Parameter estimation for Einstein-dilaton-Gauss-Bonnet gravity with ringdown signals
作者机构:MOE Key Laboratory of Fundamental Physical Quantities MeasurementHubei Key Laboratory of Gravitation and Quantum PhysicsPGMFand School of PhysicsHuazhong University of Science and TechnologyWuhan 430074China
出 版 物:《Chinese Physics C》 (中国物理C(英文版))
年 卷 期:2023年第47卷第10期
页 面:213-224页
核心收录:
学科分类:07[理学] 070201[理学-理论物理] 0702[理学-物理学]
基 金:the National Key R&D Program of China(2022YFC2204602) the Natural Science Foundation of China(11925503)
主 题:Einstein-dilaton-Gauss-Bonnet gravity quasinormal modes space-based gravitational-wave detection parameter estimation
摘 要:Future space-based gravitational-wave detectors will detect gravitational waves with high sensitivity in the millihertz frequency band,providing more opportunities to test theories of gravity than ground-based *** study of quasinormal modes(QNMs)and their application in gravity theory testing have been an important aspect in the field of gravitational *** this study,we investigate the capability of future space-based gravitational wave detectors,such as LISA,TaiJi,and TianQin,to constrain the dimensionless deviating parameter for Einsteindilaton-Gauss-Bonnet(EdGB)gravity with ringdown signals from the merger of binary black *** ringdown signal is modeled by the two strongest QNMs in EdGB *** time-delay interferometry,we calculate the signal-to-noise ratio of different space-based detectors for ringdown signals to analyze their *** Fisher information matrix is employed to analyze the accuracy of parameter estimation,with particular focus on the dimensionless deviating parameter for EdGB *** impact of the parameters of gravitational wave sources on the estimation accuracy of the dimensionless deviating parameter is also *** find that the constraint ability of EdGB gravity is limited because the uncertainty of the dimensionless deviating parameter increases with a decrease in the dimensionless deviating *** and TaiJi offer more advantages in constraining the dimensionless deviating parameter to a more accurate level for massive black holes,whereas TianQin is more suited to less massive black *** Bayesian inference method is used to perform parameter estimation on simulated data,which verifies the reliability of the conclusion.