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Tominaga, Nozomu (ORCID:0000000185373153)

Publications and source records attributed to Tominaga, Nozomu (ORCID:0000000185373153).

Optical follow-up observation for GW event S190510g using Subaru/Hyper Suprime-Cam

Abstract A gravitational wave event, S190510g, which was classified as a binary-neutron-star coalescence at the time of preliminary alert, was detected by LIGO/Virgo collaboration on 2019 May 10. At 1.7 hours after the issue of its preliminary alert, we started a target-of-opportunity imaging observation in the Y band to search for its optical counterpart using the Hyper Suprime-Cam (HSC) on the Subaru Telescope. The observation covers a 118.8 deg2 sky area corresponding to $11.6\%$ confidence in the localization skymap released in the preliminary alert and $1.2\%$ in the updated skymap. We divided the observed area into two fields based on the availability of HSC reference images. For the fields with the HSC reference images, we applied an image subtraction technique; for the fields without the HSC reference images, we sought individual HSC images by matching a catalog of observed objects with the PS1 catalog. The search depth is 22.28 mag in the former method and the limit of search depth is 21.3 mag in the latter method. Subsequently, we performed visual inspection and obtained 83 candidates using the former method and 50 candidates using the latter method. Since we only have the one-day photometric data, we evaluated the probability of candidates being located inside the 3D skymap by estimating their distances with photometry of associated extended objects. We found three candidates are likely located inside the 3D skymap and concluded they could be a counterpart of S190510g, while most of the 133 candidates were likely to be supernovae because the number density of candidates was consistent with the expected number of supernova detections. By comparing our observational depth with a light-curve model of such a kilonova reproducing AT2017gfo, we show that early deep observations with the Subaru/HSC can capture the rising phase of the blue component of a kilonova at the estimated distance of S190510g (∼230 Mpc).

79 ASTRONOMY AND ASTROPHYSICS↗

Follow-up observations for IceCube-170922A: Detection of rapid near-infrared variability and intensive monitoring of TXS 0506+056

Abstract We present our follow-up observations to search for an electromagnetic counterpart of the IceCube high-energy neutrino IceCube-170922A. Monitoring observations of a likely counterpart, TXS 0506+056, are also described. First, we quickly took optical and near-infrared images of seven flat-spectrum radio sources within the IceCube error region right after the neutrino detection and found a rapid flux decline of TXS 0506+056 in Kanata/HONIR J-band data. Motivated by this discovery, intensive follow-up observations of TXS 0506+056 were continuously performed, including our monitoring imaging observations, spectroscopic observations, and polarimetric observations in optical and near-infrared wavelengths. TXS 0506+056 showed a large-amplitude (∼1.0 mag) variability in a time scale of several days or longer, although no significant variability was detected in a time scale of a day or shorter. TXS 0506+056 also showed a bluer-when-brighter trend in optical and near-infrared wavelengths. Structure functions of the variabilities were examined and indicate that TXS 0506+056 is not a special blazar in terms of optical variability. Polarization measurement results of TXS 0506+056 are also discussed.

(galaxies:) BL Lacertae objects: general↗

Photometric classification of Hyper Suprime-Cam transients using machine learning

Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.

Takahashi, Ichiro↗

Spatially resolved molecular gas properties of host galaxy of Type I superluminous supernova SN 2017egm

Abstract We present the results of CO(1–0) observations of the host galaxy of a Type I superluminous supernova (SLSN-I), SN 2017egm, one of the closest SLSNe-I at z = 0.03063, by using the Atacama Large Millimeter/submillimeter Array. The molecular gas mass of the host galaxy is Mgas = (4.8 ± 0.3) × 109 M⊙, placing it on the sequence of normal star-forming galaxies in an Mgas–star-formation rate (SFR) plane. The molecular hydrogen column density at the location of SN 2017egm is higher than that of the Type II SN PTF10bgl, which is also located in the same host galaxy, and those of other Type II and Ia SNe located in different galaxies, suggesting that SLSNe-I have a preference for a dense molecular gas environment. On the other hand, the column density at the location of SN 2017egm is comparable to those of Type Ibc SNe. The surface densities of molecular gas and the SFR at the location of SN 2017egm are consistent with those of spatially resolved local star-forming galaxies and follow the Schmidt–Kennicutt relation. These facts suggest that SLSNe-I can occur in environments with the same star-formation mechanism as in normal star-forming galaxies.

Hatsukade, Bunyo (ORCID:0000000164698725)↗