J/MNRAS/456/2260 K2 Variability Catalogue II (Armstrong+, 2016)
K2 Variable Catalogue.
II: Machine learning classification of variable stars and eclipsing binaries
in K2 fields 0-4.
Armstrong D.J., Kirk J., Lam K.W.F., McCormac J., Osborn H.P., Spake J.,
Walker S., Brown D.J.A., Kristiansen M.H., Pollacco D., West R.,
Wheatley P.J.
<Mon. Not. R. Astron. Soc. 456, 2260 (2016)>
=2016MNRAS.456.2260A 2016MNRAS.456.2260A (SIMBAD/NED BibCode)
ADC_Keywords: Stars, variable ; Binaries, eclipsing
Keywords: methods: data analysis - techniques: photometric - catalogues -
binaries: eclipsing - stars: variable: general
Abstract:
We are entering an era of unprecedented quantities of data from
current and planned survey telescopes. To maximize the potential of
such surveys, automated data analysis techniques are required. Here we
implement a new methodology for variable star classification, through
the combination of Kohonen Self-Organizing Maps (SOMs, an unsupervised
machine learning algorithm) and the more common Random Forest (RF)
supervised machine learning technique. We apply this method to data
from the K2 mission fields 0-4, finding 154 ab-type RR Lyraes (10
newly discovered), 377 δ Scuti pulsators, 133 γ Doradus
pulsators, 183 detached eclipsing binaries, 290 semidetached or
contact eclipsing binaries and 9399 other periodic (mostly
spot-modulated) sources, once class significance cuts are taken into
account. We present light-curve features for all K2 stellar targets,
including their three strongest detected frequencies, which can be
used to study stellar rotation periods where the observed variability
arises from spot modulation. The resulting catalogue of variable
stars, classes, and associated data features are made available
online. We publish our SOM code in python as part of the open source
pymvpa package, which in combination with already available RF modules
can be easily used to recreate the method.
Description:
Data are taken from the K2 satellite (Howell et al.,
2014PASP..126..398H 2014PASP..126..398H). K2 is the repurposed Kepler mission, and
provides light-curve flux measurements at a 30min 'long' cadence
continuously for 80d per target. Targets are organized into
campaigns, with each campaign spanning an ∼80d period and covering
several thousand objects. A much smaller number of targets (a few tens
per campaign) are available at the 'short' cadence of ∼1min.
For the purposes of this work, we restrict ourselves to long cadence
data only, to preserve uniformity in the data.
Complete catalogue and data feature files.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table4.dat 90 68910 Catalogue, Campaigns 0-4, Warwick lightcurves
table5.dat 136 68910 Data Features, Campaigns 0-4, Warwick lightcurves
table6.dat 90 29591 Catalogue, Campaigns 3-4, PDC lightcurves
table7.dat 136 29591 Data Features, Campaigns 3-4, PDC lightcurves
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See also:
J/A+A/579/A19 : K2 Variable Catalogue (Armstrong+, 2015)
http://deneb.astro.warwick.ac.uk/phrlbj/k2varcat/ : K2VarCat home page
Byte-by-byte Description of file: table4.dat table6.dat
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Bytes Format Units Label Explanations
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1- 9 I9 --- ID EPIC ID
11 I1 --- Campaign [0/4] K2 Campaign when observed
13- 18 A6 --- Class Variability Class with Maximum Probability
20- 27 F8.6 --- PDSCUT Delta Scuti Class Probability
29- 36 F8.6 --- PEA Detached Eclipsing Binary Class Probability
38- 45 F8.6 --- PEB Non-Detached Eclipsing Binary Class Probability
47- 54 F8.6 --- PGDOR Gamma Doradus Class Probability
56- 63 F8.6 --- PNoise Noise Class Probability
65- 72 F8.6 --- POTHPER Other Periodic Variable Class Probability
74- 81 F8.6 --- PRRab RR Lyrae ab Type Class Probability
83- 90 F8.6 --- Anomaly Anomaly Score for Object
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Byte-by-byte Description of file: table5.dat table7.dat
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Bytes Format Units Label Explanations
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1- 9 I9 --- ID EPIC ID
11 I1 --- Campaign [0/4] K2 Campaign when observed
13- 16 I4 --- SOMIndex Location on Self-Organising-Map
18- 26 F9.6 d Per1 Dominant Lomb Scargle Period
28- 36 F9.6 d Per2 Second Lomb Scargle Period
38- 46 F9.6 d Per3 Third Lomb Scargle Period
48- 55 F8.6 --- SOMDist Distance to closest SOM pixel
57- 64 F8.6 --- php2pmean Mean point-to-point scatter in phase
66- 73 F8.6 --- php2pmax Max point-to-point scatter in phase
75- 83 F9.6 --- Amplitude Max-Min of phase curve
85- 92 F8.6 --- Ampratio21 Period 2 to period amplitude ratio
94-101 F8.6 --- Ampratio31 Period 3 to period amplitude ratio
103-111 F9.6 --- p2pmean Mean point-to-point scatter
113-122 F10.6 --- p2p98perc 98th percentile of point-to-point scatter
124-136 F13.6 --- stdoverr Flux standard deviation over mean error
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Acknowledgements:
David Armstrong, d.j.armstrong(at)warwick.ac.uk
References:
Armstrong et al., Paper I 2015A&A...579A..19A 2015A&A...579A..19A, Cat. J/A+A/579/A19
(End) Patricia Vannier [CDS] 02-Dec-2015