提高干涉引力波探测器在有限光行时间内对超光矢量暗物质的灵敏度

S. Morisaki, Tomohiro Fujita, Y. Michimura, Hiromasa Nakatsuka, Ippei Obata
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引用次数: 13

摘要

最近的一些研究指出,引力波探测器对超光速矢量暗物质敏感,并且可以改进等效原理测试给出的当前最佳约束。虽然引力波探测器是一种高度精确的测量臂长度差的工具,但它的灵敏度有限,因为矢量暗物质引起的测试质量镜的位移几乎是常见的。在本文中,我们指出,如果考虑到探测器臂中有限光传播时间的影响,灵敏度将得到显著提高。这种效应使先进的LIGO能够将$U(1)_{B-L}$规范耦合的约束比目前的最佳约束提高一个数量级。这也使得未来的引力波探测器的灵敏度远远高于目前的探测器。新效应对约束的改善因子取决于矢量暗物质的质量,先进的LIGO、爱因斯坦望远镜、宇宙探测器、DECIGO和LISA的最大改善因子分别为470美元、880美元、1600美元、180美元和1400美元。包括新效应,我们更新了先进LIGO第一次观测运行给出的约束条件,并且与目前的最佳约束条件相比,将$U(1)_B$规范耦合的约束条件提高了一个数量级。
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Improved sensitivity of interferometric gravitational-wave detectors to ultralight vector dark matter from the finite light-traveling time
Recently several studies have pointed out that gravitational-wave detectors are sensitive to ultralight vector dark matter and can improve the current best constraints given by the Equivalence Principle tests. While a gravitational-wave detector is a highly precise measuring tool of the length difference of its arms, its sensitivity is limited because the displacements of its test mass mirrors caused by vector dark matter are almost common. In this Letter we point out that the sensitivity is significantly improved if the effect of finite light-traveling time in the detector's arms is taken into account. This effect enables advanced LIGO to improve the constraints on the $U(1)_{B-L}$ gauge coupling by an order of magnitude compared with the current best constraints. It also makes the sensitivities of the future gravitational-wave detectors overwhelmingly better than the current ones. The factor by which the constraints are improved due to the new effect depends on the mass of the vector dark matter, and the maximum improvement factors are $470$, $880$, $1600$, $180$ and $1400$ for advanced LIGO, Einstein Telescope, Cosmic Explorer, DECIGO and LISA respectively. Including the new effect, we update the constraints given by the first observing run of advanced LIGO and improve the constraints on the $U(1)_B$ gauge coupling by an order of magnitude compared with the current best constraints.
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