发表机构
University of Virginia; University of Surrey; Space Telescope Science Institute; University of Toronto（弗吉尼亚大学; 萨里大学; 太空望远镜科学研究所; 多伦多大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过前向建模双星观测模拟器，量化了超暗矮星系中未分辨双星对速度弥散估计的偏差，并强调需结合双星种群与观测节奏进行校正。
AI 中文摘要
银河系中的超暗矮星系（UFDs）是研究低质量星系形成和暗物质的理想探针，因为它们高度受暗物质主导。然而，在质量最低的系统中，未分辨的双星轨道运动通过夸大测量的速度弥散并偏差对推断质量的解释，使动力学质量估计复杂化。我们开发了一个灵活的前向建模流程，即双星观测模拟器（Binary Observation Simulator），用于生成矮星系中双星种群的模拟多历元视向速度观测，并量化双星引起的偏差如何依赖于星系属性和观测策略。我们生成了跨越真实速度弥散$\sigma_{\rm true}\sim0.75$-$3.5$ km/sec、双星比例$0.1$-$0.9$以及长达$10$年的多历元基线的模拟样本。我们发现，虽然多历元监测减少了双星引起的偏差，但对于低质量晕，残余污染仍然显著：即使$10$年的基线，对于$\sigma_{\rm true}\lesssim1$ km/sec的系统，仍可留下约$10$-$120\\%$的相对偏差。我们还注意到，小样本量（$\lesssim20$）在恢复的速度弥散中引入了大量的随机散射，有时掩盖了较长观测基线预期的改进。将该框架应用于真实的约$17$年的牧夫座I（Bootes I）观测记录，重现了文献中的速度弥散，给出了基于该观测节奏的经验校正，并表明将相同的观测重新分配到一半数量的恒星上，将消除大约一半的残余双星偏差。这些结果强调，对于最暗弱矮星的稳健弥散估计，需要对双星种群和巡天观测节奏进行前向建模。
英文摘要
Ultra-faint dwarf galaxies (UFDs) in the Milky Way are ideal probes of low-mass galaxy formation and dark matter because they are highly dark-matter dominated. In the lowest-mass systems, however, unresolved binary orbital motion complicates dynamical mass estimates by inflating measured velocity dispersions and biasing the interpretation of the inferred masses. We develop a flexible forward-modeling pipeline, the Binary Observation Simulator, to generate mock multi-epoch radial-velocity observations of binary populations in dwarf galaxies and to quantify how binary-induced biases depend on both galaxy properties and observing strategy. We generate mock samples spanning true velocity dispersion of $σ_{\rm true}\sim0.75$-$3.5$ km/sec, binary fractions of $0.1$-$0.9$, and multi-epoch baselines of up to $10$ yr. We find that, while multi-epoch monitoring reduces the binary-induced bias, residual contamination remains significant for low-mass halos: even a $10$-yr baseline can leave $\sim10$-$120\%$ relative bias for systems with $σ_{\rm true}\lesssim1$ km/sec. We also note that small sample sizes ($\lesssim20$) introduce substantial stochastic scatter in the recovered dispersions, sometimes masking the expected improvement from longer observational baselines. Applying the framework to the real $\sim17$-yr Bootes I observing record reproduces the literature velocity dispersions, yields an empirical correction conditioned on that cadence, and shows that redistributing the same observations onto half the number of stars would have removed roughly half of the residual binary bias. These results emphasize that robust dispersion estimates for the faintest dwarfs require forward modeling of both binary populations and survey cadence.
Comments15 pages + appendices, 6 figures, submitted to ApJ. Code available at https://github.com/xou-mit/binary-observation-simulator
