Context. As part of the third Gaia data Release, we present the contributions of the non-stellar and classification modules from theeighth coordination unit (CU8) of thedata Processing and Analysis Consortium, which...
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Context. As part of the third Gaia data Release, we present the contributions of the non-stellar and classification modules from theeighth coordination unit (CU8) of thedata Processing and Analysis Consortium, which is responsib.e for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their ob.ectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use thesedata products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A sub.et of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Ob.ect Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic extinction (TGe) module uses theextinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b|& 5. *** DR3 includes 1591 million sources with DSC classifications;56 million sources to which the OA clustering is applied;1.4 million sources with redshift estimates from UGC;6.4 million sources with QSOC redshift;and 3.1 million level 9 HeALPixes of size 0.013 deg2where theextinction is evaluated by TGe. Conclusions. Validation shows that results are in good agreement with values from external catalogues;for example 90% of the QSOC redshifts have absoluteerror lower than 0.1 for sources with empty warning flags, while
Context. The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. A worldwide ob.ervational effort from the ground has...
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Context. The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. A worldwide ob.ervational effort from the ground has provided, in one century, an extremely heterogeneous collection of chemical abundances for about two million stars in total, with fragmentary sky coverage. Aims. This situation is revolutionised by the Gaia third data release (DR3), which contains the parametrisation of Radial Velocity Spectrometer (RVS) data performed by the General Stellar Parametriser-spectroscopy, GSP-Spec, module. Here we describe the parametrisation of the first 34 months of Gaia RVS ob.ervations. Methods. GSP-Spec estimates the chemo-physical parameters from combined RVS spectra of single stars, without additional inputs from astrometric, photometric, or spectro-photometric bP/RP data. The main analysis workflow described here, MatisseGauguin, is based on projection and optimisation methods and provides the stellar atmospheric parameters;the individual chemical abundances of N, Mg, Si, S, Ca, Ti, Cr, Fe i, Fe ii, Ni, Zr, Ce and Nd;the differential equivalent width of a cyanogen line;and the parameters of a diffuse interstellar band (DIb) feature. Another workflow, based on an artificial neural network (ANN) and referred to with the same acronym, provides a second set of atmospheric parameters that are useful for classification control. For both workflows, we implement a detailed quality flag chain considering different error sources. Results. With about 5.6 million stars, the Gaia DR3 GSP-Spec all-sky catalogue is the largest compilation of stellar chemo-physical parameters ever published and the first one from spacedata. Internal and external biases haveb.en studied taking into account the implemented flags. In some cases, simple calibrations with low degree polynomials are suggested. The homogeneity and quality of theestimated parameters enab.es chemo-dynamical studies of G
Context. The astrophysical characterisation of sources is among the major new data products in the third Gaia data release (DR3). In particular, there are stellar parameters for 471 million sources estimated from low-...
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Context. The astrophysical characterisation of sources is among the major new data products in the third Gaia data release (DR3). In particular, there are stellar parameters for 471 million sources estimated from low-resolution bP/RP spectra. Aims. We present the General Stellar Parameterizer from Photometry (GSP-Phot), which is part of the astrophysical parameters inference system (Apsis). GSP-Phot is designed to produce a homogeneous catalogue of parameters for hundreds of millions of single non-variab.e stars based on their astrometry, photometry, and low-resolution bP/RP spectra. These parameters areeffective temperature, surface gravity, metallicity, absolute MG magnitude, radius, distance, and extinction for each star. Methods. GSP-Phot uses a bayesian forward-modelling approach to simultaneously fit thebP/RP spectrum, parallax, and apparent G magnitude. A major design feature of GSP-Phot is the use of the apparent flux levels of bP/RP spectra to derive, in combination with isochrone models, tight ob.ervational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat Gaia ob.ervations of the same source. Results. Thedata release includes GSP-Phot results for 471 million sources with G eff and 0.2-0.25 for log g, but these depend strongly on data quality. In particular, GSP-Phot results are significantly better for stars with good parallax measurements ($/σ$ > 20), mostly within 2kpc. Metallicity estimates exhibit substantial biases compared to literature values and are only useful at a qualitative level. However, we provide an empirical calibration of our metallicity estimates that largely removes thesebiases. extinctions A0 and AbP show typical differences from reference values of 0.07-0.09 mag. MCMC samples of the parameters are also availab.e for 95% of the sources. Conclusions. GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes
We present the Dark energy Spectroscopic Instrument (DeSI) Strong Lens Foundry. We discovered ∼ 3500 new strong gravitational lens candidates in the DeSI Legacy Imaging Surveys using residual neural networks (ResNet)...
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Context. The Gaia Radial Velocity Spectrometer (RVS) provides the unique opportunity of a spectroscopic analysis of millions of stars at medium-resolution (λ/∆λ ∼11500) in the near-infrared (845 - 872 nm). This wav...
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Context. The Gaia Radial Velocity Spectrometer (RVS) provides the unique opportunity of a spectroscopic analysis of millions of stars at medium-resolution (λ/∆λ ∼11500) in the near-infrared (845 - 872 nm). This wavelength range includes the Ca ii infrared triplet (IRT) at 850.03, 854.44, and 866.45 nm, which is a good diagnostics of magnetic activity in the chromosphere of late-type stars. Aims. Here we present the method devised for inferring the Gaia stellar activity index from the analysis of the Ca ii IRT in the RVS spectrum, together with its scientific validation. Methods. The Gaia stellar activity index is derived from the Ca ii IRT excess equivalent width with respect to a reference spectrum, taking the projected rotational velocity (v sin i) into account. Scientific validation of the Gaia stellar activity index is performed by deriving a R'IRT index, largely independent of the photospheric parameters, and considering the correlation with the R'HK index for a sample of stars. A sample of well studied PMS stars is considered to identify the regime in which the Gaia stellar activity index may be affected by mass accretion. The position of these stars in the colour-magnitude diagram and the correlation with the amplitude of the photometric rotational modulation is also scrutinised. Results. Gaia DR3 contains a stellar activity index derived from the Ca ii IRT for some 2 × 106 stars in the Galaxy. This represents a gold mine for studies on stellar magnetic activity and mass accretion in the solar vicinity. Three regimes of the chromospheric stellar activity are identified, confirming suggestions madeby previous authors on much smaller R'HK datasets. The highest stellar activity regime is associated with PMS stars and RS CVn systems, in which activity is enhanced by tidal interaction. Someevidence of a bimodal distribution in MS stars with Teff 5000 K is also found, which defines the two other regimes, without a clear gap in between. Stars with 3500 K>Teff > 50
Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from theeighth coordination unit (CU8) of thedata Processing and Analysis Consortium, which...
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Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from theeighth coordination unit (CU8) of thedata Processing and Analysis Consortium, which is responsib.e for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their ob.ectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use thesedata products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A sub.et of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Ob.ect Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic extinction (TGe) module uses theextinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5◦. Results. Gaia DR3 includes 1591 million sources with DSC classifications;56 million sources to which the OA clustering is applied;1.4 million sources with redshift estimates from UGC;6.4 million sources with QSOC redshift;and 3.1 million level 9 HeALPixes of size 0.013 deg2 where theextinction is evaluated by TGe. Conclusions. Validation shows that results are in good agreement with values from external catalogues;for example 90% of the QSOC redshifts have absoluteerror lower than 0.1 for sources with empty warning flags, wh
Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles haveb.en published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number o...
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Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles haveb.en published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number of voxels in thebrain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].
We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gra...
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We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark energy Survey (DeS) and the Hubb.e Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol eCS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg2. We use DeS Year 3 weak-lensing data for 688 clusters with redshifts z<0.95 and HST weak-lensing data for 39 clusters with 0.6e weak-lensing measurements enab.e robust mass measurements of sample clusters and allow us to empirically constrain the SZ ob.ervab.e-mass relation without having to make strong assumptions about, e.g., the hydrodynamical state of the clusters. For a flat ΛCDM cosmology, and marginalizing over the sum of massive neutrinos, we measure Ωm=0.286±0.032, σ8=0.817±0.026, and the parameter combination σ8(Ωm/0.3)0.25=0.805±0.016. Our measurement of S8≡σ8Ωm/0.3=0.795±0.029 and the constraint from Planck CMb anisotropies (2018 TT, Te, ee+lowe) differ by 1.1σ. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses ∑mν<0.18 eV. When additionally allowing the dark energy equation of state parameter w to vary, we obtain w=−1.45±0.31 from our cluster-based analysis. In combination with Planck data, we measure w=−1.34−0.15+0.22, or a 2.2σ difference with a cosmological constant. We use the cluster abundance to measure σ8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the ΛCDM model fit to Planck primary CMbdata.
Gaia data Release 3 provides novel flux-calibrated low-resolution spectrophotometry for '220 million sources in the wavelength range 330 nm ≤ λ ≤ 1050 nm (XP spectra). Synthetic photometry directly tied to a fl...
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