arXiv subjects

J. Rybizki

Publications and source records attributed to J. Rybizki.

15 recordsLinked to original sources

arXiv2022

Gaia DR3: Apsis III -- Non-stellar content and source classification

Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible 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 objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data 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 subset 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 Object 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 the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5 deg. 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 squared degree, where the extinction is evaluated by TGE.

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arXiv2022

Gaia Data Release 3: Analysis of the Gaia BP/RP spectra using the General Stellar Parameterizer from Photometry

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-variable stars based on their astrometry, photometry, and low-resolution BP/RP spectra. These parameters are effective temperature, surface gravity, metallicity, absolute $M_G$ magnitude, radius, distance, and extinction for each star. GSP-Phot uses a Bayesian forward-modelling approach to simultaneously fit the BP/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 observational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat Gaia observations of the same source. The data release includes GSP-Phot results for 471 million sources with $G<19$. Typical differences to literature values are 110 K for $T_{\rm eff}$ 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 ($\varpi/σ_varpi>20$), 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 these biases. Extinctions $A_0$ and $A_{\rm BP}$ show typical differences from reference values of 0.07-0.09 mag. MCMC samples of the parameters are also available for 95% of the sources. GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes, such as sample selections (OB stars, red giants, solar analogues etc.).

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arXiv2022

Gaia Data Release 3: Astrophysical parameters inference system (Apsis) I -- methods and content overview

Gaia Data Release 3 contains a wealth of new data products for the community. Astrophysical parameters are a major component of this release. They were produced by the Astrophysical parameters inference system (Apsis) within the Gaia Data Processing and Analysis Consortium. The aim of this paper is to describe the overall content of the astrophysical parameters in Gaia Data Release 3 and how they were produced. In Apsis we use the mean BP/RP and mean RVS spectra along with astrometry and photometry, and we derive the following parameters: source classification and probabilities for 1.6 billion objects, interstellar medium characterisation and distances for up to 470 million sources, including a 2D total Galactic extinction map, 6 million redshifts of quasar candidates and 1.4 million redshifts of galaxy candidates, along with an analysis of 50 million outlier sources through an unsupervised classification. The astrophysical parameters also include many stellar spectroscopic and evolutionary parameters for up to 470 million sources. These comprise Teff, logg, and m_h (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (up to 5 million), diffuse interstellar band analysis (0.5 million), activity indices (2 million), H-alpha equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). This catalogue is the most extensive homogeneous database of astrophysical parameters to date, and it is based uniquely on Gaia data.

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arXiv2022

Gaia Data Release 3: Apsis II -- Stellar Parameters

The third Gaia data release contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way. To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly-derived, all-sky catalog of stellar astrophysical parameters (APs): Teff, logg, [M/H], [$α$/Fe], activity index, emission lines, rotation, 13 chemical abundance estimates, radius, age, mass, bolometric luminosity, distance, and dust extinction. We developed the Apsis pipeline to infer APs of Gaia objects by analyzing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against other literature works, including benchmark stars, interferometry, and asteroseismology. Here we assessed the stellar analysis performance from Apsis statistically. We describe the quantities we obtained, including our results' underlying assumptions and limitations. We provide guidance and identify regimes in which our parameters should and should not be used. Despite some limitations, this is the most extensive catalog of uniformly-inferred stellar parameters to date. These comprise Teff, logg, and [M/H] (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (1/2 million), activity indices (2 million), H{$α$} equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS are planned for the next Gaia data release.

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arXiv2022

Gaia Data Release 3. Stellar chromospheric activity and mass accretion from Ca II IRT observed by the Radial Velocity Spectrometer

The Gaia Radial Velocity Spectrometer provides the unique opportunity of a spectroscopic analysis of millions of stars at medium-resolution in the near-infrared. This wavelength range includes the Ca II infrared triplet (IRT), which is a good diagnostics of magnetic activity in the chromosphere of late-type stars. Here we present the method devised for inferring the Gaia stellar activity index together with its scientific validation. 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. Three regimes of the chromospheric stellar activity are identified, confirming suggestions made by previous authors on much smaller $R'_{\rm HK}$ datasets. The highest stellar activity regime is associated with PMS stars and RS CVn systems, in which activity is enhanced by tidal interaction. Some evidence of a bimodal distribution in MS stars with $T_{\rm eff}\ge$ 5000 K is also found, which defines the two other regimes, without a clear gap in between. Stars with 3500 K$\le T_{\rm eff} \le$ 5000 K are found to be either very active PMS stars or active MS stars with a unimodal distribution in chromospheric activity. A dramatic change in the activity distribution is found for $T_{\rm eff}\le$3500 K, with a dominance of low activity stars close to the transition between partially- and fully-convective stars and a rise in activity down into the fully-convective regime.

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arXiv2022

Gaia Data Release 3: Analysis of RVS spectra using the General Stellar Parametriser from spectroscopy

The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. Gaia DR3 contains the parametrisation of RVS data performed by the General Stellar Parametriser-spectroscopy, module. Here we describe the parametrisation of the first 34 months of RVS observations. GSP-spec estimates the chemo-physical parameters from combined RVS spectra of single stars. 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, FeI, FeII, Ni, Zr, Ce and Nd; the differential equivalent width of a cyanogen line; and the parameters of a DIB feature. Another workflow, based on an artificial neural network, provides a second set of atmospheric parameters that are useful for classification control. We implement a detailed quality flag chain considering different error sources. 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 space data. Internal and external biases have been studied taking into account the implemented flags. In some cases, simple calibrations with low degree polynomials are suggested. The homogeneity and quality of the estimated parameters enables chemo-dynamical studies of Galactic stellar populations, interstellar extinction studies from individual spectra, and clear constraints on stellar evolution models. We highly recommend that users adopt the provided quality flags for scientific exploitation . The Gaia DR3 GSP-spec catalogue is a major step in the scientific exploration of Milky Way stellar populations, confirming the Gaia promise of a new Galactic vision (abridged).

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arXiv2022

Astrophysical Parameters from Gaia DR2, 2MASS & AllWISE

Stellar physical and dynamical properties are essential knowledge to understanding the structure, formation, and evolution of our Galaxy. We produced an all-sky uniformly derived catalog of stellar astrophysical parameters (APs; age, mass, temperature, bolometric luminosity, distance, dust extinction) to give insight into the physical properties of Milky-Way stars. Exploiting the power of multi-wavelength and multi-survey observations from Gaia DR2 parallaxes and integrated photometry along with 2MASS and AllWISE photometry, we introduce an all-sky uniformly derived catalog of stellar astrophysical parameters, including dust extinction (A0) and average grain size (R0) along the line of sight, for 123,097,070 stars. In contrast with previous works, we do not use a Galactic model as prior in our analysis. We validate our results against other literature (e.g., benchmark stars, interferometry, Bayestar, StarHorse). The limited optical information in the Gaia photometric bands or the lack of ultraviolet or spectroscopic information renders the chemistry inference prior dominated. We demonstrate that Gaia parallaxes bring sufficient leverage to explore the detailed structures of the interstellar medium in our Milky Way. In Gaia DR3, we will obtain the dispersed optical light information to break through some limitations of this analysis, allowing us to infer stellar chemistry in particular. Gaia promises us data to construct the most detailed view of the chemo-dynamics of field star populations in our Galaxy. Our catalog is available from GAVO at http://dc.g-vo.org/tableinfo/gdr2ap.main (soon Gaia Archive and VizieR)

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arXiv2021

Estimating distances from parallaxes. V: Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3

Stellar distances constitute a foundational pillar of astrophysics. The publication of 1.47 billion stellar parallaxes from Gaia is a major contribution to this. Yet despite Gaia's precision, the majority of these stars are so distant or faint that their fractional parallax uncertainties are large, thereby precluding a simple inversion of parallax to provide a distance. Here we take a probabilistic approach to estimating stellar distances that uses a prior constructed from a three-dimensional model of our Galaxy. This model includes interstellar extinction and Gaia's variable magnitude limit. We infer two types of distance. The first, geometric, uses the parallax together with a direction-dependent prior on distance. The second, photogeometric, additionally uses the colour and apparent magnitude of a star, by exploiting the fact that stars of a given colour have a restricted range of probable absolute magnitudes (plus extinction). Tests on simulated data and external validations show that the photogeometric estimates generally have higher accuracy and precision for stars with poor parallaxes. We provide a catalogue of 1.47 billion geometric and 1.35 billion photogeometric distances together with asymmetric uncertainty measures. Our estimates are quantiles of a posterior probability distribution, so they transform invariably and can therefore also be used directly in the distance modulus (5log10(r)-5). The catalogue may be downloaded or queried using ADQL at various sites (see http://www.mpia.de/homes/calj/gedr3_distances.html) where it can also be cross-matched with the Gaia catalogue.

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arXiv2020

Gaia Early Data Release 3: The Gaia Catalogue of Nearby Stars

We produce a clean and well-characterised catalogue of objects within 100\,pc of the Sun from the \G\ Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. The selection of objects within 100\,pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100\,pc is included in the catalogue. We have produced a catalogue of \NFINAL\ objects that we estimate contains at least 92\% of stars of stellar type M9 within 100\,pc of the Sun. We estimate that 9\% of the stars in this catalogue probably lie outside 100\,pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of \G\ Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10\,pc of the Sun.

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arXiv2019

4MOST Consortium Survey 2: The Milky Way Halo High-Resolution Survey

We will study the formation history of the Milky Way, and the earliest phases of its chemical enrichment, with a sample of more than 1.5 million stars at high galactic latitude. Elemental abundances of up to 20 elements with a precision of better than 0.2 dex will be derived for these stars. The sample will include members of kinematically coherent substructures, which we will associate with their possible birthplaces by means of their abundance signatures and kinematics, allowing us to test models of galaxy formation. Our target catalogue is also expected to contain 30,000 stars at a metallicity of less than one hundredth that of the Sun. This sample will therefore be almost a factor of 100 larger than currently existing samples of metal-poor stars for which precise elemental abundances are available (determined from high-resolution spectroscopy), enabling us to study the early chemical evolution of the Milky Way in unprecedented detail.

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arXiv2019

4MOST Consortium Survey 3: Milky Way Disc and Bulge Low-Resolution Survey (4MIDABLE-LR)

The mechanisms of the formation and evolution of the Milky Way are encoded in the orbits, chemistry and ages of its stars. With the 4MOST MIlky way Disk And BuLgE Low-Resolution Survey (4MIDABLE-LR) we aim to study kinematic and chemical substructures in the Milky Way disc and bulge region with samples of unprecedented size out to larger distances and greater precision than conceivable with Gaia alone or any other ongoing or planned survey. Gaia gives us the unique opportunity for target selection based almost entirely on parallax and magnitude range, hence increasing the efficiency in sampling larger Milky Way volumes with well-defined and effective selection functions. Our main goal is to provide a detailed chrono-chemo-kinematical extended map of our Galaxy and the largest Gaia follow-up down to $G = 19$ magnitudes (Vega). The complex nature of the disc components (for example, large target densities and highly structured extinction distribution in the Milky Way bulge and disc area), prompted us to develop a survey strategy with five main sub-surveys that are tailored to answer the still open questions about the assembly and evolution of our Galaxy, while taking full advantage of the Gaia data.

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arXiv2019

4MOST Consortium Survey 4: Milky Way Disc and Bulge High-Resolution Survey (4MIDABLE-HR)

The signatures of the formation and evolution of a galaxy are imprinted in its stars. Their velocities, ages, and chemical compositions present major constraints on models of galaxy formation, and on various processes such as the gas inflows and outflows, the accretion of cold gas, radial migration, and the variability of star formation activity. Understanding the evolution of the Milky Way requires large observational datasets of stars via which these quantities can be determined accurately. This is the science driver of the 4MOST MIlky way Disc And BuLgE High-Resolution (4MIDABLE-HR) survey: to obtain high-resolution spectra at $R \sim 20\,000$ and to provide detailed elemental abundances for large samples of stars in the Galactic disc and bulge. High data quality will allow us to provide accurate spectroscopic diagnostics of two million stellar spectra: precise radial velocities; rotation; abundances of many elements, including those that are currently only accessible in the optical, such as Li, s-, and r-process; and multi-epoch spectra for a sub-sample of stars. Synergies with complementary missions like Gaia and TESS will provide masses, stellar ages and multiplicity, forming a multi-dimensional dataset that will allow us to explore and constrain the origin and structure of the Milky Way.

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arXiv2018

Estimating distances from parallaxes IV: Distances to 1.33 billion stars in Gaia Data Release 2

For the vast majority of stars in the second Gaia data release, reliable distances cannot be obtained by inverting the parallax. A correct inference procedure must instead be used to account for the nonlinearity of the transformation and the asymmetry of the resulting probability distribution. Here we infer distances to essentially all 1.33 billion stars with parallaxes published in the second \gaia\ data release. This is done using a weak distance prior that varies smoothly as a function of Galactic longitude and latitude according to a Galaxy model. The irreducible uncertainty in the distance estimate is characterized by the lower and upper bounds of an asymmetric confidence interval. Although more precise distances can be estimated for a subset of the stars using additional data (such as photometry), our goal is to provide purely geometric distance estimates, independent of assumptions about the physical properties of, or interstellar extinction towards, individual stars. We analyse the characteristics of the catalogue and validate it using clusters. The catalogue can be queried on the Gaia archive using ADQL at http://gea.esac.esa.int/archive/ and downloaded from http://www.mpia.de/~calj/gdr2_distances.html .

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arXiv2018

New stellar encounters discovered in the second Gaia data release

Passing stars may play an important role in the evolution of our solar system. We search for close stellar encounters to the Sun among all 7.2 million stars in Gaia-DR2 that have six-dimensional phase space data. We characterize encounters by integrating their orbits through a Galactic potential and propagating the correlated uncertainties via a Monte Carlo resampling. After filtering to remove spurious data, we find 694 stars that have median (over uncertainties) closest encounter distances within 5 pc, all occurring within 15 Myr from now. 26 of these have at least a 50% chance of coming closer than 1 pc (and 7 within 0.5 pc), all but one of which are newly discovered here. We further confirm some and refute several other previously-identified encounters, confirming suspicions about their data. The closest encounter in the sample is Gl 710, which has a 95% probability of coming closer than 0.08 pc (17 000 AU). Taking mass estimates from Gaia astrometry and multiband photometry for essentially all encounters, we find that Gl 710 also has the largest impulse on the Oort cloud. Using a Galaxy model, we compute the completeness of the Gaia-DR2 encountering sample as a function of perihelion time and distance. Only 15% of encounters within 5 pc occurring within +/- 5 Myr of now have been identified, mostly due to the lack of radial velocities for faint and/or cool stars. Accounting for the incompleteness, we infer the present rate of encounters within 1 pc to be 19.7 +/- 2.2 per Myr, a quantity expected to scale quadratically with the encounter distance out to at least several pc. Spuriously large parallaxes in our sample from imperfect filtering would tend to inflate both the number of encounters found and this inferred rate. The magnitude of this effect is hard to quantify.

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arXiv2015

The local stellar luminosity function and mass-to-light ratio in the NIR

A new sample of stars, representative of the solar neighbourhood luminosity function, is constructed from the Hipparcos catalogue and the Fifth Catalogue of Nearby Stars. We have cross-matched to sources in the 2MASS catalogue so that for all stars individually determined Near Infrared photometry (NIR) is available on a homogeneous system (typically K_s). The spatial completeness of the sample has been carefully determined by statistical methods, and the NIR luminosity function of the stars has been derived by direct star counts. We find a local volume luminosity of 0.121 +/- 0.004 L_K_sun/(pc**3), corresponding to a volumetric mass-to-light ratio of M/L_K = 0.31 +/- 0.02 M_sun/L_K_sun, where giants contribute 80 per cent to the light but less than 2 per cent to the stellar mass. We derive the surface brightness of the solar cylinder with the help of a vertical disc model. We find a surface brightness of 99 L_K_sun/(pc**2) with an uncertainty of approximately 10 %. This corresponds to a mass-to-light ratio for the solar cylinder of M/L_K = 0.34 M_sun/L_K_sun. The mass-to-light ratio for the solar cylinder is only 10% larger than the local value despite the fact that the local population has a much larger contribution of young stars. It turns out that the effective scale heights of the lower main sequence carrying most of the mass is similar to that of the giants, which are dominating the NIR light. The corresponding colour for the solar cylinder is V-K=2.89 mag compared to the local value of V-K = 2.46 mag. An extrapolation of the local surface brightness to the whole Milky Way yields a total luminosity of M_K = -24.2 mag. The Milky Way falls in the range of K band Tully-Fisher (TF) relations from the literature.

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