arXiv subjects

Shun Yamamoto

Publications and source records attributed to Shun Yamamoto.

4 recordsLinked to original sources

arXiv2025

Can we hear beats with pulsar timing arrays?

An isolated supermassive black hole binary (SMBHB) produces an identical cross-correlation pattern of pulsar timings as an isotropic stochastic background gravitational waves (GWs) generated possibly by inflation. Can there remain the identical cross-correlation pattern in the presence of a secondary SMBHB? To address this issue, the present paper focuses on GWs with similar amplitudes but slightly different frequencies $f_1$ and $f_2$ coming from two different directions. Beats between the two GWs can modify angular correlation patterns. The beat-induced correlation patterns are not stationary but modulated with a beat frequency $f_{beat} \equiv |f_1 - f_2|$. We obtain an analytic solution that allows us to infer $f_{beat}$ from the modulated angular correlations.

gr-qc↗

arXiv2023

Hemisphere-averaged Hellings-Downs curve between pulsar pairs for a gravitational wave source

The Hellings-Downs (HD) curve plays a crucial role in search for nano-hertz gravitational waves (GWs) with pulsar timing arrays. We discuss the angular pattern of correlations for pulsar pairs within a celestial hemisphere. The hemisphere-averaged correlation curve depends upon the sky location of a GW compact source like a binary of supermassive black holes. If a single source is dominant, the variation in the hemisphere-averaged angular correlation is greatest when the hemisphere has its North Pole at the sky location of the GW source. Possible GW amplitude and source distance relevant to the current PTAs by using the hemisphere-averaged correlation are also studied.

gr-qc↗

arXiv2019

Repeated Multimarket Contact with Private Monitoring: A Belief-Free Approach

This paper studies repeated games where two players play multiple duopolistic games simultaneously (multimarket contact). A key assumption is that each player receives a noisy and private signal about the other's actions (private monitoring or observation errors). There has been no game-theoretic support that multimarket contact facilitates collusion or not, in the sense that more collusive equilibria in terms of per-market profits exist than those under a benchmark case of one market. An equilibrium candidate under the benchmark case is belief-free strategies. We are the first to construct a non-trivial class of strategies that exhibits the effect of multimarket contact from the perspectives of simplicity and mild punishment. Strategies must be simple because firms in a cartel must coordinate each other with no communication. Punishment must be mild to an extent that it does not hurt even the minimum required profits in the cartel. We thus focus on two-state automaton strategies such that the players are cooperative in at least one market even when he or she punishes a traitor. Furthermore, we identify an additional condition (partial indifference), under which the collusive equilibrium yields the optimal payoff.

cs.GT↗

arXiv2019

Comparison of various methods to extract ringdown frequency from gravitational wave data

The ringdown part of gravitational waves in the final stage of merger of compact objects tells us the nature of strong gravity which can be used for testing the theories of gravity. The ringdown waveform, however, fades out in a very short time with a few cycles, and hence it is challenging for gravitational wave data analysis to extract the ringdown frequency and its damping time scale. We here propose to build up a suite of mock data of gravitational waves to compare the performance of various approaches developed to detect quasi-normal modes from a black hole. In this paper we present our initial results of comparisons of the following five methods; (1) plain matched filtering with ringdown part (MF-R) method, (2) matched filtering with both merger and ringdown parts (MF-MR) method, (3) Hilbert-Huang transformation (HHT) method, (4) autoregressive modeling (AR) method, and (5) neural network (NN) method. After comparing their performance, we discuss our future projects.

gr-qc↗