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Register a new userMachine-Learned Identification of RR Lyrae Stars from Sparse, Multi-band Data: the PS1 Sample
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RR Lyrae stars may be the best practical tracers of Galactic halo (sub-)structure and kinematics. The PanSTARRS1 (PS1) $3pi$ survey offers multi-band, multi-epoch, precise photometry across much of the sky, but a robust identification of RR Lyrae stars in this data set poses a challenge, given PS1s sparse, asynchronous multi-band light curves ($lesssim 12$ epochs in each of five bands, taken over a 4.5-year period). We present a novel template fitting technique that uses well-defined and physically motivated multi-band light curves of RR Lyrae stars, and demonstrate that we get accurate period estimates, precise to 2~sec in $>80%$ of cases. We augment these light curve fits with other {em features} from photometric time-series and provide them to progressively more detailed machine-learned classification models. From these models we are able to select the widest ($3/4$ of the sky) and deepest (reaching 120 kpc) sample of RR Lyrae stars to date. The PS1 sample of $sim 45,000$ RRab stars is pure (90%), and complete (80% at 80 kpc) at high galactic latitudes. It also provides distances precise to 3%, measured with newly derived period-luminosity relations for optical/near-infrared PS1 bands. With the addition of proper motions from {em Gaia} and radial velocity measurements from multi-object spectroscopic surveys, we expect the PS1 sample of RR Lyrae stars to become the premier source for studying the structure, kinematics, and the gravitational potential of the Galactic halo. The techniques presented in this study should translate well to other sparse, multi-band data sets, such as those produced by the Dark Energy Survey and the upcoming Large Synoptic Survey Telescope Galactic plane sub-survey.
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This paper presents results from photometric and statistical-parallax analysis of a sample of 850 field RR Lyrae (RRL) variables. The photometric and spectroscopic data for sample RRLs are obtained from (1) our new spectroscopic observations (for 448 RRLs) carried out with the Southern African Large Telescope (SALT); (2) our photometric observations using the 1.0-m telescope of the South African Astronomical Observatory (SAAO), and (3) literature. These are combined with accurate proper motion data from the second release of textit{Gaia} mission (DR2). This study primarily determines the velocity distribution of solar neighborhood RRLs, and it also calibrates the zero points of the RRLs visual V-band luminosity-metallicity (LZ or $M_V-$[text{Fe/H}]) relation and their period-luminosity-metallicity (PLZ) relations in the textit{WISE} $W_1-$ and textit{2MASS} $Ks-$band. The calibrated PLZ and LZ relations are used to estimate the Galactic Center distance and the distance modulus of the Large Magellanic Cloud (LMC), which are found to be 7.99$pm$0.49,kpc and 18.46$pm$0.09 ,mag, respectively. All our results are in excellent agreement with available literature based on statistical parallax analysis, but are considerably more accurate and precise. Moreover, the zero-points of our calibrated PLZ and LZ relations are quite consistent with current results found by other techniques and yield the LMC distance modulus that is within 0.04,mag of the current most precise estimate.
In area and depth, the Pan-STARRS1 (PS1) 3$pi$ survey is unique among many-epoch, multi-band surveys and has enormous potential for all-sky identification of variable sources. PS1 has observed the sky typically seven times in each of its five bands ($grizy$) over 3.5 years, but unlike SDSS not simultaneously across the bands. Here we develop a new approach for quantifying statistical properties of non-simultaneous, sparse, multi-color lightcurves through light-curve structure functions, effectively turning PS1 into a $sim 35$-epoch survey. We use this approach to estimate variability amplitudes and timescales $(omega_r, tau)$ for all point-sources brighter than $r_{mathrm{P1}}=21.5$ mag in the survey. With PS1 data on SDSS Stripe 82 as ``ground truth, we use a Random Forest Classifier to identify QSOs and RR Lyrae based on their variability and their mean PS1 and WISE colors. We find that, aside from the Galactic plane, QSO and RR Lyrae samples of purity $sim$75% and completeness $sim$92% can be selected. On this basis we have identified a sample of $sim 1,000,000$ QSO candidates, as well as an unprecedentedly large and deep sample of $sim$150,000 RR Lyrae candidates with distances from $sim$10 kpc to $sim$120 kpc. Within the Draco dwarf spheroidal, we demonstrate a distance precision of 6% for RR Lyrae candidates. We provide a catalog of all likely variable point sources and likely QSOs in PS1, a total of $25.8times 10^6$ sources.
RR Lyrae stars for a long time had the reputation of being rather simple pulsators, but the advent of high-precision space photometry has meanwhile changed this picture dramatically. This article summarizes the results obtained for two remarkable Blazhko RR Lyrae stars and discusses how our view of RR Lyrae stars has changed since the availability of ultra-precise satellite photometry as it is obtained by CoRoT and Kepler. Both stars, CoRoT 105288363 and V445 Lyrae, show a multitude of phenomena that were impossible to observe from the ground, either because of the small amplitude of the effect, or because uninterrupted long-term monitoring was required for a detection. Not only was it found that strong and irregular cycle-to-cycle changes of the Blazhko effect can occur, and that seemingly chaotic phenomena need to be accounted for when modeling the Blazhko effect, but also a rich spectrum of low-amplitude frequencies was detected in addition to the fundamental radial pusation in RRab stars. The so-called period doubling phenomenon, higher radial overtones and possibly also non-radial modes make RR Lyrae stars more multifaceted than previously thought. This article presents the various aspects of irregularity of the Blazhko effect, questioning its long-standing definition as a periodic modulation, and also discusses the low-amplitude pulsation signatures that had been hidden in the noise of observations for centuries.
We identify the RR Lyrae and delta Scuti (DSCT) stars in three catalogs of GALEX variable sources. The NUV amplitude of RR Lyrae stars is about twice that in V-band, so we find a larger percentage of low amplitude variables than catalogs such as Abbas et al (2014). Interestingly, the (NUV-V)_0 color is sensitive to metallicity and can be used to distinguish between variables of the same period but differing [Fe/H]. This color is also more sensitive to T_eff than optical colors and can be used to identify the red edge of the instability gap. We find 8 DSCT stars, 17 RRc stars, 1 RRd star and 84 RRab stars in the GALEX variable catalogs of Welsh et al (2005) and Wheatley et al (2008). We also classify 6 DSCT stars, 5 RRc stars and 18 RRab stars among the 55 variable GALEX sources identified as stars or RR Lyraes in the catalog of Gezari et al (2013). We provide ephemerides and light curves for the 26 variables that were not previously known.
We report the detection of spatially distinct stellar density features near the apocenters of the Sagittarius (Sgr) streams main leading and trailing arm. These features are clearly visible in a high-fidelity stellar halo map that is based on RR Lyrae from Pan-STARRS1: there is a plume of stars 10 kpc beyond the apocenter of the leading arm, and there is a spur extending to 130 kpc, almost 30 kpc beyond the previously detected apocenter of the trailing arm. Such apocenter substructure is qualitatively expected in any Sgr stream model, as stars stripped from the progenitor at different pericenter passages become spatially separated there. The morphology of these new Sgr stream substructures could provide much-needed new clues and constraints for modeling the Sgr system, including the level of dynamical friction that Sgr has experienced. We also report the discovery of a new, presumably unrelated halo substructure at 80 kpc from the Sun and $10^circ$ from the Sgr orbital plane, which we dub the Outer Virgo Overdensity.
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