arXiv subjects

Coryn A. L. Bailer-Jones

Publications and source records attributed to Coryn A. L. Bailer-Jones.

At least 37 records · Page 2Linked to original sources

arXiv2016

Estimating distances from parallaxes. III. Distances of two million stars in the Gaia DR1 catalogue

We infer distances and their asymmetric uncertainties for two million stars using the parallaxes published in the Gaia DR1 (GDR1) catalogue. We do this with two distance priors: A minimalist, isotropic prior assuming an exponentially decreasing space density with increasing distance, and an anisotropic prior derived from the observability of stars in a Milky Way model. We validate our results by comparing our distance estimates for 105 Cepheids which have more precise, independently estimated distances. For this sample we find that the Milky Way prior performs better (the RMS of the scaled residuals is 0.40) than the exponentially decreasing space density prior (RMS is 0.57), although for distances beyond 2 kpc the Milky Way prior performs worse, with a bias in the scaled residuals of -0.36 (vs. -0.07 for the exponentially decreasing space density prior). We do not attempt to include the photometric data in GDR1 due to the lack of reliable colour information. Our distance catalogue is available at http://www.mpia.de/homes/calj/tgas distances/main.html as well as at CDS. This should only be used to give individual distances. Combining data or testing models should be done with the original parallaxes, and attention paid to correlated and systematic uncertainties.

astro-ph.GA↗

arXiv2016

Estimating distances from parallaxes. II. Performance of Bayesian distance estimators on a Gaia-like catalogue

Estimating a distance by inverting a parallax is only valid in the absence of noise. As most stars in the Gaia catalogue will have non-negligible fractional parallax errors, we must treat distance estimation as a constrained inference problem. Here we investigate the performance of various priors for estimating distances, using a simulated Gaia catalogue of one billion stars. We use three minimalist, isotropic priors, as well an anisotropic prior derived from the observability of stars in a Milky Way model. The two priors that assume a uniform distribution of stars--either in distance or in space density---give poor results: The root mean square fractional distance error, f_RMS, grows far in excess of 100% once the fractional parallax error, f_true, is larger than 0.1. A prior assuming an exponentially decreasing space density with increasing distance performs well once its single scale length parameter has been set to an appropriate value: f_RMS is roughly equal to f_true for f_true < 0.4, yet does not increase further as f_true increases up to to 1.0. The Milky Way prior performs well except towards the Galactic centre, due to a mismatch with the (simulated) data. Such mismatches will be inevitable (and remain unknown) in real applications, and can produce large errors. We therefore suggest to adopt the simpler exponentially decreasing space density prior, which is also less time-consuming to compute. Including Gaia photometry improves the distance estimation significantly for both the Milky Way and exponentially decreasing space density prior, yet doing so requires additional assumptions about the physical nature of stars.

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arXiv2015

A Package for the Automated Classification of Periodic Variable Stars

We present a machine learning package for the classification of periodic variable stars. Our package is intended to be general: it can classify any single band optical light curve comprising at least a few tens of observations covering durations from weeks to years, with arbitrary time sampling. We use light curves of periodic variable stars taken from OGLE and EROS-2 to train the model. To make our classifier relatively survey-independent, it is trained on 16 features extracted from the light curves (e.g. period, skewness, Fourier amplitude ratio). The model classifies light curves into one of seven superclasses - Delta Scuti, RR Lyrae, Cepheid, Type II Cepheid, eclipsing binary, long-period variable, non-variable - as well as subclasses of these, such as ab, c, d, and e types for RR Lyraes. When trained to give only superclasses, our model achieves 0.98 for both recall and precision as measured on an independent validation dataset (on a scale of 0 to 1). When trained to give subclasses, it achieves 0.81 for both recall and precision. In order to assess classification performance of the subclass model, we applied it to the MACHO, LINEAR, and ASAS periodic variables, which gave recall/precision of 0.92/0.98, 0.89/0.96, and 0.84/0.88, respectively. We also applied the subclass model to Hipparcos periodic variable stars of many other variability types that do not exist in our training set, in order to examine how much those types degrade the classification performance of our target classes. In addition, we investigate how the performance varies with the number of data points and duration of observations. We find that recall and precision do not vary significantly if the number of data points is larger than 80 and the duration is more than a few weeks. The classifier software of the subclass model is available from the GitHub repository (https://goo.gl/xmFO6Q).

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arXiv2014

The EPOCH Project: I. Periodic variable stars in the EROS-2 LMC database

The EPOCH (EROS-2 periodic variable star classification using machine learning) project aims to detect periodic variable stars in the EROS-2 light curve database. In this paper, we present the first result of the classification of periodic variable stars in the EROS-2 LMC database. To classify these variables, we first built a training set by compiling known variables in the Large Magellanic Cloud area from the OGLE and MACHO surveys. We crossmatched these variables with the EROS-2 sources and extracted 22 variability features from 28 392 light curves of the corresponding EROS-2 sources. We then used the random forest method to classify the EROS-2 sources in the training set. We designed the model to separate not only $δ$ Scuti stars, RR Lyraes, Cepheids, eclipsing binaries, and long-period variables, the superclasses, but also their subclasses, such as RRab, RRc, RRd, and RRe for RR Lyraes, and similarly for the other variable types. The model trained using only the superclasses shows 99% recall and precision, while the model trained on all subclasses shows 87% recall and precision. We applied the trained model to the entire EROS-2 LMC database, which contains about 29 million sources, and found 117 234 periodic variable candidates. Out of these 117 234 periodic variables, 55 285 have not been discovered by either OGLE or MACHO variability studies. This set comprises 1 906 $δ$ Scuti stars, 6 607 RR Lyraes, 638 Cepheids, 178 Type II Cepheids, 34 562 eclipsing binaries, and 11 394 long-period variables. A catalog of these EROS-2 LMC periodic variable stars will be available online at http://stardb.yonsei.ac.kr and at the CDS website (http://vizier.u-strasbg.fr/viz-bin/VizieR).

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arXiv2013

Weather on the Nearest Brown Dwarfs: Resolved Simultaneous Multi-Wavelength Variability Monitoring of WISE J104915.57-531906.1AB

We present two epochs of MPG/ESO 2.2m GROND simultaneous 6-band ($r'i'z'JHK$) photometric monitoring of the closest known L/T transition brown dwarf binary WISE J104915.57-531906.1AB. We report here the first resolved variability monitoring of both the T0.5 and L7.5 components. We obtained 4 hours of focused observations on the night of UT 2013-04-22, as well as 4 hours of defocused (unresolved) observations on the night of UT 2013-04-16. We note a number of robust trends in our light curves. The $r'$ and $i'$ light curves appear to be anticorrelated with $z'$ and $H$ for the T0.5 component and in the unresolved lightcurve. In the defocused dataset, $J$ appears correlated with $z'$ and $H$ and anticorrelated with $r'$ and $i'$, while in the focused dataset we measure no variability for $J$ at the level of our photometric precision, likely due to evolving weather phenomena. In our focused T0.5 component lightcurve, the $K$ band lightcurve displays a significant phase offset relative to both $H$ and $z'$. We argue that the measured phase offsets are correlated with atmospheric pressure probed at each band, as estimated from 1D atmospheric models. We also report low-amplitude variability in $i'$ and $z'$ intrinsic to the L7.5 component.

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arXiv2013

Assessment of stochastic and deterministic models of 6304 quasar lightcurves from SDSS Stripe 82

The optical light curves of many quasars show variations of tenths of a magnitude or more on time scales of months to years. This variation often cannot be described well by a simple deterministic model. We perform a Bayesian comparison of over 20 deterministic and stochastic models on 6304 QSO light curves in SDSS Stripe 82. We include the damped random walk (or Ornstein-Uhlenbeck [OU] process), a particular type of stochastic model which recent studies have focused on. Further models we consider are single and double sinusoids, multiple OU processes, higher order continuous autoregressive processes, and composite models. We find that only 29 out of 6304 QSO lightcurves are described significantly better by a deterministic model than a stochastic one. The OU process is an adequate description of the vast majority of cases (6023). Indeed, the OU process is the best single model for 3462 light curves, with the composite OU process/sinusoid model being the best in 1706 cases. The latter model is the dominant one for brighter/bluer QSOs. Furthermore, a non-negligible fraction of QSO lightcurves show evidence that not only the mean is stochastic but the variance is stochastic, too. Our results confirm earlier work that QSO light curves can be described with a stochastic model, but place this on a firmer footing, and further show that the OU process is preferred over several other stochastic and deterministic models. Of course, there may well exist yet better (deterministic or stochastic) models which have not been considered here.

astro-ph.CO↗

arXiv2011

The substellar mass function in the central region of the open cluster Praesepe from deep LBT observations

Studies of the mass function (MF) of open clusters of different ages allow us to probe the efficiency with which brown dwarfs evaporate from clusters to populate the field. Surveys of older clusters (age >100 Myr) are not affected so severely by several problems encountered in young clusters, such as intra-cluster extinction and large uncertainties in brown dwarf models. We present the results of a deep photometric survey to study the MF of the central region of the old open cluster Praesepe (age~590$^{+150}_{-120}$ Myr, distance ~190$^{+6.0}_{-5.8}$ pc), down to the substellar regime. We performed an optical ($riz$ and $Y$-band) photometric survey of Praesepe using the Large Binocular Telescope Camera covering an area of ~0.59 deg$^2$ in the cluster centre from $i$~19.0 mag (~100 M_Jup) down to a 5$σ$ detection limit at $i$~25.6mag (~40 M_Jup). The survey is approximately 95% complete at $i=23.8$ mag and $z=22.0$ mag (~55 M_Jup). We identify 59 cluster member candidates, of which 37 are substellar, by comparing with the predictions of a dusty atmosphere model. The MF of those candidates rises from the substellar boundary until ~67 M_Jup and then declines. This is quite different from the form inferred for other open clusters older than 50 Myr, but seems to be similar to those found in very young open clusters, the MFs of which peak at ~10 M_Jup. Either Praesepe really does have a different MF from other clusters or they had similar initial MFs but a different dynamical evolution. Since most of the candidates are faint, we lack astrometric or spectroscopic follow-ups to test their memberships. However, the contaminations by field dwarfs, galaxies, or giants are found to have little effect on the shape of MF and therefore the MF of `real' cluster members should have similar characteristics.

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arXiv2010

Classification of field dwarfs and giants in RAVE and its use in stellar stream detection

An efficient separation between dwarfs and giants in surveys of bright stars is important, especially for studies in which distances are estimated through photometric parallax relations. We use the available spectroscopic log g estimates from the second RAVE data release (DR2) to assign each star a probability for being a dwarf or subgiant/giant based on mixture model fits to the log g distribution in different color bins. We further attempt to use these stars as a labeled training set in order to classify stars which lack log g estimates into dwarfs and giants with a SVM algorithm. We assess the performance of this classification against different choices of the input feature vector. In particular, we use different combinations of reduced proper motions, 2MASS JHK, DENIS IJK and USNO-B B2R2 apparent magnitudes. Our study shows that -- for our color ranges -- the infrared bands alone provide no relevant information to separate dwarfs and giants. Even when optical bands and reduced proper motions are added, the fraction of true giants classified as dwarfs (the contamination) remains above 20%. Using only the dwarfs with available spectroscopic log g and distance estimates (the latter from Breddels et al. 2010), we then repeat the stream search by Klement, Fuchs & Rix (2008, KFR08), which assumed all stars were dwarfs and claimed the discovery of a new stellar stream at V = -160 km/s in a sample of 7015 stars from RAVE DR1. Our re-analysis of the pure DR2 dwarf sample exhibits an overdensity of 5 stars at the phase-space position of the KFR08 stream, with a metallicity distribution that appears inconsistent with that of stars at comparably low rotational velocities. Compared to several smooth Milky Way models, the mean standardized deviation of the KFR08 stream is only marginal at 1.6$\pm$0.4... (abbreviated)

astro-ph.GA↗

arXiv2010

Photometric identification of blue horizontal branch stars

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.

astro-ph.GA↗

arXiv2008

The Milky Way Tomography with SDSS: II. Stellar Metallicity

Using effective temperature and metallicity derived from SDSS spectra for ~60,000 F and G type main sequence stars (0.2<g-r<0.6), we develop polynomial models for estimating these parameters from the SDSS u-g and g-r colors. We apply this method to SDSS photometric data for about 2 million F/G stars and measure the unbiased metallicity distribution for a complete volume-limited sample of stars at distances between 500 pc and 8 kpc. The metallicity distribution can be exquisitely modeled using two components with a spatially varying number ratio, that correspond to disk and halo. The two components also possess the kinematics expected for disk and halo stars. The metallicity of the halo component is spatially invariant, while the median disk metallicity smoothly decreases with distance from the Galactic plane from -0.6 at 500 pc to -0.8 beyond several kpc. The absence of a correlation between metallicity and kinematics for disk stars is in a conflict with the traditional decomposition in terms of thin and thick disks. We detect coherent substructures in the kinematics--metallicity space, such as the Monoceros stream, which rotates faster than the LSR, and has a median metallicity of [Fe/H]=-0.96, with an rms scatter of only ~0.15 dex. We extrapolate our results to the performance expected from the Large Synoptic Survey Telescope (LSST) and estimate that the LSST will obtain metallicity measurements accurate to 0.2 dex or better, with proper motion measurements accurate to ~0.2 mas/yr, for about 200 million F/G dwarf stars within a distance limit of ~100 kpc (g<23.5). [abridged]

astro-ph↗

arXiv2006

Prospects for Gaia and other space-based surveys

Gaia is a fully-approved all-sky astrometric and photometric survey due for launch in 2011. It will measure accurate parallaxes and proper motions for everything brighter than G=20 (ca. 10^9 stars). Its primary objective is to study the composition, origin and evolution of our Galaxy from the 3D structure, 3D velocities, abundances and ages of its stars. In some respects it can be considered as a cosmological survey at redshift zero. Several other upcoming space-based surveys, in particular JWST and Herschel, will study star and galaxy formation in the early (high-redshift) universe. In this paper I briefly describe these missions, as well as SIM and Jasmine, and explain why they need to observe from space. I then discuss some Galactic science contributions of Gaia concerning dark matter, the search for substructure, stellar populations and the mass--luminosity relation. The Gaia data are complex and require the development of novel analysis methods; here I summarize the principle of the astrometric processing. In the last two sections I outline how the Gaia data can be exploited in connection with other observational and theoretical work in order to build up a more comprehensive picture of galactic evolution.

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arXiv2005

Multiband photometric detection of a huge flare on the M9 dwarf 2MASSW J1707183+643933

We present simultaneous UV-G-R-I monitoring of 19 M dwarfs that revealed a huge flare on the M9 dwarf 2MASSW J1707183+643933 with an amplitude in the UV of at least 6 magnitudes. This is one of the strongest detections ever of an optical flare on an M star and one of the first in an ultracool dwarf (UCD, spectral types later than about M7). Four intermediate strength flares (Delta m_UV < 4 mag) were found in this and three other targets. For the whole sample we deduce a flare probability of 0.013 (rate of 0.018/hr), and 0.049 (0.090/hr) for 2M1707+64 alone. Deviations of the flare emission from a blackbody is consistent with strong Halpha line emission. We also confirm the previously found rotation period for 2M1707+64 (Rockenfeller, Bailer-Jones & Mundt (2006), http://arxiv.org/abs/astro-ph/0511614/) and determine it more precisely to be 3.619 +/- 0.015 hr.

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arXiv2005

Variability and periodicity of field M dwarfs revealed by multichannel monitoring

We present simultaneous, multiband monitoring of 19 field M dwarfs (spectral types M2-M9). Significant variability was found in seven objects in at least one out of the three channels I, R and G. Two objects, LHS370 (M5V) and 2M1707+64 (M9V), show periods of 5.9+-2.0 and 3.65+-0.1 hours respectively. On account of the agreement with the typical values of v*sin(i) published for M dwarfs (Mohanty & Basri 2003), we claim these to be the objects' rotation periods. In the case of 2M1707+64 we furthermore find evidence for the presence of magnetically-induced cool spots as the reason for the observed variability (at a temperature contrast of 4-8 percent, with a projected surface coverage factor of less than 0.075) and can rule out the scenario of dust clouds (as represented by the COND or DUSTY models). Comparing the frequency of occurrence of variability in this and various L dwarf samples published over the past few years, we find that variability is more common in field L dwarfs than in field M dwarfs. This implies a change in the physical nature and/or extent of surface features when moving from M to L dwarfs.

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arXiv2003

Natural Coronagraphic Observations of the Eclipsing T Tauri System KH 15D: Evidence for Accretion and Bipolar Outflow in a WTTS

We present high resolution (R $\sim$ 44,000) UVES spectra of the eclipsing pre-main sequence star KH 15D covering the wavelength range 4780 to 6810 Å obtained at three phases: out of eclipse, near minimum light and during egress. The system evidently acts like a natural coronagraph, enhancing the contrast relative to the continuum of hydrogen and forbidden emission lines during eclipse. At maximum light the H$α$ equivalent width was $\sim$2 Å and the profile showed broad wings and a deep central absorption. During egress the equivalent width was much higher ($\sim$70 Å) and the broad wings, which extend to $\pm$ 300 km/s, were prominent. During eclipse totality the equivalent width was less than during egress ($\sim$40 Å) and the high velocity wings were much weaker. H$β$ showed a somewhat different behavior, revealing only the blue-shifted portion of the high velocity component during eclipse and egress. [OI] $λλ$6300, 6363 lines are easily seen both out of eclipse and when the photosphere is obscured and exhibit little or no flux variation with eclipse phase. Our interpretation is that KH 15D, although clearly a weak-line T Tauri star by the usual criteria, is still accreting matter from a circumstellar disk, and has a well-collimated bipolar jet. As the knife-edge of the occulting matter passes across the close stellar environment it is evidently revealing structure in the magnetosphere of this pre-main sequence star with unprecedented spatial resolution. We also show that there is only a small, perhaps marginally significant, change in the velocity of the K7 star between the maximum light and egress phases probed here.

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arXiv2003

The sigma Orionis substellar population

VLT/FORS spectroscopy and 2MASS near-infrared photometry, together with previously known data, have been used to establish the membership and the properties of a sample of low-mass candidate members of the sigma Orionis cluster with masses spanning from 1 Msun down to about 0.013 Msun (i.e., deuterium-burning mass limit). We have observed K-band infrared excess and remarkably intense H(alpha) emission in various cluster members, which, in addition to the previously detected forbidden emision lines and the presence of LiI in absorption at 6708 A, have allowed us to tentatively classify sigma Orionis members as classical or weak-line TTauri stars and substellar analogs. Variability of the H(alpha) line has been investigated and detected in some objects. Based on the K-band infrared excesses and the intensity of H(alpha) emission, we estimate that the minimum disk frequency of the sigma Orionis low-mass population is in the range 5-12%.

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arXiv2002

Fine Structure in the Circumstellar Environment of a Young, Solar-like Star: the Unique Eclipses of KH 15D

Results of an international campaign to photometrically monitor the unique pre-main sequence eclipsing object KH 15D are reported. An updated ephemeris for the eclipse is derived that incorporates a slightly revised period of 48.36 d. There is some evidence that the orbital period is actually twice that value, with two eclipses occurring per cycle. The extraordinary depth (~3.5 mag) and duration (~18 days) of the eclipse indicate that it is caused by circumstellar matter, presumably the inner portion of a disk. The eclipse has continued to lengthen with time and the central brightness reversals are not as extreme as they once were. V-R and V-I colors indicate that the system is slightly bluer near minimum light. Ingress and egress are remarkably well modeled by the passage of a knife-edge across a limb-darkened star. Possible models for the system are briefly discussed.

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arXiv2000

Stellar parameters from very low resolution spectra and medium band filters: Teff, logg and [M/H] using neural networks

Large scale, deep survey missions such as GAIA will collect enormous amounts of data on a significant fraction of the stellar content of our Galaxy. These missions will require a careful optimisation of their observational systems in order to maximise their scientific return, and will require reliable and automated techniques for parametrizing the very large number of stars detected. To address these two problems, I investigate the precision to which the three principal stellar parameters (Teff, logg, [M/H]) can be determined as a function of spectral resolution and signal-to-noise (SNR) ratio, using a large grid of synthetic spectra. The parametrization technique is a neural network, which is shown to provide an accurate three-dimensional physical parametrization of stellar spectra across a wide range of parameters. It is found that even at low resolution (50-100 AA FWHM) and SNR (5-10 per resolution element), Teff and \met can be determined to 1% and 0.2 dex respectively across a large range of temperatures (4000-30000 K) and metallicities (-3.0 to +1.0 dex), and that logg is measurable to +/- 0.2 dex for stars earlier than solar. The accuracy of the results is probably limited by the finite parameter sampling of the data grid. The ability of medium band filter systems (with 10-15 filters) for determining stellar parameters is also investigated. Although easier to implement in a unpointed survey, it is found that they are only competitive at higher SNRs (> 50).

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arXiv2000

Achieving a wide field near infrared camera for the Calar Alto 3.5m telescope

The ongoing development of large infrared array detectors has enabled wide field, deep surveys to be undertaken. There are, however, a number of challenges in building an infrared instrument which has both excellent optical quality and high sensitivity over a wide field. We discuss these problems in the context of building a wide field imaging camera for the 3.5m telescope at Calar Alto with the new 2K*2K HgCdTe HAWAII-2 focal plane array. Our final design is a prime focus camera with a 15' field-of-view, called Omega 2000. To achieve excellent optical quality over the whole field, we have had to dispense with the reimaging optics and cold Lyot stop. We show that creative baffling schemes, including the use of undersized baffles, can compensate for the lost K band sensitivity. A moving baffle will be employed in Omega 2000 to allow full transmission in the non-thermal J and H bands.

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