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Register a new userCharacterizing stellar halo populations II: The age gradient in blue horizontal-branch stars
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The distribution of Milky Way halo blue horizontal-branch (BHB) stars is examined using action-based extended distribution functions (EDFs) that describe the locations of stars in phase space, metallicity, and age. The parameters of the EDFs are fitted using stars observed in the Sloan Extension for Galactic Understanding and Exploration-II (SEGUE-II) survey that trace the phase-space kinematics and chemistry out to ~70 kpc. A maximum a posteriori probability (MAP) estimate method and a Markov Chain Monte Carlo method are applied, taking into account the selection function in positions, distance, and metallicity for the survey. The best-fit EDF declines with actions less steeply at actions characteristic of the inner halo than at the larger actions characteristic of the outer halo, and older ages are found at smaller actions than at larger actions. In real space, the radial density profile steepens smoothly from -2 at ~2 kpc to -4 in the outer halo, with an axis ratio ~0.7 throughout. There is no indication for rotation in the BHBs, although this is highly uncertain. A moderate level of radial anisotropy is detected, with $beta_s$ varying from isotropic to between ~0.1 and ~0.3 in the outer halo depending on latitude. The BHB data are consistent with an age gradient of -0.03 Gyr kpc$^{-1}$, with some uncertainty in the distribution of the larger ages. These results are consistent with a scenario in which older, larger systems contribute to the inner halo, whilst the outer halo is primarily comprised of younger, smaller systems.
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We present an analysis of the relative age distribution of the Milky Way halo, based on samples of blue horizontal-branch (BHB) stars obtained from the Panoramic Survey Telescope and Rapid Response System and textit{Galaxy Evolution Explorer} photometry, as well a Sloan Digital Sky Survey spectroscopic sample. A machine-learning approach to the selection of BHB stars is developed, using support vector classification, with which we produce chronographic age maps of the Milky Way halo out to 40,kpc from the Galactic center. We identify a characteristic break in the relative age profiles of our BHB samples, corresponding to a Galactocentric radius of $R_{rm{GC}} sim 14$,kpc. Within the break radius, we find an age gradient of $-63.4 pm 8.2$ Myr kpc$^{-1}$, which is significantly steeper than obtained by previous studies that did not discern between the inner- and outer-halo regions. The gradient in the relative age profile and the break radius signatures persist after correcting for the influence of metallicity on our spectroscopic calibration sample. We conclude that neither are due to the previously recognized metallicity gradient in the halo, as one passes from the inner-halo to the outer-halo region. Our results are consistent with a dissipational formation of the inner-halo population, involving a few relatively massive progenitor satellites, such as those proposed to account for the assembly of textit{Gaia}-Enceladus, which then merged with the inner halo of the Milky Way.
We have analyzed new HST/ACS and HST/WFC3 imaging in F475W and F814W of two previously-unobserved fields along the M31 minor axis to confirm our previous constraints on the shape of M31s inner stellar halo. Both of these new datasets reach a depth of at least F814W$<$27 and clearly detect the blue horizontal branch (BHB) of the field as a distinct feature of the color-magnitude diagram. We measure the density of BHB stars and the ratio of BHB to red giant branch stars in each field using identical techniques to our previous work. We find excellent agreement with our previous measurement of a power-law for the 2-D projected surface density with an index of 2.6$^{+0.3}_{-0.2}$ outside of 3 kpc, which flattens to $alpha <$1.2 inside of 3 kpc. Our findings confirm our previous suggestion that the field BHB stars in M31 are part of the halo population. However, the total halo profile is now known to differ from this BHB profile, which suggests that we have isolated the metal-poor component. This component appears to have an unbroken power-law profile from 3-150 kpc but accounts for only about half of the total halo stellar mass. Discrepancies between the BHB density profile and other measurements of the inner halo are therefore likely due to the different profile of the metal-rich halo component, which is not only steeper than the profile of the met al-poor component, but also has a larger core radius. These profile differences also help to explain the large ratio of BHB/RGB stars in our observations.
We present the structure of the Milky Way stellar halo beyond Galactocentric distances of $r = 50$ kpc traced by blue horizontal-branch (BHB) stars, which are extracted from the survey data in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We select BHB candidates based on $(g,r,i,z)$ photometry, where the $z$-band is on the Paschen series and the colors that involve the $z$-band are sensitive to surface gravity. About 450 BHB candidates are identified between $r = 50$ kpc and 300 kpc, most of which are beyond the reach of previous large surveys including the Sloan Digital Sky Survey. We find that the global structure of the stellar halo in this range has substructures, which are especially remarkable in the GAMA15H and XMM-LSS fields in the HSC-SSP. We find that the stellar halo can be fitted to a single power-law density profile with an index of $alpha simeq 3.3$ ($3.5$) with (without) these fields and its global axial ratio is $q simeq 2.2$ ($1.3$). Thus, the stellar halo may be significantly disturbed and be made in a prolate form by halo substructures, perhaps associated with the Sagittarius stream in its extension beyond $r sim 100$ kpc. For a broken power-law model allowing different power-law indices inside/outside a break radius, we obtain a steep power-law slope of $alpha sim 5$ outside a break radius of $simeq 100$ kpc ($200$ kpc) for the case with (without) GAMA15H and XMM-LSS. This radius of $200$ kpc might be as close as a halo boundary if there is any, although larger BHB sample is required from further HSC-SSP survey to increase its statistical significance.
We investigate the performance of some common machine learning techniques in identifying BHB stars from photometric data. To train the machine learning algorithms, we use previously published spectroscopic identifications of BHB stars from SDSS data. We investigate the performance of three different techniques, namely k nearest neighbour classification, kernel density estimation and a support vector machine (SVM). We discuss the performance of the methods in terms of both completeness and contamination. We discuss the prospect of trading off these values, achieving lower contamination at the expense of lower completeness, by adjusting probability thresholds for the classification. We also discuss the role of prior probabilities in the classification performance, and we assess via simulations the reliability of the dataset used for training. Overall it seems that no-prior gives the best completeness, but adopting a prior lowers the contamination. We find that the SVM generally delivers the lowest contamination for a given level of completeness, and so is our method of choice. Finally, we classify a large sample of SDSS DR7 photometry using the SVM trained on the spectroscopic sample. We identify 27,074 probable BHB stars out of a sample of 294,652 stars. We derive photometric parallaxes and demonstrate that our results are reasonable by comparing to known distances for a selection of globular clusters. We attach our classifications, including probabilities, as an electronic table, so that they can be used either directly as a BHB star catalogue, or as priors to a spectroscopic or other classification method. We also provide our final models so that they can be directly applied to new data.
Blue horizontal-branch stars are Population II objects which are burning helium in their core and possess a hydrogen-burning shell and radiative envelope. Because of their low rotational velocities, diffusion has been predicted to work in their atmospheres. In many respects, blue horizontal-branch stars closely resemble the magnetic chemically peculiar stars of the upper main sequence, which show photometric variability caused by abundance spots on their surfaces. These spots are thought to be caused by diffusion and the presence of a stable magnetic field. However, the latter does not seem to be axiomatic. We searched for rotationally induced variability in 30 well-established bright field blue horizontal-branch stars in the solar neighbourhood and searched the literature for magnetic fields measurements of our targets. We employed archival photometric time series data from the ASAS, ASAS-SN, and SuperWASP surveys. The data were carefully reduced and processed, and a time series analysis was applied using several different techniques. We also synthesized existing photometric and spectroscopic data of magnetic chemically peculiar stars in order to study possible different surface characteristics producing lower amplitudes. In the accuracy limit of the employed data, no significant variability signals were found in our sample stars. The resulting upper limits for variability are given. We conclude that either no stellar surface spots are present in field blue horizontal-branch stars, or their characteristics (contrast, total area, and involved elements) are not sufficient to produce amplitudes larger than a few millimagnitudes in the optical wavelength region. New detailed models taking into account the elemental abundance pattern of blue horizontal-branch stars are needed to synthesize light curves for a comparison with our results.
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