arXiv subjects

Laurent Eyer

Publications and source records attributed to Laurent Eyer.

At least 37 records · Page 2Linked to original sources

arXiv2019

Multivariate Time-series Analysis of Variable Objects in the Gaia Mission

In astronomy, we are witnessing an enormous increase in the number of source detections, precision, and diversity of measurements. Additionally, multi-epoch data is becoming the norm, making time-series analyses an important aspect of current astronomy. The Gaia mission is an outstanding example of a multi-epoch survey that provides measurements in a large diversity of domains, with its broad-band photometry; spectrophotometry in blue and red (used to derive astrophysical parameters); spectroscopy (employed to infer radial velocities, v sin(i), and other astrophysical parameters); and its extremely precise astrometry. Most of all that information is provided for sources covering the entire sky. Here, we present several properties related to the Gaia time series, such as the time sampling; the different types of measurements; the Gaia G, G BP and G RP-band photometry; and Gaia-inspired studies using the CORrelation-RAdial-VELocities data to assess the potential of the information on the radial velocity, the FWHM, and the contrast of the cross-correlation function. We also present techniques (which are used or are under development) that optimize the extraction of astrophysical information from the different instruments of Gaia, such as the principal component analysis and the multi-response regression. The detailed understanding of the behavior of the observed phenomena in the various measurement domains can lead to richer and more precise characterization of the Gaia data, including the definition of more informative attributes that serve as input to (our) machine-learning algorithms.

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arXiv2019

Distances and parallax bias in Gaia DR2

We derive Bayesian distances for all stars in the RV sample of Gaia DR2, and use the statistical method of Schoenrich, Binney & Asplund(2012) to validate the distances and test the Gaia parallaxes. In contrast to other methods, which rely on special sources, our method directly tests the distances to all stars in our sample. We find clear evidence for a near-linear trend of distance bias f with distance s, proving a parallax offset delta p. On average, we find delta p = -0.054 mas (parallaxes in Gaia DR2 need to be increased) when accounting for the parallax uncertainty under-estimate in the Gaia set (delta p = -0.048 mas on the raw parallax errors) with negligible formal error and a systematic uncertainty of about 0.006 mas. The value is in concordance with results from asteroseismic measurements, but differs from the much lower bias found on quasar samples. We further use our method to compile a comprehensive set of quality cuts in colour, apparent magnitude, and astrometric parameters. Last, we find that for this sample delta p appears to strongly depend on the parallax uncertainty sigma_p (when including the additional 0.043 mas) with a statistical confidence far in excess of 10σand a proportionality factor close to 1, though the dependence varies somewhat with sigma_p. Correcting for the sigma_p dependence also resolves otherwise unexplained correlations of the offset with the number of observation periods n_{vis} and ecliptic latitude. Every study using Gaia DR2 parallaxes/distances should investigate the sensitivity of their results on the parallax biases described here and - for fainter samples - in the DR2 astrometry paper.

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arXiv2018

All-sky RR Lyrae Stars in the Gaia Data

The second Gaia data release is expected to contain data products from about 22 months of observation. Based on these data, we aim to provide an advance publication of a full-sky Gaia map of RR Lyrae stars. Although comprehensive, these data still contain a significant fraction of sources which are insufficiently sampled for Fourier series decomposition of the periodic light variations. The challenges in the identification of RR Lyrae candidates with (much) fewer than 20 field-of-view transits are described. General considerations of the results, their limitations, and interpretation are presented together with prospects for improvement in subsequent Gaia data releases.

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arXiv2018

Understanding the Galaxy

A general overview of the understanding of our Galaxy is presented following the lines of its main structures: halo, disc, bulge/bar. This review is emphasising some "Time Domain Astronomy" contributions. On the one hand the distance and tangential motion of the stars are essential to this understanding and are obtained through multi-epoch surveys, on the other hand the chemistry of the stars, and their radial velocity are also key elements to map Galactic (sub-)structures and unravel their history and evolution. Contemporary surveys are revolutionising our view of the Milky Way and galaxies in general. Among these, the Gaia mission excels by its precision astrometry of 1.3 billion stars stretching through the Milky Way and beyond, providing the first 3D view of a major part of the Milky Way.

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arXiv2017

The fast transient sky with Gaia

The ESA Gaia satellite scans the whole sky with a temporal sampling ranging from seconds and hours to months. Each time a source passes within the Gaia field of view, it moves over 10 CCDs in 45 s and a lightcurve with 4.5 s sampling (the crossing time per CCD) is registered. Given that the 4.5 s sampling represents a virtually unexplored parameter space in optical time domain astronomy, this data set potentially provides a unique opportunity to open up the fast transient sky. We present a method to start mining the wealth of information in the per CCD Gaia data. We perform extensive data filtering to eliminate known on-board and data processing artefacts, and present a statistical method to identify sources that show transient brightness variations on ~2 hours timescales. We illustrate that by using the Gaia photometric CCD measurements, we can detect transient brightness variations down to an amplitude of 0.3 mag on timescales ranging from 15 seconds to several hours. We search an area of ~23.5 square degrees on the sky, and find four strong candidate fast transients. Two candidates are tentatively classified as flares on M-dwarf stars, while one is probably a flare on a giant star and one potentially a flare on a solar type star. These classifications are based on archival data and the timescales involved. We argue that the method presented here can be added to the existing Gaia Science Alerts infrastructure for the near real-time public dissemination of fast transient events.

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arXiv2017

Short timescale variables in the Gaia era: detection and characterization by structure function analysis

We investigate the capabilities of the ESA Gaia mission for detecting and character- izing short timescale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short timescale variability and estimating the underlying characteristic timescales from Gaia photometry, through extensive light-curve simulations for various periodic and transient short timescale variable types. We show that, with this approach, we can detect fast periodic variabil- ity, with amplitudes down to a few millimagnitudes, as well as some M dwarf flares and supernovae explosions, with limited contamination from longer timescale variables or constant sources. Timescale estimates from the variogram give valuable informa- tion on the rapidity of the underlying variation, which could complement timescale estimates from other methods, like Fourier-based periodograms, and be reinvested in preparation of ground-based photometric follow-up of short timescale candidates evi- denced by Gaia. The next step will be to find new short timescale variable candidates from real Gaia data, and to further characterize them using all the Gaia information, including color and spectrum.

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arXiv2017

Gaia's Cepheids and RR Lyrae Stars and Luminosity Calibrations Based on Tycho-Gaia Astrometric Solution

Gaia Data Release 1 contains parallaxes for more than 700 Galactic Cepheids and RR Lyrae stars, computed as part of the Tycho-Gaia Astrometric Solution (TGAS). We have used TGAS parallaxes, along with literature ($V, I, J, {K_\mathrm{s}}, W_1$) photometry and spectroscopy, to calibrate the zero point of the Period-Luminosity and Period-Wesenheit relations of classical and type II Cepheids, and the near-infrared Period-Luminosity, Period-Luminosity-Metallicity and optical Luminosity-Metallicity relations of RR Lyrae stars. In this contribution we briefly summarise results obtained by fitting these basic relations adopting different techniques that operate either in parallax or distance (absolute magnitude) space.

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arXiv2017

Pulsating star research and the Gaia revolution

In this article we present an overview of the ESA Gaia mission and of the unprecedented impact that Gaia will have on the field of variable star research. We summarise the contents and impact of the first Gaia data release on the description of variability phenomena, with particular emphasis on pulsating star research. The Tycho-Gaia astrometric solution, although limited to 2.1 million stars, has been used in many studies related to pulsating stars. Furthermore a set of 3,194 Cepheids and RR Lyrae stars with their times series have been released. Finally we present the plans for the ongoing study of variable phenomena with Gaia and highlight some of the possible impacts of the second data release on variable, and specifically, pulsating stars.

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arXiv2017

Learn from every mistake! Hierarchical information combination in astronomy

Throughout the processing and analysis of survey data, a ubiquitous issue nowadays is that we are spoilt for choice when we need to select a methodology for some of its steps. The alternative methods usually fail and excel in different data regions, and have various advantages and drawbacks, so a combination that unites the strengths of all while suppressing the weaknesses is desirable. We propose to use a two-level hierarchy of learners. Its first level consists of training and applying the possible base methods on the first part of a known set. At the second level, we feed the output probability distributions from all base methods to a second learner trained on the remaining known objects. Using classification of variable stars and photometric redshift estimation as examples, we show that the hierarchical combination is capable of achieving general improvement over averaging-type combination methods, correcting systematics present in all base methods, is easy to train and apply, and thus, it is a promising tool in the astronomical "Big Data" era.

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arXiv2017

Crossmatching variable objects with the Gaia data

Tens of millions of new variable objects are expected to be identified in over a billion time series from the Gaia mission. Crossmatching known variable sources with those from Gaia is crucial to incorporate current knowledge, understand how these objects appear in the Gaia data, train supervised classifiers to recognise known classes, and validate the results of the Variability Processing and Analysis Coordination Unit (CU7) within the Gaia Data Analysis and Processing Consortium (DPAC). The method employed by CU7 to crossmatch variables for the first Gaia data release includes a binary classifier to take into account positional uncertainties, proper motion, targeted variability signals, and artefacts present in the early calibration of the Gaia data. Crossmatching with a classifier makes it possible to automate all those decisions which are typically made during visual inspection. The classifier can be trained with objects characterized by a variety of attributes to ensure similarity in multiple dimensions (astrometry, photometry, time-series features), with no need for a-priori transformations to compare different photometric bands, or of predictive models of the motion of objects to compare positions. Other advantages as well as some disadvantages of the method are discussed. Implementation steps from the training to the assessment of the crossmatch classifier and selection of results are described.

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arXiv2016

Short timescale variables in stellar clusters: From Gaia to ground-based telescopes

Combined studies of variable stars and stellar clusters open great horizons, and they allow us to improve our understanding of stellar cluster formation and stellar evolution. In that prospect, the Gaia mission will provide astrometric, photometric, and spectroscopic data for about one billion stars of the Milky Way. This will represent a major census of stellar clusters, and it will drastically increase the number of known variable stars. In particular, the peculiar Gaia scanning law offers the opportunity to investigate the rather unexplored domain of short timescale variability (from tens of seconds to a dozen of hours), bringing invaluable clues to the fields of stellar physics and stellar aggregates. We assess the Gaia capabilities in terms of short timescale variability detection, using extensive light-curve simulations for various variable object types. We show that Gaia can detect periodic variability phenomena with amplitude variations larger than a few millimagnitudes. Additionally, we plan to perform subsequent follow-up of variables stars detected in clusters by Gaia to better characterize them. Hence, we develop a pipeline for the analysis of high cadence photometry from ground-based telescopes such as the 1.2m Euler telescope (La Silla, Chile) and the 1.2m Mercator telescope (La Palma, Canary Islands).

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arXiv2015

A comparative study of four significance measures for periodicity detection in astronomical surveys

We study the problem of periodicity detection in massive data sets of photometric or radial velocity time series, as presented by ESA's Gaia mission. Periodicity detection hinges on the estimation of the false alarm probability (FAP) of the extremum of the periodogram of the time series. We consider the problem of its estimation with two main issues in mind. First, for a given number of observations and signal-to-noise ratio, the rate of correct periodicity detections should be constant for all realized cadences of observations regardless of the observational time patterns, in order to avoid sky biases that are difficult to assess. Second, the computational loads should be kept feasible even for millions of time series. Using the Gaia case, we compare the $F^M$ method (Paltani 2004, Schwarzenberg-Czerny 2012), the Baluev method (Baluev 2008) and the GEV method (Süveges 2014), as well as a method for the direct estimation of a threshold. Three methods involve some unknown parameters, which are obtained by fitting a regression-type predictive model using easily obtainable covariates derived from observational time series. We conclude that the GEV and the Baluev methods both provide good solutions to the issues posed by a large-scale processing. The first of these yields the best scientific quality at the price of some moderately costly pre-processing. When this pre-processing is impossible for some reason (e.g. the computational costs are prohibitive or good regression models cannot be constructed), the Baluev method provides a computationally inexpensive alternative with slight biases in regions where time samplings exhibit strong aliases.

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arXiv2015

Revealing δ Cephei's Secret Companion and Intriguing Past

Classical Cepheid variable stars are crucial calibrators of the cosmic distance scale thanks to a relation between their pulsation periods and luminosities. Their archetype, δ Cephei, is an important calibrator for this relation. In this paper, we show that δ Cephei is a spectroscopic binary based on newly-obtained high-precision radial velocities. We combine these new data with literature data to determine the orbit, which has period 2201 days, semi-amplitude 1.5 km/s, and high eccentricity (e = 0.647). We re-analyze Hipparcos intermediate astrometric data to measure δ Cephei's parallax ($\varpi = 4.09 \pm 0.16$ mas) and find tentative evidence for an orbital signature, although we cannot claim detection. We estimate that Gaia will fully determine the astrometric orbit. Using the available information from spectroscopy, velocimetry, astrometry, and Geneva stellar evolution models ($M_{δCep} ~ 5.0 - 5.25 M_\odot$), we constrain the companion mass to within $0.2 < M_2 < 1.2 M_\odot$. We discuss the potential of ongoing and previous interactions between the companion and δ Cephei near pericenter passage, informing reported observations of circumstellar material and bow-shock. The orbit may have undergone significant changes due to a Kozai-Lidov mechanism driven by the outer (visual and astrometric) companion HD 213307. Our discovery of δ Cephei's nature as a spectroscopic binary exposes a hidden companion and reveals a rich and dynamical history of the archetype of classical Cepheid variables.

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arXiv2015

The Gaia Mission, Binary Stars and Exoplanets

On the 19th of December 2013, the Gaia spacecraft was successfully launched by a Soyuz rocket from French Guiana and started its amazing journey to map and characterise one billion celestial objects with its one billion pixel camera. In this presentation, we briefly review the general aims of the mission and describe what has happened since launch, including the Ecliptic Pole scanning mode. We also focus especially on binary stars, starting with some basic observational aspects, and then turning to the remarkable harvest that Gaia is expected to yield for these objects.

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arXiv2015

The variability processing and analysis of the Gaia mission

We present the variability processing and analysis that is foreseen for the Gaia mission within Coordination Unit 7 (CU7) of the Gaia Data Processing and Analysis Consortium (DPAC). A top level description of the tasks is given.

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arXiv2015

Automated eclipsing binary detection: applying the Gaia CU7 pipeline to Hipparcos

We demonstrate the eclipsing binary detection performance of the Gaia variability analysis and processing pipeline using Hipparcos data. The automated pipeline classifies 1,067 (0.9%) of the 118,204 Hipparcos sources as eclipsing binary candidates. The detection rate amounts to 89% (732 sources) in a subset of 819 visually confirmed eclipsing binaries, with the period correctly identified for 80% of them, and double or half periods obtained in 6% of the cases.

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arXiv2014

Time series data mining for the Gaia variability analysis

Gaia is an ESA cornerstone mission, which was successfully launched December 2013 and commenced operations in July 2014. Within the Gaia Data Processing and Analysis consortium, Coordination Unit 7 (CU7) is responsible for the variability analysis of over a billion celestial sources and nearly 4 billion associated time series (photometric, spectrophotometric, and spectroscopic), encoding information in over 800 billion observations during the 5 years of the mission, resulting in a petabyte scale analytical problem. In this article, we briefly describe the solutions we developed to address the challenges of time series variability analysis: from the structure for a distributed data-oriented scientific collaboration to architectural choices and specific components used. Our approach is based on Open Source components with a distributed, partitioned database as the core to handle incrementally: ingestion, distributed processing, analysis, results and export in a constrained time window.

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arXiv2014

Rotation and the Cepheid Mass Discrepancy

We recently showed that rotation significantly affects most observable Cepheid quantities, and that rotation, in combination with the evolutionary status of the star, can resolve the long-standing Cepheid mass discrepancy problem. We therefore provide a brief overview of our results regarding the problem of Cepheid masses. We also briefly mention the impact of rotation on the Cepheid period-luminosity(-color) relation, which is crucial for determining extragalactic distances, and thus for calibrating the Hubble constant.

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