Automated Classificationof X-ray Sources

R. J. Hanisch, A. A. Suchkov, R. L. WhiteSpace Telescope Science Institute

 T. A. McGlynn, E. L. Winter, M. F. Corcoran

NASA Goddard Space Flight Center 

W. VogesMax-Planck-Institute for Extraterrestrial Physics

Supported by NASA’s Applied Information Systems Research Program, Grant NAG5-11019

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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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USNOA2

DSS

ClassX Overview

ClassifierNetwork

Post ClassificationAnalysis andVerification

ClassifierTraining

Classifier specifica-tions and statisticsClassifier specifica-tions and statistics

Data Pipeline

WGACAT

RASS

GSC2

2MASSNVSS

FIRST

ChandraXMM

SDSS

Initially use small-coverage resources for verification.

Use existing high-coverage resources to get information on user sources.

1

2 3

HST

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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, …

X-ray, optical, IR, ...Training sets

WGACAT, ROSAT All Sky Survey, ...

ClassificationgranularityCoarse: Stellar vs. Extragalactic

Fine: A0 vs. B0…, AGN vs. QSO vs. galaxy

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ClassX Performance

• 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!

• Stellar and extragalactic sources are easily distinguished.

X-ray, opt.X-ray, opt., IR

Very few stars classifiedas extragalactic sources

Almost no extra-galactic sources classified as stars

Small amount ofconfusion among

different stellar types

Extragalactic sourceclassifications moreambiguous owing to

class overlap

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X-ray Stars in ρ Oph• 10X increase in

number of identified X-ray stars

• Dominance of late-type stars consistent with large pre-main-sequence 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 early-type 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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X-ray Binaries

• 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.

mx1 (soft x-ray magnitude)

X-r

ay h

ardn

ess

rati

o

Additional XRBs?

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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.

Knownsources

ClassXsources

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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/