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Xiang-Yu Lyu

Publications and source records attributed to Xiang-Yu Lyu.

3 recordsLinked to original sources

Probing the Extreme-Mass-Ratio Inspirals Population Constraints with TianQin

Extreme-mass-ratio inspirals (EMRIs), consisting of a massive black hole and a stellar compact object, are one of the most important sources for space-borne gravitational wave detectors like TianQin. Their population study can be used to constrain astrophysical models that interpret the EMRI formation mechanisms. In this paper, as an initial attempt, we employ a parametrization method to describe the EMRI population model in the loss cone formation channel. This approach, however, can be extended to other models such as the accretion disc driven formation channel. We present the phenomenological characteristic of the MBH mass, spin, and redshift distributions. Then, we investigate the posterior distribution of the hyper-parameters that describe this population model. The optimistic results show that TianQin could recover almost all the posterior of the hyper-parameters within $1\sigma$ confidence interval. The hyper-parameters $\alpha_1, \alpha_2, b$, which describe the MBH mass distribution, could be measured with an accuracy of $46.4\%$, $12.6\%$, and $3\%$, respectively. The hyper-parameters $\mu_z$, and $\sigma_z$, which describe the redshift distribution, could be measured with an accuracy of $15.4\%$ and $21.1\%$. With this estimation accuracy, the EMRI population characteristics can be effectively demonstrated, potentially serving as evidence for EMRI formation in the future studies. Furthermore, with an increasing number of detectable events, the parameter estimation for the hyper-parameters will improve and the confidence intervals will be narrowed.

astro-ph.HE

Near Real-Time Gravitational Wave Data Analysis of the Massive Black Hole Binary with TianQin

Space-borne gravitational wave (GW) detectors can detect the merger of massive black holes. The early warning and localization of GW events before merging can be used to inform electromagnetic telescopes and conduct multimessenger observations. However, this requires real-time data transmission and analysis capabilities. The geocentric orbit of the space-borne GW detector TianQin makes it possible to conduct real-time data transmission. In this study, we develop a search and localization pipeline for massive black hole binaries (MBHBs) with TianQin under both regular and real-time data transmission modes. We demonstrate that, with real-time data transmission, MBHBs can be accurately localized on the fly. With the approaching merger, each analysis can be finished in only 40 min. For an MBHB system at a distance of 1 Gpc, if we receive data every hour, then we can pinpoint its location to within less than 1 deg$^2$ on the final day before the merger.

gr-qc

GWSpace: a multi-mission science data simulator for space-based gravitational wave detection

Space-based gravitational wave detectors such as TianQin, LISA, and TaiJi have the potential to outperform themselves through joint observation. To achieve this, it is desirable to practice joint data analysis in advance on simulated data that encodes the intrinsic correlation among the signals found in different detectors that operate simultaneously. In this paper, we introduce GWSpace, a package that can simulate the joint detection data from TianQin, LISA, and TaiJi. The software is not a groundbreaking work that starts from scratch. Rather, we use as many open-source resources as possible, tailoring them to the needs of simulating the multi-mission science data and putting everything into a ready-to-go and easy-to-use package. We shall describe the main components, the construction, and a few examples of application of the package. A common coordinate system, namely the Solar System Barycenter (SSB) coordinate system, is utilized to calculate spacecraft orbits for all three missions. The paper also provides a brief derivation of the detection process and outlines the general waveform of sources detectable by these detectors.

gr-qc