随机效应对使用天文偏振源的超轻暗物质搜索的影响
Stochastic effect on ultralight dark matter searches with astronomical polarized sources
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中文总结 AI 辅助
该研究提出统一统计框架，分类超轻ALP暗物质引起的偏振振荡信号为四区域，并强调源距离不确定性可致耦合约束改变三倍，为天文偏振源搜索提供一致基础。
中文摘要 AI 辅助
超轻轴子类粒子（ALP）是暗物质的有力候选者。在标准晕模型中，超轻银河系暗物质表现为随机高斯随机场，穿过该场的线偏振光的偏振角随观测者与源之间的场差成比例地随机振荡。该信号的统计特性取决于源的大小及其与观测者的距离相对于ALP康普顿长度和相干长度，因此也取决于ALP质量。我们提出了一个统一的统计框架，用于对任意大小和距离的光源进行偏振振荡搜索。我们将随机振荡振幅的统计特性分为四个不同的区域，并提供了包括它们之间过渡区域在内的无缝描述。我们的框架重现了先前已知情况下的信号模型，包括实验室规模的搜索以及使用脉冲星和宇宙微波背景的搜索。我们提供了一种包含信号随机性的似然方法，并表明必须仔细考虑源距离的不确定性，因为它们可能使ALP-光子耦合的约束结果改变多达三倍。我们的结果为解释和比较使用天文偏振源进行的一系列ALP搜索提供了一致的基础。
英文摘要
Ultralight axion-like particles (ALP) are the well-motivated candidates for the dark matter. In the standard halo model, the ultralight galactic dark matter behaves as a stochastic Gaussian random field, and the polarization angle of the linearly polarized light propagating through the field stochastically oscillates proportional to the field difference between the observer and the source. The statistics of this signal depend on the source size and its distance from the observer relative to the ALP Compton length and coherence length, and therefore on the ALP mass. We present a unified statistical framework for the polarization-oscillation searches with light sources of arbitrary size and distance. We classify the statistics of the stochastic oscillation amplitude into four distinct regimes and provide a seamless description including the transitional regimes between them. Our framework reproduces the signal models in previously known cases including the laboratory-scale searches and searches using pulsars and the cosmic microwave background. We provide a likelihood prescription that incorporates the stochasticity of the signal, and show that uncertainties in source distance must be carefully accounted for, as they can alter the resulting constraints on the ALP-photon coupling by up to a factor of three. Our results provide a consistent basis for interpreting and comparing a broad range of ALP searches with astronomical polarized sources.
发表机构
- Princeton University（普林斯顿大学）
机构由 AI 辅助整理，请以论文原文为准。
