论文标题

超轻骨化暗物质检测的强度干涉测量法

Intensity interferometry for ultralight bosonic dark matter detection

论文作者

Masia-Roig, Hector, Figueroa, Nataniel L., Bordon, Ariday, Smiga, Joseph A., Stadnik, Yevgeny V., Budker, Dmitry, Centers, Gary P., Gramolin, Alexander V., Hamilton, Paul S., Khamis, Sami, Palm, Christopher A., Pustelny, Szymon, Sushkov, Alexander O., Wickenbrock, Arne, Kimball, Derek F. Jackson

论文摘要

可以通过在玻色子的康普顿频率附近振荡的经典波形磁场来描述超轻的玻色子暗物质(UBDM)。如果用于直接检测UBDM相互作用的测量方案对田间的签名二次敏感,则信号的接近零频率(DC)分量。因此,可以使用具有给定有限带宽的检测器来搜索具有比其带宽大的数量级的康普顿频率的玻色子。这打开了类似于汉伯里棕色和Twiss强度干涉法的检测方案的可能性。假设UBDM在银河引力电位中被病毒,则随机速度与康普顿频率产生了轻微的偏差。这些导致强度在时间尺度上由动能中的扩散确定的时间尺度上的随机波动。为了减轻普遍存在的局部低频噪声,可以使用传感器网络来通过测量传感器之间的互相关来搜索随机强度波动。此方法本质上是宽带,因为大量的康普顿频率将在传感器带宽内产生接近零的频率组件,可以同时搜索。现有传感器网络的测量值具有足够的灵敏度来搜索实验未开发的参数空间。

Ultralight bosonic dark matter (UBDM) can be described by a classical wave-like field oscillating near the Compton frequency of the bosons. If a measurement scheme for the direct detection of UBDM interactions is sensitive to a signature quadratic in the field, then there is a near-zero-frequency (dc) component of the signal. Thus, a detector with a given finite bandwidth can be used to search for bosons with Compton frequencies many orders of magnitude larger than its bandwidth. This opens the possibility of a detection scheme analogous to Hanbury Brown and Twiss intensity interferometry. Assuming that the UBDM is virialized in the galactic gravitational potential, the random velocities produce slight deviations from the Compton frequency. These result in stochastic fluctuations of the intensity on a time scale determined by the spread in kinetic energies. In order to mitigate ubiquitous local low-frequency noise, a network of sensors can be used to search for the stochastic intensity fluctuations by measuring cross-correlation between the sensors. This method is inherently broadband, since a large range of Compton frequencies will yield near-zero-frequency components within the sensor bandwidth that can be searched for simultaneously. Measurements with existing sensor networks have sufficient sensitivity to search experimentally unexplored parameter space.

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