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2921. Classification of type Ia supernovae
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.
2922. Classification of WR planetary nebulae
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.
2923. Classification of 2XMM variable sources
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.
2924. Classification of X-ray counterparts of 3FGL sources
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.
2925. Classification of 1.5<=z<=3 HUDF galaxies
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).
2926. Classifications of 188 SNe Ia
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.
2927. Classifications of SN host galaxies
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.
2928. Classifications of SN host galaxies. III
ID:
ivo://CDS.VizieR/J/PASP/117/773
Title:
Classifications of SN host galaxies. III
Short Name:
J/PASP/117/773
Date:
21 Oct 2021
Publisher:
CDS
Description:
A homogeneous sample comprising host galaxies of 604 recent supernovae, including 212 objects discovered primarily in 2003 and 2004, has been classified on the David Dunlap Observatory system.
2929. Classifiers for star/galaxy separation
ID:
ivo://CDS.VizieR/J/AJ/141/189
Title:
Classifiers for star/galaxy separation
Short Name:
J/AJ/141/189
Date:
21 Oct 2021
Publisher:
CDS
Description:
We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function.
2930. Classifying 3FGL with ANN
ID:
ivo://CDS.VizieR/J/MNRAS/470/1291
Title:
Classifying 3FGL with ANN
Short Name:
J/MNRAS/470/1291
Date:
21 Oct 2021
Publisher:
CDS
Description:
In its first four years of operation, the Fermi-Large Area Telescope (LAT) detected 3033 {gamma}-ray emitting sources. In the Fermi-LAT Third Source Catalogue (3FGL) about 50 per cent of the sources have no clear association with a likely {gamma}-ray emitter. We use an artificial neural network algorithm aimed at distinguishing BL Lacs from FSRQs to investigate the source subclass of 559 3FGL unassociated sources characterized by {gamma}-ray properties very similar to those of active galactic nuclei. Based on our method, we can classify 271 objects as BL Lac candidates, 185 as FSRQ candidates, leaving only 103 without a clear classification. We suggest a new zoo for {gamma}-ray objects, where the percentage of sources of uncertain type drops from 52 per cent to less than 10 per cent. The result of this study opens up new considerations on the population of the {gamma}-ray sky, and it will facilitate the planning of significant samples for rigorous analyses and multiwavelength observational campaigns.

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