论文标题

用重力波探测暗物质的前景

Prospects of Probing Dark Matter Condensates with Gravitational Waves

论文作者

Banerjee, Shreya, Bera, Sayantani, Mota, David F.

论文摘要

Lambda-Cold暗物质模型迄今为止最准确地解释了宇宙学观察。但是,在银河尺度上,它仍然困扰着各种缺点。已经提出了诸如超氟黑质,玻色 - 因斯坦冷凝水(BEC)暗物质和模糊暗物质的模型,以克服其中一些缺点。在这项工作中,我们使用当前对重力波(GW)传播速度的探测这些模型来自Ligo-Virgo探测器网络的二进制中子星GW170817检测,并使用它来研究这三个模型的允许参数空间,用于高级LIGO+VIRGO,LIGO,LISA,IPTA,IPTA和SKA检测频率。 GW的速度已被证明取决于介质的折射率,这又取决于通过银河系光环的密度分布的暗物质模型参数。我们使用来自GW速度测量和银河系半径结合的边界来限制这些模型的参数空间。我们的发现表明,使用高级Ligo-Virgo检测器灵敏度,此处考虑的三个模型仍然不受限制。仅对于检测频率才能获得有意义的约束,$ \ leq 10^{ - 9} $ Hz,它属于IPTA和SKA等射电望远镜的检测范围。考虑到这种最佳情况,我们发现在三种凝聚力模型中,模糊的暗物质模型是在不久的将来被伪造/验证的最可行的场景。

The Lambda-Cold Dark Matter model explains cosmological observations most accurately till date. However, it is still plagued with various shortcomings at galactic scales. Models of dark matter such as superfluid dark matter, Bose-Einstein Condensate(BEC) dark matter and fuzzy dark matter have been proposed to overcome some of these drawbacks. In this work, we probe these models using the current constraint on the gravitational wave (GW) propagation speed coming from the binary neutron star GW170817 detection by LIGO-Virgo detector network and use it to study the allowed parameter space for these three models for Advanced LIGO+Virgo, LISA, IPTA and SKA detection frequencies. The speed of GW has been shown to depend upon the refractive index of the medium, which in turn, depends on the dark matter model parameters through the density profile of the galactic halo. We constrain the parameter space for these models using the bounds coming from GW speed measurement and the Milky Way radius bound. Our findings suggest that with Advanced LIGO-Virgo detector sensitivity, the three models considered here remain unconstrained. A meaningful constraint can only be obtained for detection frequencies $\leq 10^{-9}$ Hz, which falls in the detection range of radio telescopes such as IPTA and SKA. Considering this best possible case, we find that out of the three condensate models, the fuzzy dark matter model is the most feasible scenario to be falsified/ validated in near future.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源