ABSTRACT In the Milky Way, the thick disk can be defined using individual stellar abundances, kinematics, or age, or geometrically, as stars high above the midplane. In nearby galaxies, where only a ...geometric definition can be used, thick disks appear to have large radial scale lengths, and their red colors suggest that they are uniformly old. The Milky Way's geometrically thick disk is also radially extended, but it is far from chemically uniform: -enhanced stars are confined within the inner Galaxy. In simulated galaxies, where old stars are centrally concentrated, geometrically thick disks are radially extended, too. Younger stellar populations flare in the simulated disks' outer regions, bringing those stars high above the midplane. The resulting geometrically thick disks therefore show a radial age gradient, from old in their central regions to younger in their outskirts. Based on our age estimates for a large sample of giant stars in the APOGEE survey, we can now test this scenario for the Milky Way. We find that the geometrically defined thick disk in the Milky Way has indeed a strong radial age gradient: the median age for red clump stars goes from ∼9 Gyr in the inner disk to 5 Gyr in the outer disk. We propose that at least some nearby galaxies could also have thick disks that are not uniformly old, and that geometrically thick disks might be complex structures resulting from different formation mechanisms in their inner and outer parts.
The Poor Old Heart of the Milky Way Rix, Hans-Walter; Chandra, Vedant; Andrae, René ...
Astrophysical journal/The Astrophysical journal,
12/2022, Letnik:
941, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Abstract
Our Milky Way should host an ancient, metal-poor, and centrally concentrated stellar population, which reflects the star formation and enrichment in the few most massive progenitors that ...coalesced at high redshift to form the proto-Galaxy. While metal-poor stars are known to reside in the inner few kiloparsecs of our Galaxy, current data do not yet provide a comprehensive picture of such a metal-poor “heart” of the Milky Way. We use information from Gaia Data Release 3, especially the XP spectra, to construct a sample of 2 million bright (
G
BP
< 15.5 mag) giant stars within 30° of the Galactic center (GC) with robust M/H estimates,
δ
M/H ≲ 0.1. For ∼1.25 million stars we calculate orbits from Gaia Radial Velocity Spectrometer velocities and astrometry. This sample reveals an extensive, ancient, and metal-poor population that includes ∼18,000 stars with −2.7 < M/H < −1.5, representing a stellar mass of ≳5 × 10
7
M
⊙
. The spatial distribution of these M/H < −1.5 stars has a Gaussian extent of only
σ
R
GC
∼
2.7
kpc
around the GC, with most orbits confined to the inner Galaxy. At high orbital eccentricities, there is clear evidence for
accreted
halo stars in their pericentral orbit phase. Most stars show
α
/Fe enhancement and Al/Fe–Mn/Fe abundances expected for an origin in the more massive portions of the proto-Galaxy. Stars with M/H < −2 show no net rotation, whereas those with M/H ∼ −1 are rotation dominated. These central, metal-poor stars most likely predate the oldest disk population (
τ
age
≈ 12.5 Gyr), which implies that they formed at
z
≳ 5, forging the proto-Milky Way.
Context.
Gaia
Data Release 3 will contain more than a billion sources with positions, parallaxes, and proper motions. In addition, for hundreds of millions of stars, it will include low-resolution ...blue photometer (BP) and red photometer (RP) spectra. Obtained by dispersing light with prisms, these spectra have resolutions that are too low to allow us to measure individual spectral lines and bands. However, the combined BP/RP spectra can be used to estimate some stellar properties such as
T
eff
, log
g
, and M/H.
Aims.
We investigate the feasibility of using the ExtraTrees algorithm to estimate the alpha element to iron abundance ratio
α
/Fe from low-resolution BP/RP spectra.
Methods.
To infer
α
/Fe from the spectra, we created regression models using the ExtraTrees algorithm trained on two samples: a set of synthetic spectra and a set of observed spectra from stars that have known
α
/Fe since they have also been observed using the High Efficiency and Resolution Multi-Element Spectrograph (HERMES) as part of the Galactic Archaeology with HERMES survey. We applied each model to the other sample and to a larger observed sample to assess the performance of the models. In addition, we used our models to analyse stars from the
Gaia
-Enceladus structure.
Results.
We find that the model trained on synthetic data has some ability to reconstruct
α
/Fe from synthetic spectra, but little to none when used on observed spectra. The model trained on observed data reconstructs realistic
α
/Fe from observed spectra, but only for cool stars (⪅5000 K) that have the same correlations as in the training sample between
α
/Fe and other properties such as Fe/H.
Conclusions.
Models using the ExtraTrees algorithm can be used to estimate
α
/Fe from low-resolution BP/RP spectra of cool stars. However, they do this by exploiting correlations between
α
/Fe and other parameters, rather than the causal effect of
α
/Fe on the spectrum. Hence, they are unlikely to be useful in studies that attempt to distinguish stars that only differ in
α
/Fe.
We present a mock stellar catalog, matching in volume, depth and data model the content of the planned Gaia early data release 3 (Gaia EDR3). We have generated our catalog (GeDR3mock) using galaxia, ...a tool to sample stars from an underlying Milky Way (MW) model or from N-body data. We used an updated Besançon Galactic model together with the latest PARSEC stellar evolutionary tracks, now also including white dwarfs. We added the Magellanic clouds and realistic open clusters with internal rotation. We empirically modeled uncertainties based on Gaia DR2 (GDR2) and scaled them according to the longer baseline in Gaia EDR3. The apparent magnitudes were reddened according to a new selection of 3D extinction maps. To help with the Gaia selection function we provide all-sky magnitude limit maps in G and BP for a few relevant GDR2 subsets together with the routines to produce these maps for user-defined subsets. We supplement the catalog with photometry and extinctions in non-Gaia bands. The catalog is available in the Virtual Observatory (http://dc.g-vo.org/tableinfo/gedr3mock.main) and can be queried just like the actual Gaia EDR3 will be. We highlight a few capabilities of the Astronomy Data Query Language with educative catalog queries. We use the data extracted from those queries to compare GeDR3mock to GDR2, which emphasises the importance of adding observational noise to the mock data. Since the underlying truth, e.g., stellar parameters, is know in GeDR3mock, it can be used to construct priors as well as mock data tests for parameter estimation. All code, models and data used to produce GeDR3mock are linked and contained in galaxia_wrap (https://github.com/jan-rybizki/Galaxia_wrap), a python package, representing a fast galactic forward model, able to project MW models and N-body data into realistic Gaia observables.
Pulsating stars, such as Cepheids, Miras, and RR Lyrae stars, are important distance indicators and calibrators of the "cosmic distance ladder," and yet their period-luminosity-metallicity (PLZ) ...relations are still constrained using simple statistical methods that cannot take full advantage of available data. To enable optimal usage of data provided by the Gaia mission, we present a probabilistic approach that simultaneously constrains parameters of PLZ relations and uncertainties in Gaia parallax measurements. We demonstrate this approach by constraining PLZ relations of type ab RR Lyrae stars in near-infrared W1 and W2 bands, using Tycho-Gaia Astrometric Solution (TGAS) parallax measurements for a sample of 100 type ab RR Lyrae stars located within 2.5 kpc of the Sun. The fitted PLZ relations are consistent with previous studies, and in combination with other data, deliver distances precise to 6% (once various sources of uncertainty are taken into account). To a precision of 0.05 mas (1 ), we do not find a statistically significant offset in TGAS parallaxes for this sample of distant RR Lyrae stars (median parallax of 0.8 mas and distance of 1.4 kpc). With only minor modifications, our probabilistic approach can be used to constrain PLZ relations of other pulsating stars, and we intend to apply it to Cepheid and Mira stars in the near future.
We measure the mass function for a sample of 840 young star clusters with ages between 10 and 300 Myr observed by the Panchromatic Hubble Andromeda Treasury (PHAT) survey in M31. The data show clear ...evidence of a high-mass truncation: only 15 clusters more massive than are observed, compared to the ∼100 expected for a canonical pure power-law mass function with the same total number of clusters above the catalog completeness limit. Adopting a Schechter function parameterization, we fit a characteristic truncation mass of M☉. Although previous studies have measured cluster mass function truncations, the characteristic truncation mass we measure is the lowest ever reported. Combining this M31 measurement with previous results, we find that the cluster mass function truncation correlates strongly with the characteristic star formation rate surface density of the host galaxy, where . We also find evidence that suggests the observed Mc- relation also applies to globular clusters, linking the two populations via a common formation pathway. If so, globular cluster mass functions could be useful tools for constraining the star formation properties of their progenitor host galaxies in the early universe.
Observational tests of stellar and Galactic chemical evolution call for the joint knowledge of a star's physical parameters, detailed element abundances, and precise age. For cool main-sequence (MS) ...stars the abundances of many elements can be measured from spectroscopy, but ages are very hard to determine. The situation is different if the MS star has a white dwarf (WD) companion and a known distance, as the age of such a binary system can then be determined precisely from the photometric properties of the cooling WD. As a pilot study for obtaining precise age determinations of field MS stars, we identify nearly 100 candidates for such wide binary systems: a faint WD whose GPS1 proper motion matches that of a brighter MS star in Gaia/TGAS with a good parallax ( ϖ/ϖ ≤ 0.05). We model the WD's multi-band photometry with the BASE-9 code using this precise distance (assumed to be common for the pair) and infer ages for each binary system. The resulting age estimates are precise to ≤10% (≤20%) for 42 (67) MS-WD systems. Our analysis more than doubles the number of MS-WD systems with precise distances known to date, and it boosts the number of such systems with precise age determination by an order of magnitude. With the advent of the Gaia DR2 data, this approach will be applicable to a far larger sample, providing ages for many MS stars (that can yield detailed abundances for over 20 elements), especially in the age range of 2-8 , where there are only few known star clusters.
Abstract
Statistical studies of cataloged object properties are central to astrophysics. But one cannot model those objects’ population properties without the sample’s selection function, the ...quantitative understanding of which objects could have ended up in such a catalog. As didactic introductions to this topic are scarce in the astrophysical literature, we provide one here, addressing the following questions: What is a selection function? On what arguments
q
should it depend? Over what domain must a selection function be defined? What simplifying approximations can be made? And, how is a selection function used in “modeling”? We argue that volume-complete samples, limited by the faintest objects, reflect a highly suboptimal selection function, needlessly reducing the number of bright and usually rare sample members. We illustrate these points by a worked example: github.com/gaia-unlimited/WD-selection-function, deriving the space density of white dwarfs (WDs) in the Galactic neighborhood as a function of their luminosity and color, Φ
0
(
M
G
, (
B
−
R
)) in mag
−2
pc
−3
. We construct a sample
of 10
5
presumed WDs through straightforward selection cuts on the Gaia EDR3 catalog in magnitude, color, and parallax,
q
= (
G
, (
B
−
R
),
ϖ
). We then combine a simple model for Φ
0
with this selection function’s
S
(
q
)
effective survey volume to estimate Φ
0
(
M
G
, (
B
−
R
)) precisely and robustly against the detailed choices for
S
(
q
)
. This resulting WD luminosity–color function Φ
0
(
M
G
, (
B
−
R
)) differs dramatically from the initial number density distribution in the luminosity−color plane: by orders of magnitude in density and by four magnitudes in density peak location.
The extended main-sequence turn offs (eMSTOs) of several young to intermediate age clusters are examined in the Magellanic Clouds and the Milky Way. We explore the effects of extended star formation ...(eSF) and a range of stellar rotation rates on the behavior of the color-magnitude diagram, paying particular attention to the MSTO. We create synthetic stellar populations based on MESA stellar models to simulate observed Hubble Space Telescope and Gaia star cluster data. We model the effect of rotation as a nonparametric distribution, allowing for maximum flexibility. In our models the slow rotators comprise the blueward, and fast rotators the redward portion of the eMSTO. We simulate data under three scenarios: nonrotating eSF, a range of rotation rates with a single age, and a combination of age and rotation effects. We find that two of the five clusters (the youngest and oldest) favor an age spread, but these also achieve the overall worst fits of all clusters. The other three clusters show comparable statistical evidence between rotation and an age spread. In all five cases, a rotation-rate distribution alone is capable of qualitatively matching the observed eMSTO structure. In future work, we aim to compare our predicted V sin i with observations in order to better constrain the physics related to stellar rotation.