圆周率的成本：二进制黑洞推断中偏心率诱导偏置的量化
The Cost of Circularity: Quantifying Eccentricity-Induced Biases in Binary Black Hole Inference
AI总结：
研究揭示了二进制黑洞推断中偏心率偏置问题，指出圆形波形模型在高偏心率下存在系统性偏差，强调偏心波形模型对准确推断的重要性。
摘要：
动态组装的二进制黑洞预计在LIGO-Virgo-KAGRA频段内会保留可测量的轨道偏心率，但大多数参数估计分析仍然假设准圆形吸积。这提出了一个关键问题：未建模的偏心率如何强烈影响BBH合并的推断属性？我们通过注入由TEOBResumS-Dali生成的偏心信号，并使用圆形、进动的IMRPhenomXPHM波形模型来恢复它们。在20-80个太阳质量以及偏心率高达e=0.5的情况下，我们发现圆形波形模型仅在非常小的偏心率下仍可靠。在10Hz处，偏心率约为0.2时，恢复的质量、自旋、倾角和距离开始出现显著系统性偏差。圆形进动模板通过引入人工进动来模仿偏心幅度和相位调制，突显了这些效应之间的主要退化性。对于高质量、中等偏心率的合并，圆形模型对参数的误估程度会偏置天体物理学解释和种群研究。我们的结果确立了偏心波形模型在当前和下一代探测器中准确推断所必需的参数空间边界。
英文摘要：
Dynamically assembled binary black holes are expected to retain measurable orbital eccentricity in the LIGO-Virgo-KAGRA band, but most parameter estimation analyses still assume quasi-circular inspirals. This raises a critical question: how strongly does unmodeled eccentricity bias the inferred properties of BBH mergers? We address this by injecting eccentric signals generated with TEOBResumS-Dali and recovering them using the circular, precessing IMRPhenomXPHM waveform model. Across $20$-$80 \, M_\odot$ and eccentricities up to $e=0.5$, we find that circular waveform models remain reliable only for very small eccentricities. Above $e\sim0.2$ at 10 Hz, recovered masses, spins, inclination, and distances begin to show significant systematic offsets. Circular precessing templates mimic eccentric amplitude and phase modulations by introducing artificial precession, highlighting a major degeneracy between these effects. For high-mass, moderately eccentric mergers, circular models misestimate parameters at a level that would bias astrophysical interpretation and population studies. Our results establish the parameter-space boundaries where eccentric waveform models become essential for accurate inference in current and next-generation detectors.
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