}i$, but also any other source of line broadening (macroturbulence, residual instrumental effects, etc.)
vbroad is the median value of the epoch vbroad measurements, leaving aside the epoch vbroad values obtained using deblended spectra and those obtained at the beginning of the Gaia operations, when the optics were suffering from contamination from water resulting in broadening of the spectral lines. The total number of epochs used is stored in vbroad_nb_transits.
Due to technical and algorithmic limitations, values lower than $\sim $10 km/s are known to be systematically overestimated, but they still can be used to identify slow rotators.
vbroad is provided for about 3.5 million bright stars. See Frémat et al. (2022) for a description of the validation of the vbroad measurements.
vbroad_error is the uncertainty associated to vbroad. It is the standard deviation of the epoch vbroad${}_{j}$ measurements.
Note: When vbroad_error $>$ vbroad, the star vbroad estimation is: 0$\le $vbroad$\mathrm{\le}$vbroad+vbroad_error.
The number of transits (epochs) used to compute vbroad. Only nonblended transits acquired after the first decontamination (OBMT=1317 rev) have been used.
The magnitude grvs_mag is estimated using the flux in the RVS spectra. It is the median value of the epoch ${G}_{\mathrm{RVS}}^{\mathrm{t}}$ measurements, leaving aside the epoch ${G}_{\mathrm{RVS}}^{\mathrm{t}}$ values obtained using deblended spectra. The total number of epochs used is stored in grvs_mag_nb_transits.
grvs_mag is provided for about 32.2 million of sources. It is not provided for stars fainter than grvs_mag=14.1 mag.
For those stars where no grvs_mag is provided, an estimation of the magnitude in the RVS band can be obtained using the magnitudes phot_g_mean_mag and phot_rp_mean_mag and the transformation in Sartoretti et al. (2022).
The grvs_mag_error is the uncertainty on the median (${\sigma}_{\mathrm{med}}$), to which a constant of 0.004 mag has been added to take into account a calibration floor contribution:
$$\mathrm{\U0001d690\U0001d69b\U0001d69f\U0001d69c}\mathrm{\_}\mathrm{\U0001d696\U0001d68a\U0001d690}\mathrm{\_}\mathrm{\U0001d68e\U0001d69b\U0001d69b\U0001d698\U0001d69b}=\sqrt{{\sigma}_{med}^{2}+{0.004}^{2}}$$ 
$${\sigma}_{\mathrm{med}}=\sqrt{\frac{\pi}{2}}.\frac{\sigma ({G}_{\mathrm{RVS}}^{\mathrm{t}})}{\sqrt{\mathtt{\text{grvs\_mag\_nb\_transits}}}}$$ 
where $\sigma ({G}_{\mathrm{RVS}}^{\mathrm{t}})$ is the standard deviation of the epoch ${G}_{\mathrm{RVS}}^{\mathrm{t}}$ measurements and grvs_mag_nb_transits is the number of epochs for which a ${G}_{\mathrm{RVS}}^{\mathrm{t}}$ has been obtained.
The number of transits (epochs) used to compute grvs_mag. Only nonblended transits have been used.
grvs_mag_nb_transits includes a few nonblended transit data not included in rv_nb_transits, but still relevant for the grvs_mag estimation.
The signal to noise ratio in the mean spectrum is calculated using the median of the ratio of the fluxes and flux uncertainties $\overline{{f}_{\text{bin}}}/{\sigma}_{f,\text{bin}}$ on all the individual bins.
The flux per wavelength bin in the mean spectrum is
$$\overline{{f}_{\text{bin}}}=\frac{{\sum}_{j=0}^{n}{f}_{j}}{n}$$ 
where $j$ is the $j$th CCD spectrum being combined out of a total of $n$ in a particular wavelength bin.
The uncertainty on the flux per wavelength bin is
$${\sigma}_{f,\text{bin}}=\frac{{\sigma}_{{f}_{n}}}{\sqrt{n}}$$ 
where ${\sigma}_{{f}_{n}}$ is the standard deviation of all the flux values contributing to an individual wavelength bin:
$${\sigma}_{{f}_{n}}=\sqrt{\frac{1}{n}\sum _{j=0}^{n}{({f}_{j}\overline{{f}_{\text{bin}}})}^{2}}$$ 
This field is provided only for the stars having the rvs_mean_spectrum published, which can be selected using the flag has_rvs=true.
Flag indicating if variability was identified in the photometric data:

•
‘NOT_AVAILABLE’: source not processed and/or exported to catalogue;

•
‘CONSTANT’: Source not identified as variable;

•
‘VARIABLE’: source identified and processed as variable, see variability tables and Chapter 10.
Note that for this data release only a subset of (variable) sources was processed and/or exported, so for many (known) variable sources this flag is set to ‘NOT AVAILABLE’. No ‘CONSTANT’ sources were exported either.
Galactic Longitude of the object at reference epoch ref_epoch, see Section 4.1.7 of the release documentation for conversion details.
Galactic Latitude of the object at reference epoch ref_epoch, see Section 4.1.7 of the release documentation for conversion details.
Ecliptic Longitude of the object at reference epoch ref_epoch, obtained from the equatorial coordinates using the transformation defined in Volume 1, Section 1.5.3 of ESA (1997).
Note that in the transformation applied here the ICRS origin is shifted in the equatorial plane from $\mathrm{\Gamma}$ by $\varphi =0.05542$ arcsec, positive from $\mathrm{\Gamma}$ to the ICRS origin (Chapront et al. 2002). The ICRS has an unambiguous definition with an origin in the ICRF equator defined by the realisation of the ICRF. The ecliptic system is less welldefined, potentially depending on additional conventions in dynamical theories. The transformation employed here corresponds to the inertial mean ecliptic with obliquity and $\mathrm{\Gamma}$ defined by reference to the ICRS equator. Both the obliquity and the position of $\mathrm{\Gamma}$ on the ICRS equator with respect to the ICRS origin have been obtained from Lunar Laser Ranging measurements. This has no time dependence – there is no secular variation of the obliquity and no precession – and it simply defines the relative situation of the various planes at J2000.
Ecliptic Latitude of the object at reference epoch ref_epoch. For further details see the description for attribute ecl_lon.
in_qso_candidates : Flag indicating the availability of additional information in the QSO candidates table (boolean)
This flag indicates that this source has been identified and/or processed as a QSO candidate by some of the DPAC processing chains. The information derived from this processing is provided in the separate qso_candidates table (see Chapter 12).
in_galaxy_candidates : Flag indicating the availability of additional information in the galaxy candidates table (boolean)
This flag indicates that this source has been identified and/or processed as a galaxy candidate by some of the DPAC processing chains. The information derived from this processing is provided in the separate galaxy_candidates table (see Chapter 12).
non_single_star : Flag indicating the availability of additional information in the various NonSingle Star tables (short)
This flag indicates that this source has been identified as a nonsingle star by some of the DPAC processing chains (see Chapter 7). The additional parameters derived from this processing are provided separately in one of the tables from the NonSingle Star section.
The flag is organised in three bits informing about the nature of the nonsingle star model.

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bit 1 (leastsignificant bit) is set to 1 in case of an astrometric binary

•
bit 2 is set to 1 in case of a spectroscopic binary

•
bit 3 is set to 1 in case of an eclisping binary
Note that some models can be combinations of two of the nonsingle star natures coded in this flag.
has_xp_continuous : Flag indicating the availability of mean BP/RP spectrum in continuous representation for this source (boolean)
This flag indicates that a mean BP/RP spectrum is available for this source in continuous representation.
For more information about this representation, see the table xp_continuous_mean_spectrum and 5.3.4 of the documentation.
has_xp_sampled : Flag indicating the availability of mean BP/RP spectrum in sampled form for this source (boolean)
This flag indicates that a mean BP/RP spectrum is available for this source in sampled form.
For more information about this representation, see the table xp_sampled_mean_spectrum and 5.3.4 of the documentation.
This flag indicates that a mean RVS spectrum is available for this source.
has_epoch_photometry : Flag indicating the availability of epoch photometry for this source (boolean)
This flag indicates that epoch photometry is available for the source. Epoch photometry always contains G band integrated photometry, together with BP and/or RP integrated photometry when available.
This flag indicates that epoch radial velocities are provided for the source.
In DR3, this will concern only a small subset of variable stars that have been studied based on these epoch data, and they will be served in the archive through table vari_epoch_radial_velocity. For releases from DR4 onwards this interface will be changed to the DataLink protocol as many more sources will feature this product.
has_mcmc_gspphot : Flag indicating the availability of GSPPhot MCMC samples for this source (boolean)
This flag indicates that MCMC samples from the GSPPhot processing are available for this source.
This flag indicates that MCMC samples from the MSC processing are available for this source.
in_andromeda_survey : Flag indicating that the source is present in the Gaia Andromeda Photometric Survey (GAPS) (boolean)
This flag indicates that the source is present in the Gaia Andromeda Photometric Survey (or GAPS), and as such that photometric light curves are provided for this source. GAPS contains all the sources contained in a 5.5 deg radius field centred on the Andromeda galaxy (Evans et al. 2022); brief details of GAPS are given also in Section 5.8.1.
classprob_dsc_combmod_quasar : Probability from DSCCombmod of being a quasar (data used: BP/RP spectrum, photometry, astrometry) (float)
Probability that the object is of the named class.
This is the overall probability for this class, computed by combining the class probabilities from DSCSpecmod (which classifies objects using BP/RP spectra) and DSCAllosmod (which classifies objects using several astrometric and photometric features). It is important to realise that the DSC classes are defined by the training data used, and that this may produce a narrower definition of the class than may be expected given the class name. This is a posterior probability that includes the global class prior, given in the documentation.
classprob_dsc_combmod_galaxy : Probability from DSCCombmod of being a galaxy (data used: BP/RP spectrum, photometry, astrometry) (float)
Probability that the object is of the named class.
This is the overall probability for this class, computed by combining the class probabilities from DSCSpecmod (which classifies objects using BP/RP spectra) and DSCAllosmod (which classifies objects using several astrometric and photometric features). It is important to realise that the DSC classes are defined by the training data used, and that this may produce a narrower definition of the class than may be expected given the class name. This is a posterior probability that includes the global class prior, given in the documentation.
classprob_dsc_combmod_star : Probability from DSCCombmod of being a single star (but not a white dwarf) (data used: BP/RP spectrum, photometry, astrometry) (float)
Probability that the object is of the named class.
This is the overall probability for this class, computed by combining the class probabilities from DSCSpecmod (which classifies objects using BP/RP spectra) and DSCAllosmod (which classifies objects using several astrometric and photometric features). It is important to realise that the DSC classes are defined by the training data used, and that this may produce a narrower definition of the class than may be expected given the class name. This is a posterior probability that includes the global class prior, given in the documentation.
teff_gspphot : Effective temperature from GSPPhot Aeneas best library using BP/RP spectra (float, Temperature[K])
Effective temperature (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax (see Section 11.3.3 of the online documentation). This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value.
teff_gspphot_lower : Lower confidence level (16%) of effective temperature from GSPPhot Aeneas best library using BP/RP spectra (float, Temperature[K])
Lower confidence level (16%) of effective temperature (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
teff_gspphot_upper : Upper confidence level (84%) of effective temperature from GSPPhot Aeneas best library using BP/RP spectra (float, Temperature[K])
Upper confidence level (84%) of effective temperature (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
logg_gspphot : Surface gravity from GSPPhot Aeneas best library using BP/RP spectra (float, GravitySurface[log cgs])
Surface gravity (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax (see Section 11.3.3 of the online documentation). This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value.
logg_gspphot_lower : Lower confidence level (16%) of surface gravity from GSPPhot Aeneas best library using BP/RP spectra (float, GravitySurface[log cgs])
Lower confidence level (16%) of surface gravity (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
logg_gspphot_upper : Upper confidence level (84%) of surface gravity from GSPPhot Aeneas best library using BP/RP spectra (float, GravitySurface[log cgs])
Upper confidence level (84%) of surface gravity (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
mh_gspphot : Iron abundance from GSPPhot Aeneas best library using BP/RP spectra (float, Abundances[dex])
Decimal logarithm of the ratio of the number abundance of iron to the number abundance of hydrogen relative to the same ratio of solar abundances inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax, assuming source is a single star (see Section 11.3.3 of the online documentation). This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value.
mh_gspphot_lower : Lower confidence level (16%) of iron abundance from GSPPhot Aeneas best library using BP/RP spectra (float, Abundances[dex])
Decimal logarithm of the ratio of the number abundance of iron to the number abundance of hydrogen relative to the same ratio of solar abundances inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax, assuming source is a single star (see Section 11.3.3 of the online documentation). This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
mh_gspphot_upper : Upper confidence level (84%) of iron abundance from GSPPhot Aeneas best library using BP/RP spectra (float, Abundances[dex])
Decimal logarithm of the ratio of the number abundance of iron to the number abundance of hydrogen relative to the same ratio of solar abundances inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax, assuming source is a single star (see Section 11.3.3 of the online documentation). This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
distance_gspphot : Distance from GSPPhot Aeneas best library using BP/RP spectra (float, Length & Distance[pc])
Distance (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax(see Section 11.3.3 of the online documentation). This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. NB: The actual fit parameter is ${\mathrm{log}}_{10}d$ and a prior is imposed to ensure a value between [0,5], thus the minimum possible distance is 1 pc and the maximum is 100 kpc.
distance_gspphot_lower : Lower confidence level (16%) of distance from GSPPhot Aeneas best library using BP/RP spectra (float, Length & Distance[pc])
Lower confidence level (16%) of distance (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. NB: The actual fit parameter is ${\mathrm{log}}_{10}d$ and a prior is imposed to ensure a value between [0,5], thus the minimum possible distance is 1 pc and the maximum is 100 kpc.
distance_gspphot_upper : Upper confidence level (84%) of distance from GSPPhot Aeneas best library using BP/RP spectra (float, Length & Distance[pc])
Upper confidence level (84%) of distance (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. NB: The actual fit parameter is ${\mathrm{log}}_{10}d$ and a prior is imposed to ensure a value between [0,5], thus the minimum possible distance is 1 pc and the maximum is 100 kpc.
azero_gspphot : Monochromatic extinction ${A}_{0}$ at 541.4 nm from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Monochromatic extinction ${A}_{0}$ at 541.4 nm (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. NB: This is the extinction parameter in the adopted Fitzpatrick extinction law (Fitzpatrick 1999, see Section 11.2.3 of the online documentation).
azero_gspphot_lower : Lower confidence level (16%) of monochromatic extinction ${A}_{0}$ at 541.4 nm from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Lower confidence level (16%) of monochromatic extinction ${A}_{0}$ at 541.4 nm (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. NB: This is the extinction parameter in the adopted Fitzpatrick extinction law (Fitzpatrick 1999, see Section 11.2.3 of the online documentation).
azero_gspphot_upper : Upper confidence level (84%) of monochromatic extinction ${A}_{0}$ at 541.4 nm from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Upper confidence level (84%) of monochromatic extinction ${A}_{0}$ at 541.4 nm (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. NB: This is the extinction parameter in the adopted Fitzpatrick extinction law (Fitzpatrick 1999, see Section 11.2.3 of the online documentation).
ag_gspphot : Extinction in G band from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Broadband extinction in G band (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value.
ag_gspphot_lower : Lower confidence level (16%) of extinction in G band from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Lower confidence level (16%) of broadband extinction in G band (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
ag_gspphot_upper : Upper confidence level (84%) of extinction in G band from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Upper confidence level (84%) of broadband extinction in G band (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval.
ebpminrp_gspphot : Reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the median of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Note that while $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})={A}_{\mathrm{BP}}{A}_{\mathrm{RP}}$, this was computed at the level of MCMC samples. Hence, this relation is not exactly true for the median values.
ebpminrp_gspphot_lower : Lower confidence level (16%) of reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Lower confidence level (16%) of reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 16th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. Note that while $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})={A}_{\mathrm{BP}}{A}_{\mathrm{RP}}$, this was computed at the level of MCMC samples. Hence, this relation is not exactly true for the lower confidence levels.
ebpminrp_gspphot_upper : Upper confidence level (84%) of reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ from GSPPhot Aeneas best library using BP/RP spectra (float, Magnitude[mag])
Upper confidence level (84%) of reddening $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})$ (assuming source is a single star) inferred by GSPPhot Aeneas from BP/RP spectra, apparent G magnitude and parallax. This is the 84th percentile of the MCMC samples. Taken from best library that achieves the highest goodnessoffit value. Lower and upper levels include 68% confidence interval. Note that while $E({G}_{\mathrm{BP}}{G}_{\mathrm{RP}})={A}_{\mathrm{BP}}{A}_{\mathrm{RP}}$, this was computed at the level of MCMC samples. Hence, this relation is not exactly true for the upper confidence levels.
libname_gspphot : Name of library that achieves the highest mean logposterior in MCMC samples and was used to derive GSPPhot parameters in this table (string)
Name of library of synthetic stellar spectra (one of A, MARCS, OB, PHOENIX) for which GSPPhot achieves the highest goodnessoffit score (i.e. the highest mean logposterior in its MCMC samples), referred to as “best library”. This is the library used to derive GSPPhot parameters in this table (gaia_source) and in table astrophysical_parameters. For more information on the synthetic libraries see Section 11.2.3.