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Automated Classification
of X-ray Sources
R. J. Hanisch, A. A. Suchkov, R. L. White
Space Telescope Science Institute
T. A. McGlynn, E. L. Winter, M. F. Corcoran
NASA Goddard Space Flight Center
W. Voges
Max-Planck-Institute for Extraterrestrial Physics
Supported by NASA’s Applied Information Systems Research Program, Grant NAG5-11019
ClassX
• ClassX is a Virtual Observatory prototype project
aimed at the semi-automated classification of
unidentified X-ray sources.
• ClassX draws from numerous on-line object catalogs
using VO standard protocols (“cone search”,
VOTable) to collect multi-wavelength position, flux,
and source extent information.
• ClassX uses these data to train oblique decision tree
classifiers, and then apply the classifiers to
unidentified X-ray sources.
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ClassX Overview
Use existing highcoverage resources
to get information on
user sources.
Classifier
Training
Initially use smallcoverage resources
for verification.
WGACAT
SDSS
1
RASS
Classifier
Classifier specificaspecifications
tions and
and statistics
statistics
HST
USNOA2
DSS
GSC2
2MASS
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Data
Pipeline
2
Classifier
Network
Post Classification
Analysis and
3 Verification
Chandra
XMM
NVSS
FIRST
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What Kind of Classifier?
Classifiers can be distinguished
along several orthogonal
dimensions. Exploring all the
dimensions is hard.
Different tasks may require
different classifiers.
Classifier algorithm
Decision trees, oblique or
otherwise
Neural networks
Nearest neighbor
Observed quantities
Fluxes, positions, colors,
variability, spatial extent, …
Training sets
WGACAT, ROSAT All
Sky Survey, ...
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Classification
granularity
X-ray, optical, IR, ...
Coarse: Stellar vs. Extragalactic
Fine: A0 vs. B0…, AGN vs. QSO vs. galaxy
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ClassX Performance
X-ray, opt.
X-ray, opt., IR
Small amount of
confusion among
different stellar types
Almost no extragalactic sources
classified as stars
• Every output class needs
substantial representation in
the training set.
• Overlap between classes
should be minimized.
• Classifier accuracy can be
improved with additional
information (i.e., flux in
different bandpass), but not
always!
Very few stars classified
as extragalactic sources
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Extragalactic source
classifications more
ambiguous owing to
class overlap
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• Stellar and extragalactic
sources are easily
distinguished.
5
X-ray Stars in ρ Oph
•
•
•
10X increase in
number of
identified X-ray
stars
Dominance of
late-type stars
consistent with
large pre-mainsequence
population in
active star
formation region
 T Tauri-type
stars
Adds many new
T Tauri candidates
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X-ray Stars in the LMC
•
•
•
10X increase in
number of
identified earlytype stars
Dominance of
early-type stars is
consistent with
expectations for
stars at distance
of LMC
Many late-type
X-ray stars
suggest large
population of PMS
T Tauri stars in
LMC star
formation regions
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Additional XRBs?
X-ray hardness ratio
X-ray Binaries
mx1 (soft x-ray magnitude)
•
•
WGACAT “stars” (type unknown) re-classified; most are indeed stars,
most in direction of LMC/SMC
53 new XRB candidates; 50% increase in number known in WGACAT.
These are mostly high-mass XRB candidates with bright optical
counterparts.
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Quasars and AGN
•
•
•
Nearly 20X increase in number of
QSO candidates, 3X increase in
number of AGNs. ClassX
differentiates reasonably well
between QSOs and AGN.
In contrast to QSO/AGN objects
known in WGACAT, where
dominant class is AGN, objects
identified by ClassX are strongly
dominated by QSOs. On average
are much fainter in the X-rays, by
more than 1 mag; also
substantially redder in the optical.
Of ClassX-classified QSOs in
region of SDSS EDR, 60% are
confirmed.
Known
sources
ClassX
sources
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Summary
• Core technology of ClassX in place and working
effectively.
• Suite of classifiers developed.
• Initial results in areas of stellar X-ray sources…
– Pre-main-sequence stars, T Tauri stars readily identified in
galactic star formation regions
– Large increase in numbers of both early- and late-type X-ray
stars in LMC
– 50% increase in number of candidate X-ray binaries
• …and quasars/AGN
– Identifying faint, high-redshift QSOs
• Pursuing further validation, e.g., through SDSS, HST,
and Chandra observations
http://heasarc.gsfc.nasa.gov/classx/
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