Gravitational waves from an SMBH binary in M87

In this paper, we study gravitational-wave (GW) emission from a hypothetical supermassive black-hole (SMBH) binary at the center of M87. The existence of a SMBH other than that usually identified with the central AGN is a possible explanation for the observed displacement ($\sim O(1)~{\rm pc}$) between the AGN and the galactic centroid, and it is reasonable to assume consid- ering the evolution of SMBHs through galaxy mergers. Because the period of the binary and the resulting GWs is much longer than the observational time span, we calculate the variation of the GW amplitude, rather than the amplitude itself. We investigate the dependence on the orbital elements and the second BH mass taking the observational constraints into account. The frequency of the GWs is too low to be detected with the conventional pulsar timing array and we propose a new method to detect such low-frequency GWs with the distribution func- tion of pulsar spin-down rates. Although the GWs from a SMBH binary which explains the observed displacement is extremely hard to be detected even with the new method, GWs are still a useful way to probe the M87 center.Comment: 5 pages, 6 figures. Accepted for Publications of the Astronomical Society of Japa

Artificial neural networks for selection of pulsar candidates from the radio continuum surveys

Pulsar search with time-domain observation is very computationally expensive and data volume will be enormous with the next generation telescopes such as the Square Kilometre Array. We apply artificial neural networks (ANNs), a machine learning method, for efficient selection of pulsar candidates from radio continuum surveys, which are much cheaper than time-domain observation. With observed quantities such as radio fluxes, sky position and compactness as inputs, our ANNs output the "score" that indicates the degree of likeliness of an object to be a pulsar. We demonstrate ANNs based on existing survey data by the TIFR GMRT Sky Survey (TGSS) and the NRAO VLA Sky Survey (NVSS) and test their performance. Precision, which is the ratio of the number of pulsars classified correctly as pulsars to that of any objects classified as pulsars, is about 96$\%$. Finally, we apply the trained ANNs to unidentified radio sources and our fiducial ANN with five inputs (the galactic longitude and latitude, the TGSS and NVSS fluxes and compactness) generates 2,436 pulsar candidates from 456,866 unidentified radio sources. These candidates need to be confirmed if they are truly pulsars by time-domain observations. More information such as polarization will narrow the candidates down further.Comment: 11 pages, 13 figures, 3 tables, accepted for publication in MNRA