- ID:
- ivo://CDS.VizieR/J/ApJ/756/27
- Title:
- Classification of sources from the 2XMMi-DR3 cat.
- Short Name:
- J/ApJ/756/27
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- We carry out classification of 4330 X-ray sources in the 2XMMi-DR3 catalog. They are selected under the requirement of being a point source with multiple XMM-Newton observations and at least one detection with the signal-to-noise ratio larger than 20. For about one-third of them we are able to obtain reliable source types from the literature. They mostly correspond to various types of stars (611), active galactic nuclei (AGNs, 753), and compact object systems (138) containing white dwarfs, neutron stars, and stellar-mass black holes. We find that about 99% of stars can be separated from other source types based on their low X-ray-to-IR flux ratios and frequent X-ray flares. AGNs have remarkably similar X-ray spectra, with the power-law photon index centered around 1.91+/-0.31, and their 0.2-4.5keV flux long-term variation factors have a median of 1.48, with 98.5% being less than 10. In contrast, 70% of compact object systems can be very soft or hard, highly variable in X-rays, and/or have very large X-ray-to-IR flux ratios, separating them from AGNs. Using these results, we derive a source type classification scheme to classify the other sources and find 644 candidate stars, 1376 candidate AGNs, and 202 candidate compact object systems, whose false identification probabilities are estimated to be about 1%, 3%, and 18%, respectively. There are still 320 sources associated with nearby galaxies and 151 in the Galactic plane, which we expect to be mostly compact object systems or background AGNs. We also have 100 candidate ultraluminous X-ray sources. They are found to be much less variable than other accreting compact objects.
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Search Results
- ID:
- ivo://CDS.VizieR/J/A+A/566/A50
- Title:
- Classification of stellar spectra 644-681nm
- Short Name:
- J/A+A/566/A50
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- We present a study of spectral diagnostics available from optical spectra with R=17000 obtained with the VLT/Giraffe HR15n setup, using observations from the Gaia-ESO Survey, on the {gamma} Vel young cluster, with the purpose of classifying these stars and finding their fundamental parameters. We define several spectroscopic indices, sampling the amplitude of TiO bands, the H{alpha} line core and wings, and temperature- and gravity-sensitive sets of lines, each useful as a Teff or logg indicator over a limited range of stellar spectral types. H{alpha} line indices are also useful as chromospheric activity or accretion indicators. Furthermore, we use all indices to define additional global Teff- and logg-sensitive indices {tau} and {gamma}, valid for the entire range of types in the observed sample.
- ID:
- ivo://CDS.VizieR/J/A+A/657/A138
- Title:
- Classification of Swift and XMM-Newton sources
- Short Name:
- J/A+A/657/A138
- Date:
- 22 Feb 2022
- Publisher:
- CDS
- Description:
- With the advent of very large X-ray surveys, an automated classification of X-ray sources becomes increasingly valuable. This work proposes a revisited naive Bayes classification of the X-ray sources in the Swift-XRT and XMM- Newton catalogs into four classes - AGN, stars, X-ray binaries (XRBs), and cataclysmic variables (CVs) - based on their spatial, spectral, and timing properties and their multiwavelength counterparts. An outlier measure is used to identify objects of other natures. The classifier is optimized to maximize the classification performance of a chosen class (here XRBs), and it is adapted to data mining purposes. We augmented the X-ray catalogs with multiwavelength data, source class, and variability properties. We then built a reference sample of about 25000 X-ray sources of known nature. From this sample, the distribution of each property was carefully estimated and taken as reference to assign probabilities of belonging to each class. The classification was then performed on the whole catalog, combining the information from each property. Using the algorithm on the Swift reference sample, we retrieved 99%, 98%, 92%, and 34% of AGN, stars, XRBs, and CVs, respectively, and the false positive rates are 3%, 1%, 9%, and 15%. Similar results are obtained on XMM sources. When applied to a carefully selected test sample, representing 55% of the X-ray catalog, the classification gives consistent results in terms of distributions of source properties. A substantial fraction of sources not belonging to any class is efficiently retrieved using the outlier measure, as well as AGN and stars with properties deviating from the bulk of their class. Our algorithm is then compared to a random forest method; the two showed similar performances, but the algorithm presented in this paper improved insight into the grounds of each classification. This robust classification method can be tailored to include additional or different source classes and can be applied to other X-ray catalogs. The transparency of the classification compared to other methods makes it a useful tool in the search for homogeneous populations or rare source types, including multi-messenger events. Such a tool will be increasingly valuable with the development of surveys of unprecedented size, such as LSST, SKA, and Athena, and the search for counterparts of multi-messenger events.
- ID:
- ivo://CDS.VizieR/J/MNRAS/414/1617
- Title:
- Classification of type Ia supernovae
- Short Name:
- J/MNRAS/414/1617
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- Type Ia supernovae (SNe Ia) spectra are compared using the coefficient of the largest wavelet scale in their decomposition. Two distinct subgroups have been identified, and their occurrence is discussed with regards to the use of SNe Ia as cosmological probes. Apart from the group of normal SNe, another trend characterized by intrinsically redder colours consists of many different SN events, which exhibit diverse properties. These include the interaction with the circumstellar material and the existence of a specific shell structure in or surrounding the SN ejecta or super-Chandrasekhar mass progenitors. Compared with normal objects, these SNe may violate the standard width-luminosity correction. This could influence the cosmological results if these are all calibrated equally, as their fraction among SNe Ia is not negligible when performing precision cosmology. Using the largest wavelet scale coefficient in combination with long-baseline B-I colours, we show how to disentangle the SN intrinsic colour from the part that corresponds to the reddening as a result of dust extinction in the host galaxy in the SALT2 colour parameter c.
- ID:
- ivo://CDS.VizieR/J/A+A/403/659
- Title:
- Classification of WR planetary nebulae
- Short Name:
- J/A+A/403/659
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- We analyse 42 emission-line nuclei of Planetary Nebulae (PNe), in the framework of a large spectrophotometric survey of [WC] nuclei of PNe conducted since 1994, using low/medium resolution spectra obtained at ESO and at OHP. We construct a grid of selected line-intensities (normalized to C IV-5806{AA}=100) ordered by decreasing ionisation potential going from 871 to 24eV. In this grid, the stars appear to belong clearly to prominent O (hot [WO1-4] types) or C (cooler [WC4-11] types) line-sequences, in agreement with the classification of massive WR stars applied to Central Stars of Planetary Nebulae (CSPNe) by Crowther et al. (1998MNRAS.296..367C, CMB98). We propose 20 selected line ratios and the FWHM of CIV and CIII lines as classification diagnostics, which agree well with the 7 line ratios and the FWHM proposed by CMB98.
- ID:
- ivo://CDS.VizieR/J/ApJ/786/20
- Title:
- Classification of 2XMM variable sources
- Short Name:
- J/ApJ/786/20
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ~97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7-500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.
- ID:
- ivo://CDS.VizieR/J/ApJ/887/18
- Title:
- Classification of X-ray counterparts of 3FGL sources
- Short Name:
- J/ApJ/887/18
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- Approximately one-third of the gamma-ray sources in the third Fermi-LAT catalog are unidentified or unassociated with objects at other wavelengths. Observations with the X-Ray Telescope on the Neil Gehrels Swift Observatory (Swift-XRT) have yielded possible counterparts in ~30% of these source regions. The objective of this work is to identify the nature of these possible counterparts, utilizing their gamma-ray properties coupled with the Swift derived X-ray properties. The majority of the known sources in the Fermi catalogs are blazars, which constitute the bulk of the extragalactic gamma-ray source population. The galactic population on the other hand is dominated by pulsars. Overall, these two categories constitute the majority of all gamma-ray objects. Blazars and pulsars occupy different parameter space when X-ray fluxes are compared with various gamma-ray properties. In this work, we utilize the X-ray observations performed with the Swift-XRT for the unknown Fermi sources and compare their X-ray and gamma-ray properties to differentiate between the two source classes. We employ two machine-learning algorithms, decision tree and random forest (RF) classifier, to our high signal-to-noise ratio sample of 217 sources, each of which corresponds to Fermi unassociated regions. The accuracy scores for both methods were found to be 97% and 99%, respectively. The RF classifier, which is based on the application of a multitude of decision trees, associated a probability value (P_bzr_) for each source to be a blazar. This yielded 173 blazar candidates from this source sample, with P_bzr_>=90% for each of these sources, and 134 of these possible blazar source associations had P_bzr_>=99%. The results yielded 13 sources with P_bzr_<=10%, which we deemed as reasonable candidates for pulsars, seven of which result with P_bzr_<=1%. There were 31 sources that exhibited intermediate probabilities and were termed ambiguous due to their unclear characterization as a pulsar or a blazar.
- ID:
- ivo://CDS.VizieR/J/ApJ/805/181
- Title:
- Classification of 1.5<=z<=3 HUDF galaxies
- Short Name:
- J/ApJ/805/181
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- At z>~1, the distinction between merging and "normal" star-forming galaxies based on single band morphology is often hampered by the presence of large clumps which result in a disturbed, merger-like appearance even in rotationally supported disks. In this paper we discuss how a classification based on canonical, non-parametric structural indices measured on resolved stellar mass maps, rather than on single-band images, reduces the misclassification of clumpy but not merging galaxies. We calibrate the mass-based selection of mergers using the MIRAGE hydrodynamical numerical simulations of isolated and merging galaxies which span a stellar mass range of 10^9.8^-10^10.6^M_{sun}_ and merger ratios between 1:1-1:6.3. These simulations are processed to reproduce the typical depth and spatial resolution of observed Hubble Ultra Deep Field (HUDF) data. We test our approach on a sample of real z~=2 galaxies with kinematic classification into disks or mergers and on ~100 galaxies in the HUDF field with photometric/spectroscopic redshift between 1.5<=z<=3 and M>10^9.4^M_{sun}_. We find that a combination of the asymmetry A_MASS_ and M_20,MASS_ indices measured on the stellar mass maps can efficiently identify real (major) mergers with <~20% contamination from clumpy disks in the merger sample. This mass-based classification cannot be reproduced in star-forming galaxies by H-band measurements alone, which instead result in a contamination from clumpy galaxies which can be as high as 50%. Moreover, we find that the mass-based classification always results in a lower contamination from clumpy galaxies than an H-band classification, regardless of the depth of the imaging used (e.g., CANDELS versus HUDF).
- ID:
- ivo://CDS.VizieR/J/other/Sci/340.170
- Title:
- Classifications of 188 SNe Ia
- Short Name:
- J/other/Sci/340.
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- Type Ia supernovae (SNe Ia) have been used as excellent standardizable candles for measuring cosmic expansion, but their progenitors are still elusive. Here, we report that the spectral diversity of SNe Ia is tied to their birthplace environments. We found that those with high-velocity ejecta are substantially more concentrated in the inner and brighter regions of their host galaxies than are normal-velocity SNe Ia. Furthermore, the former tend to inhabit larger and more luminous hosts. These results suggest that high-velocity SNe Ia likely originate from relatively younger and more metal-rich progenitors than do normal-velocity SNe Ia and are restricted to galaxies with substantial chemical evolution.
- ID:
- ivo://CDS.VizieR/J/PASP/115/1280
- Title:
- Classifications of SN host galaxies
- Short Name:
- J/PASP/115/1280
- Date:
- 21 Oct 2021
- Publisher:
- CDS
- Description:
- Classifications on the DDO system are given for an additional 231 host galaxies of supernovae that have been discovered during the course of the Lick Observatory Supernova Search with the Katzman Automatic Imaging Telescope (KAIT). This brings the total number of hosts of supernovae (SNe) discovered (or independently rediscovered) by KAIT, which have so far been classified on a homogeneous system, to 408.
