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BIMSA General Relativity Seminar
Gravitational Wave Signatures of Quasi-Periodic Eruptions: LISA Detection Prospects for RX J1301.9+2747
Gravitational Wave Signatures of Quasi-Periodic Eruptions: LISA Detection Prospects for RX J1301.9+2747
组织者
演讲者
Leif Lui
时间
2025年11月21日 16:30 至 17:30
地点
A3-2-301
线上
Zoom 787 662 9899
(BIMSA)
摘要
One prominent model for quasi-periodic eruptions (QPEs) is that they originate from extreme mass-ratio inspirals (EMRIs) involving stellar-mass objects orbiting around massive black holes and colliding with their accretion disks. We compute the gravitational wave signals from such a model, demonstrating that orbiter-disk interactions result in small frequency shifts and high-frequency tails due to the excitation of non-discrete modes. Interestingly, we show that QPE RX J1301.9+2747 could be detectable by future space-based gravitational wave detectors, provided a moderate eccentricity around 0.250.25 and a mass exceeding 35 M⊙35M⊙ for the orbiter. Moreover, based on this QPE model, we show that the signal-to-noise ratio of the gravitational wave signals from QPEs, if detectable, will be sufficiently high to distinguish such systems from vacuum EMRIs and shed light on the origin of QPEs and environments around massive black holes.
演讲者介绍
Leif Lui is currently a visiting scholar at the Beijing Institute of Mathematical Sciences and the Kavli Institute of Astronomy and Astrophysics at Peking University. Leif completed his MPhil degree in Physics at The University of Hong Kong, and his BSc at the Chinese University of Hong Kong. He now is specializing in theoretical astrophysics, general relativity, and gravitational-wave science. His research is centered on developing sophisticated waveform models for extreme-mass-ratio inspirals (EMRIs), with a focus on how astrophysical environments—such as accretion disks, dark matter halos, and stellar clusters—imprint detectable signatures on gravitational-wave signals. His recent work, which includes a first-of-its-kind model of Quasi-Periodic Eruptions as multi-messenger EMRI sources and makes use of cutting-edge tools like the FastEMRIWaveforms (FEW) code.