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arXiv 2606.02431astro-ph.HEastro-ph.SR
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回归上的回归:将数据驱动的双黑洞并合率拟合映射到前身历史

Regression on Regression: Mapping Data-Driven Binary Black Hole Merger Rate Fits to Progenitor Histories

Canadian Institute for Theoretical Astrophysics(加拿大理论天体物理研究所);University of Toronto(多伦多大学);David A. Dunlap Department of Astronomy and Astrophysics, University of Toronto(多伦多大学戴维·邓普天文学与天体物理学系)

Emma Blanchet, Aryanna Schiebelbein-Zwack, Maya Fishbach

AI总结:

提出“回归上的回归”框架,通过将物理模型参数直接映射到数据驱动的双黑洞并合率拟合,实现灵活群体模型的物理解释,并揭示模型误设。

摘要:

双黑洞(BBH)并合率由前身形成率和形成到并合之间的延迟时间分布决定,但这些函数仍受约束不足。我们引入一个框架,将物理驱动模型的参数直接映射到现有的数据驱动的BBH并合率拟合上。这种“回归上的回归”方法能够对灵活的群体模型进行物理解释,而无需重新分析底层引力波事件数据的计算负担。将该方法应用于第四次引力波瞬态目录中的\textsc{B-Spline}并合率后验,我们拟合了最小延迟时间($τ_{\text{min}}$)、延迟时间幂律指数($α$)以及控制归一化($\mathcal{A}$)、早期增长($γ$)和晚期衰减($δ$)的前身形成参数。将锚定红移点从两个增加到四个,使中位数平方和误差(SSE)降低了约4.5倍。然而,残差显示物理模型并未通过所有四个锚点,暴露了模型误设,并展示了该框架的一个关键优势:与标准推断方法(优先加权兼容曲线并掩盖潜在张力)不同,我们的方法暴露了与模型不可调和的BBH后验。尽管在$z\gtrsim1$处存在不确定性,但低$z$处前身形成率的形状是稳健的,并且比全局恒星形成率(SFR)演化更陡峭,支持对低金属丰度环境的偏好。具体来说,前身率的对数空间斜率在$z=0.1$到$z=1.0$之间比SFR陡约5.3倍。最终,需要更复杂的唯象模型来匹配\textsc{B-Spline}并合率。

英文摘要:

The binary black hole (BBH) merger rate is governed by the progenitor formation rate and the distribution of delay-times between formation and merger, but these functions remain poorly constrained. We introduce a framework that maps the parameters of physics-driven models directly onto existing data-driven fits of the BBH merger rate. This ``regression on regression'' approach enables physical interpretation of flexible population models without the computational burden of reanalyzing the underlying gravitational-wave event data. Applying this method to the \textsc{B-Spline} merger-rate posteriors from the Fourth Gravitational-Wave Transient Catalog, we fit the minimum delay time ($τ_{\text{min}}$), delay-time power-law index ($α$), and progenitor formation parameters controlling the normalization ($\mathcal{A}$), early-time growth ($γ$), and late-time decay ($δ$). Increasing the number of anchoring redshift points from two to four reduces the median sum-squared error (SSE) by a factor of $\approx 4.5$. However, residuals reveal that the physical model does not pass through all four anchors, exposing model misspecification and demonstrating a key strength of the framework: unlike standard inference methods, which preferentially weight compatible curves and mask underlying tensions, our approach exposes BBH posteriors irreconcilable with the model. Despite uncertainties at $z\gtrsim1$, the shape of the progenitor formation rate at low-$z$ is robust and evolves more steeply than the global star formation rate (SFR), supporting a preference for low metallicity environments. Specifically, the log-space slope of the progenitor rate is $\approx 5.3$ times steeper than the SFR between $z=0.1$ and $z=1.0$. Ultimately, a more complex phenomenological model is required to match the \textsc{B-Spline} merger rates.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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