发表机构
University of Illinois Urbana-Champaign; University of Massachusetts Boston; European University of Tirana; University of New Hampshire; Lebedev Physical Institute; Russian Academy of Sciences（伊利诺伊大学厄巴纳-香槟分校; 马萨诸塞大学波士顿分校; 地拉那欧洲大学; 新罕布什尔大学; 列别杰夫物理研究所; 俄罗斯科学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对本地暗物质密度估计不一致的问题，本文提出孤立估计分布函数并线性化CBE以直接测量力场，再用符号回归获得闭式势，发现可用信息在恒星计数中，恢复的势与等温盘一致。
AI 中文摘要
本地暗物质密度决定了直接探测实验预期信号强度，然而已发表的基于恒星运动的估计值之间的差异超过了它们的误差范围，并且最近对盖亚数据的机器学习分析发现本地密度与零一致。根据金斯定理，由运动积分构建的分布函数对于任何势的选择都平凡地满足无碰撞玻尔兹曼方程（CBE），因此同时将分布函数和势拟合到CBE的搜索无法识别两者。我们的流程则孤立地估计分布函数，将方程在加速度方面线性化，从而允许直接测量本地力场，然后通过符号回归将该场拟合为闭式形式。在整个过程中，我们发现可用信息不在于CBE残差，而在于恒星计数，这是受巡天选择效应扭曲最严重的可观测量的。沿垂直方向，我们恢复的势与经典的自引力等温盘一致。
英文摘要
The local dark matter density determines the strength of the signal expected in direct-detection experiments, yet published estimates from stellar motions disagree by more than their errors, and the most recent machine-learning analysis of Gaia data finds a local density consistent with zero. According to Jeans' theorem, a distribution function built from integrals of motion satisfies the collisionless Boltzmann equation (CBE) trivially for any choice of potential, so a search that simultaneously fits the distribution function and the potential to the CBE identifies neither. Our pipeline instead estimates the distribution function in isolation, linearizing the equation in terms of accelerations and allowing for direct measurement of the local force field, and then fits closed forms to that field via symbolic regression. Throughout, we find that the usable information lies not in the CBE residual but in the stellar number counts, the observable most distorted by survey selection. Along the vertical profile, our recovered potential agrees with the classical self-gravitating isothermal disc.
CommentsThe code can be distributed upon request
