标题： 使用贝叶斯统计方法通过精密测量设备网络搜索瞬态超轻暗物质信号 显示英文标题

标题： Search for transient ultralight dark matter signatures with networks of precision measurement devices using a Bayesian statistics method

摘要： 我们分析了利用分布式全球精密测量设备网络作为暗物质和奇异物理观测站的前景。 特别是，我们考虑了全球定位系统（GPS）的原子钟，该系统由32颗中地球轨道卫星组成，这些卫星配备了铯（Cs）或铷（Rb）微波钟，并且包括若干地球上的接收站，其中一些使用高稳定性的氢原子钟。 高精度的时间数据已可供使用近二十年。 通过分析卫星和地面原子钟数据，可以寻找奇异物理的瞬态特征，例如“团块状”暗物质和暗能量，从而有效地将GPS星座转变为50,000公里孔径的传感器阵列。 在此，我们描述了GPS卫星原子钟的噪声特性，介绍了基于贝叶斯统计的搜索方法，并使用模拟的钟数据测试了该方法。 我们展示了使用该方法的预期发现能力，并证明对于某些模型，其性能可以超越现有约束几个数量级。 我们的方法不仅限于GPS或原子钟网络，还可以应用于其他精密测量设备网络。 显示英文摘要

摘要： We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the Global Positioning System (GPS), consisting of a constellation of 32 medium-Earth orbit satellites equipped with either Cs or Rb microwave clocks and a number of Earth-based receiver stations, some of which employ highly-stable H-maser atomic clocks. High-accuracy timing data is available for almost two decades. By analyzing the satellite and terrestrial atomic clock data, it is possible to search for transient signatures of exotic physics, such as "clumpy" dark matter and dark energy, effectively transforming the GPS constellation into a 50,000km aperture sensor array. Here we characterize the noise of the GPS satellite atomic clocks, describe the search method based on Bayesian statistics, and test the method using simulated clock data. We present the projected discovery reach using our method, and demonstrate that it can surpass the existing constrains by several order of magnitude for certain models. Our method is not limited in scope to GPS or atomic clock networks, and can also be applied to other networks of precision measurement devices.