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arXiv 2401.02493gr-qcastro-ph.HE
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利用模型无关的波形重构和第三代探测器识别中子星并合残骸中的热效应

Identifying thermal effects in neutron star merger remnants with model-agnostic waveform reconstructions and third-generation detectors

Miquel Miravet-Tenés, Davide Guerra, Milton Ruiz, Pablo Cerdá-Durán, José A. Font

AI总结:

本研究通过BayesWave算法和Einstein Telescope探测不同热效应处理方式下双中子星并合后的引力波信号差异,发现自洽处理热效应对避免参数偏差至关重要。

摘要:

我们探究了双中子星(BNS)并合模拟引力波信号的内在差异,这些差异源于在数值相对论建模中引入热效应的不同方法。我们考虑了一种混合方法,其中状态方程(EOS)由冷态、零温的分段多方部分和由理想气体描述的热部分组成;以及一种基于自洽、微观物理、有限温度EOS的列表方法。我们使用了对应于四种不同EOS的BNS并合模拟的时域波形。这些波形被注入到由第三代探测器Einstein Telescope灵敏度给出的高斯噪声中,并使用BayesWave进行重构,这是一种通过模型无关方法恢复信号的贝叶斯数据分析算法。热效应的两种表示方式导致了并合后信号频谱中主峰频率的不同,无论是四极基态模式还是晚期惯性模式皆是如此。对于所研究的某些EOS,这些差异大到足以被区分开来,特别是在并合后早期信号振幅最响时。我们的结果表明,在BNS并合后建模中对热效应进行自洽处理至关重要,以防止在即将到来的引力波探测中出现显著的参数偏差。

英文摘要:

We probe the intrinsic differences in simulated gravitational-wave signals from binary neutron star (BNS) mergers, arising from varying approaches to incorporating thermal effects in numerical-relativity modeling. We consider a hybrid approach in which the equation of state (EOS) comprises a cold, zero-temperature, piecewise-polytropic part and a thermal part described by an ideal gas, and a tabulated approach based on self-consistent, microphysical, finite-temperature EOS. We use time-domain waveforms corresponding to BNS merger simulations with four different EOSs. Those are injected into Gaussian noise given by the sensitivity of the third-generation detector Einstein Telescope and reconstructed using BayesWave, a Bayesian data-analysis algorithm that recovers the signals through a model-agnostic approach. The two representations of thermal effects result in different dominant peak frequencies in the spectra of the postmerger signals, for both the quadrupole fundamental mode and the late-time inertial modes. For some of the EOSs investigated those differences are large enough to be told apart, especially in the early postmerger phase when the signal amplitude is the loudest. Our results suggest that a self-consistent treatment of thermal effects in BNS postmerger modeling is essential to prevent significant parameter biases in upcoming gravitational-wave detections.

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