This table is available for ADQL queries and through the TAP endpoint.
Resource Description:
For a list of all services and tables belonging to this table's resource, see Information on resource 'Astrophysical parameters from Gaia DR2, 2MASS and AllWise'
This table has an associated publication. If you use data from it, it may be appropriate to reference 2022arXiv220103252F (ADS BibTeX entry for the publication) either in addition to or instead of the service reference.
To cite the table as such, we suggest the following BibTeX entry:
@MISC{vo:gdr2ap_main, year=2021, title={Astrophysical parameters from Gaia DR2, {2MASS} and {AllWise}}, author={Fouesneau, M. and Andrae, R. and Dharmawardena, T. and Rybizki, J. and Bailer-Jones, C. A. L. and Demleitner, M.}, url={http://dc.zah.uni-heidelberg.de/tableinfo/gdr2ap.main}, howpublished={{VO} resource provided by the {GAVO} Data Center} }
The full dataset is available in VAEX-style HDF5, suited in particular for visualisation-intensive all-sky analyses. This dump is about 100 gigabytes in size: http://dc.zah.uni-heidelberg.de/gdr2ap/q/download.
Sorted alphabetically. [Sort by DB column index]
Name | Table Head | Description | Unit | UCD |
---|---|---|---|---|
a0_best | A₀ best | multivariate maximum posterior estimate for the dust exctinction A₀ towards this source. | mag | phys.absorption |
a0_dist | P(A₀) | Distribution (min, p16, p25, p50, p75, p84, max) of the dust exctinction A₀ towards this source. In ADQL, write a0_dist[1] for the minimum, a0_dist[2] for the 16th percentile, and so on. | mag | stat;phys.absorption |
a0_p50 | A₀ med | median of the distribution of dust exctinction A₀ towards this source. | mag | phys.absorption;stat.median |
a_bp_best | A_BP best | multivariate maximum posterior estimate for the attenuation in the Gaia BP band towards this source.. | mag | phys.absorption;em.opt.B |
a_bp_dist | P(A_BP) | Distribution (min, p16, p25, p50, p75, p84, max) of the attenuation in the Gaia BP band towards this source.. In ADQL, write a_bp_dist[1] for the minimum, a_bp_dist[2] for the 16th percentile, and so on. | mag | stat;phys.absorption;em.opt.B |
a_bp_p50 | A_BP med | median of the distribution of attenuation in the Gaia BP band towards this source.. | mag | phys.absorption;em.opt.B;stat.median |
a_g_best | A_G best | multivariate maximum posterior estimate for the attenuation in the Gaia G band towards this source.. | mag | phys.absorption;em.opt |
a_g_dist | P(A_G) | Distribution (min, p16, p25, p50, p75, p84, max) of the attenuation in the Gaia G band towards this source.. In ADQL, write a_g_dist[1] for the minimum, a_g_dist[2] for the 16th percentile, and so on. | mag | stat;phys.absorption;em.opt |
a_g_p50 | A_G med | median of the distribution of attenuation in the Gaia G band towards this source.. | mag | phys.absorption;em.opt;stat.median |
a_rp_best | A_RP;em.opt.R best | multivariate maximum posterior estimate for the attenuation in the Gaia RP band towards this source.. | mag | phys.absorption |
a_rp_dist | P(A_RP;em.opt.R) | Distribution (min, p16, p25, p50, p75, p84, max) of the attenuation in the Gaia RP band towards this source.. In ADQL, write a_rp_dist[1] for the minimum, a_rp_dist[2] for the 16th percentile, and so on. | mag | stat;phys.absorption |
a_rp_p50 | A_RP;em.opt.R med | median of the distribution of attenuation in the Gaia RP band towards this source.. | mag | phys.absorption;stat.median |
bp_best | BP best | multivariate maximum posterior estimate for the Gaia BP magnitude. | mag | phot.mag;em.opt.B |
bp_dist | P(BP) | Distribution (min, p16, p25, p50, p75, p84, max) of the Gaia BP magnitude. In ADQL, write bp_dist[1] for the minimum, bp_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.opt.B |
bp_p50 | BP med | median of the distribution of Gaia BP magnitude. | mag | phot.mag;em.opt.B;stat.median |
dmod_best | DM best | multivariate maximum posterior estimate for the distance modulus. | mag | phot.mag.distMod |
dmod_dist | P(DM) | Distribution (min, p16, p25, p50, p75, p84, max) of the distance modulus. In ADQL, write dmod_dist[1] for the minimum, dmod_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag.distMod |
dmod_p50 | DM med | median of the distribution of distance modulus. | mag | phot.mag.distMod;stat.median |
err_bp | Err. BP orig | Recalibrated error from original Gaia BP magnitude. [Note sc] | mag | stat.error;phot.mag;em.opt.B |
err_g | Err. G orig | Recalibrated error from original Gaia G magnitude. [Note sc] | mag | stat.error;phot.mag;em.opt |
err_h | Err. H orig | Recalibrated error from original 2MASS H magnitude. [Note sc] | mag | stat.error;phot.mag;em.IR.H |
err_j | Err. J orig | Recalibrated error from original 2MASS J magnitude. [Note sc] | mag | stat.error;phot.mag;em.IR.J |
err_ks | Err. K orig | Recalibrated error from original 2MASS Ks magnitude. [Note sc] | mag | stat.error;phot.mag;em.IR.K |
err_parallax | Err. Parallax | Error in recalibrated parallax. [Note epc] | mas | stat.error;pos.parallax |
err_rp | Err. RP orig | Recalibrated error from original Gaia RP magnitude. [Note sc] | mag | stat.error;phot.mag;em.opt.R |
err_w1 | Err. W1 orig | Recalibrated error from original WISE W1 magnitude. [Note sc] | mag | stat.error;phot.mag;em.IR.3-4um |
err_w2 | Err. W2 orig | Recalibrated error from original WISE W2 magnitude. [Note sc] | mag | stat.error;phot.mag;em.IR.4-8um |
g_best | G best | multivariate maximum posterior estimate for the Gaia G magnitude. | mag | phot.mag;em.opt |
g_dist | P(G) | Distribution (min, p16, p25, p50, p75, p84, max) of the Gaia G magnitude. In ADQL, write g_dist[1] for the minimum, g_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.opt |
g_p50 | G med | median of the distribution of Gaia G magnitude. | mag | phot.mag;em.opt;stat.median |
h_best | H best | multivariate maximum posterior estimate for the 2MASS H magnitude. | mag | phot.mag;em.IR.H |
h_dist | P(H) | Distribution (min, p16, p25, p50, p75, p84, max) of the 2MASS H magnitude. In ADQL, write h_dist[1] for the minimum, h_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.IR.H |
h_p50 | H med | median of the distribution of 2MASS H magnitude. | mag | phot.mag;em.IR.H;stat.median |
j_best | J best | multivariate maximum posterior estimate for the 2MASS J magnitude. | mag | phot.mag;em.IR.J |
j_dist | P(J) | Distribution (min, p16, p25, p50, p75, p84, max) of the 2MASS J magnitude. In ADQL, write j_dist[1] for the minimum, j_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.IR.J |
j_p50 | J med | median of the distribution of 2MASS J magnitude. | mag | phot.mag;em.IR.J;stat.median |
ks_best | K best | multivariate maximum posterior estimate for the 2MASS Ks magnitude. | mag | phot.mag;em.IR.K |
ks_dist | P(K) | Distribution (min, p16, p25, p50, p75, p84, max) of the 2MASS Ks magnitude. In ADQL, write ks_dist[1] for the minimum, ks_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.IR.K |
ks_p50 | K med | median of the distribution of 2MASS Ks magnitude. | mag | phot.mag;em.IR.K;stat.median |
lnlike_best | ln(P) best | multivariate maximum posterior estimate for the log likelihood of the solution (paper Eq. 1). | N/A | stat.param |
lnlike_dist | P(ln(P)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log likelihood of the solution (paper Eq. 1). In ADQL, write lnlike_dist[1] for the minimum, lnlike_dist[2] for the 16th percentile, and so on. | N/A | stat;stat.param |
lnlike_p50 | ln(P) med | median of the distribution of log likelihood of the solution (paper Eq. 1). | N/A | stat.param;stat.median |
lnp_best | ln(Pp) best | multivariate maximum posterior estimate for the log posterior of the solution (paper Eq. 2). | N/A | stat.probability |
lnp_dist | P(ln(Pp)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log posterior of the solution (paper Eq. 2). In ADQL, write lnp_dist[1] for the minimum, lnp_dist[2] for the 16th percentile, and so on. | N/A | stat;stat.probability |
lnp_p50 | ln(Pp) med | median of the distribution of log posterior of the solution (paper Eq. 2). | N/A | stat.probability;stat.median |
log10jitter_best | log(jitter) best | multivariate maximum posterior estimate for the log photometric likelihood jitter common to all bands. | log(mag) | stat.param |
log10jitter_dist | P(log(jitter)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log photometric likelihood jitter common to all bands. In ADQL, write log10jitter_dist[1] for the minimum, log10jitter_dist[2] for the 16th percentile, and so on. | log(mag) | stat;stat.param |
log10jitter_p50 | log(jitter) med | median of the distribution of log photometric likelihood jitter common to all bands. | log(mag) | stat.param;stat.median |
loga_best | log(age) best | multivariate maximum posterior estimate for the log10 of the age. | log(yr) | time.age |
loga_dist | P(log(age)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log10 of the age. In ADQL, write loga_dist[1] for the minimum, loga_dist[2] for the 16th percentile, and so on. | log(yr) | stat;time.age |
loga_p50 | log(age) med | median of the distribution of log10 of the age. | log(yr) | time.age;stat.median |
logg_best | log(g) best | multivariate maximum posterior estimate for the log10 of the surface gravity. | log(cm/s**2) | phys.gravity |
logg_dist | P(log(g)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log10 of the surface gravity. In ADQL, write logg_dist[1] for the minimum, logg_dist[2] for the 16th percentile, and so on. | log(cm/s**2) | stat;phys.gravity |
logg_p50 | log(g) med | median of the distribution of log10 of the surface gravity. | log(cm/s**2) | phys.gravity;stat.median |
logl_best | log(L) best | multivariate maximum posterior estimate for the log10 of the luminosity. | log(solLum) | phys.luminosity |
logl_dist | P(log(L)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log10 of the luminosity. In ADQL, write logl_dist[1] for the minimum, logl_dist[2] for the 16th percentile, and so on. | log(solLum) | stat;phys.luminosity |
logl_p50 | log(L) med | median of the distribution of log10 of the luminosity. | log(solLum) | phys.luminosity;stat.median |
logm_best | log(M) best | multivariate maximum posterior estimate for the log10 of the mass. | log(solMass) | phys.mass |
logm_dist | P(log(M)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log10 of the mass. In ADQL, write logm_dist[1] for the minimum, logm_dist[2] for the 16th percentile, and so on. | log(solMass) | stat;phys.mass |
logm_p50 | log(M) med | median of the distribution of log10 of the mass. | log(solMass) | phys.mass;stat.median |
logt_best | log(T_eff) best | multivariate maximum posterior estimate for the log10 of the effective temperature. | log(K) | phys.temperature |
logt_dist | P(log(T_eff)) | Distribution (min, p16, p25, p50, p75, p84, max) of the log10 of the effective temperature. In ADQL, write logt_dist[1] for the minimum, logt_dist[2] for the 16th percentile, and so on. | log(K) | stat;phys.temperature |
logt_p50 | log(T_eff) med | median of the distribution of log10 of the effective temperature. | log(K) | phys.temperature;stat.median |
mag_bp | BP orig | Recalibrated Gaia BP magnitude. [Note gpc] | mag | phot.mag;em.opt.B |
mag_g | G orig | Recalibrated Gaia G magnitude. | mag | phot.mag;em.opt |
mag_h | H orig | Recalibrated 2MASS H magnitude. | mag | phot.mag;em.IR.H |
mag_j | J orig | Recalibrated 2MASS J magnitude. | mag | phot.mag;em.IR.J |
mag_ks | K orig | Recalibrated 2MASS Ks magnitude. | mag | phot.mag;em.IR.K |
mag_rp | RP orig | Recalibrated Gaia RP magnitude. [Note gpc] | mag | phot.mag;em.opt.R |
mag_w1 | W1 orig | Recalibrated WISE W1 magnitude. | mag | phot.mag;em.IR.3-4um |
mag_w2 | W2 orig | Recalibrated WISE W2 magnitude. | mag | phot.mag;em.IR.4-8um |
parallax | Parallax | Recalibrated parallax. | mas | pos.parallax |
r0_best | R₀ best | multivariate maximum posterior estimate for the average dust grain size extinction parameter. | N/A | phys.absorption |
r0_dist | P(R₀) | Distribution (min, p16, p25, p50, p75, p84, max) of the average dust grain size extinction parameter. In ADQL, write r0_dist[1] for the minimum, r0_dist[2] for the 16th percentile, and so on. | N/A | stat;phys.absorption |
r0_p50 | R₀ med | median of the distribution of average dust grain size extinction parameter. | N/A | phys.absorption;stat.median |
rp_best | RP best | multivariate maximum posterior estimate for the Gaia RP magnitude. | mag | phot.mag;em.opt.R |
rp_dist | P(RP) | Distribution (min, p16, p25, p50, p75, p84, max) of the Gaia RP magnitude. In ADQL, write rp_dist[1] for the minimum, rp_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.opt.R |
rp_p50 | RP med | median of the distribution of Gaia RP magnitude. | mag | phot.mag;em.opt.R;stat.median |
source_id | Source Id | Unique source identifier. Note that this *cannot* be matched against the DR1 source_id. [Note id] | N/A | meta.id;meta.main |
w1_best | W1 best | multivariate maximum posterior estimate for the WISE W1 magnitude. | mag | phot.mag;em.IR.3-4um |
w1_dist | P(W1) | Distribution (min, p16, p25, p50, p75, p84, max) of the WISE W1 magnitude. In ADQL, write w1_dist[1] for the minimum, w1_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.IR.3-4um |
w1_p50 | W1 med | median of the distribution of WISE W1 magnitude. | mag | phot.mag;em.IR.3-4um;stat.median |
w2_best | W2 best | multivariate maximum posterior estimate for the WISE W2 magnitude. | mag | phot.mag;em.IR.4-8um |
w2_dist | P(W2) | Distribution (min, p16, p25, p50, p75, p84, max) of the WISE W2 magnitude. In ADQL, write w2_dist[1] for the minimum, w2_dist[2] for the 16th percentile, and so on. | mag | stat;phot.mag;em.IR.4-8um |
w2_p50 | W2 med | median of the distribution of WISE W2 magnitude. | mag | phot.mag;em.IR.4-8um;stat.median |
Columns that are parts of indices are marked like this.
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