arXiv subjects

Berry Holl

Publications and source records attributed to Berry Holl.

28 records · Page 2Linked to original sources

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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arXiv2015

Revealing the Nature of Extreme Coronal-line Emitter SDSS J095209.56+214313.3

Extreme coronal-line emitter (ECLE) SDSSJ095209.56+214313.3, known by its strong, fading, high ionization lines, has been a long standing candidate for a tidal disruption event, however a supernova origin has not yet been ruled out. Here we add several new pieces of information to the puzzle of the nature of the transient that powered its variable coronal lines: 1) an optical light curve from the Lincoln Near Earth Asteroid Research (LINEAR) survey that serendipitously catches the optical flare, and 2) late-time observations of the host galaxy with the Swift Ultraviolet and Optical Telescope (UVOT) and X-ray telescope (XRT) and the ground-based Mercator telescope. The well-sampled, $\sim10$-year long, unfiltered LINEAR light curve constrains the onset of the flare to a precision of $\pm5$ days and enables us to place a lower limit on the peak optical magnitude. Difference imaging allows us to estimate the location of the flare in proximity of the host galaxy core. Comparison of the \textsl{GALEX} data (early 2006) with the recently acquired Swift UVOT (June 2015) and Mercator observations (April 2015) demonstrate a decrease in the UV flux over a $\sim 10$ year period, confirming that the flare was UV-bright. The long-lived UV-bright emission, detected 1.8 rest-frame years after the start of the flare, strongly disfavors a SN origin. These new data allow us to conclude that the flare was indeed powered by the tidal disruption of a star by a supermassive black hole and that TDEs are in fact capable of powering the enigmatic class of ECLEs.

astro-ph.GA↗

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.

astro-ph.IM↗

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.

astro-ph.IM↗

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.

astro-ph.IM↗

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.

astro-ph.IM↗

arXiv2011

A conjugate gradient algorithm for the astrometric core solution of Gaia

The ESA space astrometry mission Gaia, planned to be launched in 2013, has been designed to make angular measurements on a global scale with micro-arcsecond accuracy. A key component of the data processing for Gaia is the astrometric core solution, which must implement an efficient and accurate numerical algorithm to solve the resulting, extremely large least-squares problem. The Astrometric Global Iterative Solution (AGIS) is a framework that allows to implement a range of different iterative solution schemes suitable for a scanning astrometric satellite. In order to find a computationally efficient and numerically accurate iteration scheme for the astrometric solution, compatible with the AGIS framework, we study an adaptation of the classical conjugate gradient (CG) algorithm, and compare it to the so-called simple iteration (SI) scheme that was previously known to converge for this problem, although very slowly. The different schemes are implemented within a software test bed for AGIS known as AGISLab, which allows to define, simulate and study scaled astrometric core solutions. After successful testing in AGISLab, the CG scheme has been implemented also in AGIS. The two algorithms CG and SI eventually converge to identical solutions, to within the numerical noise (of the order of 0.00001 micro-arcsec). These solutions are independent of the starting values (initial star catalogue), and we conclude that they are equivalent to a rigorous least-squares estimation of the astrometric parameters. The CG scheme converges up to a factor four faster than SI in the tested cases, and in particular spatially correlated truncation errors are much more efficiently damped out with the CG scheme.

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arXiv2011

The impact of CCD radiation damage on Gaia astrometry: I. Image location estimation in the presence of radiation damage

The Gaia mission has been designed to perform absolute astrometric measurements with unprecedented accuracy; the end-of-mission parallax standard error is required to be 30 micro-arcseconds for a G2V type star of magnitude 15. These requirements set a stringent constraint on the accuracy of the estimation of the location of the stellar image on the CCD for each observation: e.g., 0.3 milli-arseconds (mas) or 0.005 pixels for the same V=15 G2V star. However the Gaia CCDs will suffer from charge transfer inefficiency (CTI) caused by radiation damage that will degrade the stellar image quality and may degrade the astrometric performance of Gaia if not properly addressed. For the first time at this level of detail, the potential impact of radiation damage on the performance of Gaia is investigated. In this first paper we focus on the evaluation of the CTI impact on the image location accuracy. We show that CTI decreases the stellar image signal-to-noise ratio and irreversibly degrades the image location estimation precision. As a consequence the location estimation standard errors increase by up to 6% for a radiation damage level equivalent to the end-of-mission. In addition the CTI-induced image distortion introduces a systematic bias in the image location estimation (up to 0.05 pixels or 3 mas in the Gaia operating conditions). We present a novel approach to CTI mitigation that enables, without correction of the raw data, the unbiased estimation of the image location and flux from damaged observations. Its implementation reduces the maximum measured location bias for the faintest magnitude to 0.005 pixels (~4e-4 pixels at magnitude 15). In a second paper we will investigate how the CTI effects affect the final astrometric accuracy of Gaia by propagating residual errors through the astrometric solution.

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