MultiCAM：一个连接暗晕质量吸积历史与其性质的多变量框架
MultiCAM: A multivariable framework for connecting the mass accretion history of haloes with their properties
AI总结：
MultiCAM框架通过同时利用暗晕完整质量吸积历史来连接多个暗晕或星系性质，克服了传统单值概括的信息损失，并在暗物质模拟中验证了其优于单时期条件丰度匹配模型的精度。
摘要：
连接星系与暗晕性质的模型通常将暗晕的质量吸积历史（MAH）概括为单一数值，并以该数值作为预测的基础。然而，单一数值的概括无法捕捉MAH的复杂性，并且在这一过程中可能会丢失信息。我们提出MultiCAM，这是传统丰度匹配框架的一种推广，能够同时将暗晕的完整MAH与多个暗晕和/或星系性质联系起来。作为首个案例研究，我们将MultiCAM应用于一个仅含暗物质的模拟中，解决暗物质晕性质与其MAH之间的连接问题。虽然某些暗晕性质（例如聚集度）与暗晕的早期质量增长相关性更强，但其他性质（如维里比）则与晚期质量增长具有更强的相关性。这凸显了考虑整个MAH对暗晕性质影响的必要性。对于我们考虑的大多数暗晕性质，我们发现使用完整MAH的MultiCAM模型比使用单一时期的条件丰度匹配模型具有更高的精度。我们还展示了MultiCAM的一种扩展，该扩展能够捕捉预测的暗晕性质之间的协方差。这一扩展为预测性质之间协方差很重要的应用提供了一个基线模型。
英文摘要：
Models that connect galaxy and halo properties often summarize a halo's mass accretion history (MAH) with a single value, and use this value as the basis for predictions. However, a single-value summary fails to capture the complexity of MAHs and information can be lost in the process. We present MultiCAM, a generalization of traditional abundance matching frameworks, which can simultaneously connect the full MAH of a halo with multiple halo and/or galaxy properties. As a first case study, we apply MultiCAM to the problem of connecting dark matter halo properties to their MAHs in the context of a dark matter-only simulation. While some halo properties, such as concentration, are more strongly correlated to the early-time mass growth of a halo, others, like the virial ratio, have stronger correlations with late-time mass growth. This highlights the necessity of considering the impact of the entire MAH on halo properties. For most of the halo properties we consider, we find that MultiCAM models that use the full MAH achieve higher accuracy than conditional abundance matching models which use a single epoch. We also demonstrate an extension of MultiCAM that captures the covariance between predicted halo properties. This extension provides a baseline model for applications where the covariance between predicted properties is important.
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