论文标题
重型二进制二进制 - 黑洞合并的进步和偏心率的衡量性
Measurability of precession and eccentricity for heavy binary-black-hole mergers
论文作者
论文摘要
引力波检测提供了对宇宙中黑洞及其形成过程的天体物理种群的见解。探测由天体物理人口的大块分布外的黑洞组成的二进制物特别有趣。在这项研究中，我们利用NR替代模型NRSUR7DQ4和从SXS和RIT目录中选择了NR替代模型NRSUR7DQ4，在中间质量黑洞范围内进行注射分析。我们的调查重点是进进的可检测性及其对偏心率的潜在堕落性，尤其是对于只有几个周期的短信号。总体质量，质量比和$χ_\ Mathrm {eff} $通常得到很好的回收，但$χ_\ Mathrm {p} $的回收率很大程度上受到限制，并且噪声会显着影响短信号的某些参数的恢复。我们还发现，在假设准圆形信号时，低于0.2的偏心率不足以模仿参数估计。我们的结果表明，在参数估计中产生高度进动的证据是必要的，但是最终确定哪种效果是造成GW190521等事件中观察到的高度预动力的最大挑战。我们强调了从短信号解释二进制的属性并突出未来第三代探测器和偏心波形模型的潜在好处，以更详尽地探索参数空间的潜在好处。
Gravitational wave detections offer insights into the astrophysical populations of black holes in the universe and their formation processes. Detections of binaries consisting of black holes lying outside the bulk distribution of the astrophysical population are particularly intriguing. In this study, we perform an injection analysis within the intermediate-mass black hole range, utilizing the NR surrogate model NRSur7dq4 and a selection of NR waveforms from the SXS and RIT catalogues. Our investigation focuses on the detectability of precession and its potential degeneracy with eccentricity, especially for short signals with only a few cycles in band. While total mass, mass ratio, and $χ_\mathrm{eff}$ are generally well recovered, the recovery of $χ_\mathrm{p}$ is largely limited, and noise significantly impacts the recovery of some parameters for short signals. We also find that eccentricity lower than 0.2 is insufficient to mimic precession in parameter estimation when assuming a quasi-circular signal. Our results suggest that a certain degree of precession is necessary to produce evidence of high precession in parameter estimation, but it remains challenging to conclusively determine which effect is responsible for the high precession observed in events like GW190521. We emphasize the importance of caution when interpreting properties of a binary from short signals and highlight the potential benefits of future third generation detectors and eccentric waveform models for more exhaustive exploration of parameter space.
