论文标题
检测具有当前和未来检测器的脉冲星的瞬态准单色重力波的前景
Prospects for detecting transient quasi-monochromatic gravitational waves from glitching pulsars with current and future detectors
论文作者
论文摘要
脉冲星正在旋转发出周期性电磁辐射的中子星。尽管脉冲星通常会随着能量而放慢速度,但有些也会经历故障:自发增加其旋转频率。根据几种模型,这些小故障还可以导致长时间瞬态重力波(GWS)的发射。我们通过比较已知故障的间接能量上限与当前和未来基于地面的GW探测器的灵敏度,从而提出了此类信号的检测前景。我们首先基于故障大小考虑了通用约束的乐观案例,并发现在第四个Ligo-Virgo-kagra观察跑步(O4)中,现实的匹配过滤器搜索(O4)可以进行检测,或将其设置为低于这些间接的上限,在这些间接上限以下,对于726个先前经过的GlitchEs和74 o5 n o5 in o5 n of the GlitchEs中的36个。使用第三代爱因斯坦望远镜或宇宙探险家,可以使用35-40%的小故障。当专门针对瞬时山脉产生gw后GW发射的情况时,按照Yim&Jones模型,间接上限更加严格。在该模型下的预测所需的带有测量愈合参数的119个小故障中,对于O4和O5的14,只有6个故障,与第三代探测器的百分比相似。我们还讨论了该模型如何匹配观察到的小故障种群。
Pulsars are rotating neutron stars that emit periodic electromagnetic radiation. While pulsars generally slow down as they lose energy, some also experience glitches: spontaneous increases of their rotational frequency. According to several models, these glitches can also lead to the emission of long-duration transient gravitational waves (GWs). We present detection prospects for such signals by comparing indirect energy upper limits on GW strain for known glitches with the sensitivity of current and future ground-based GW detectors. We first consider the optimistic case of generic constraints based on the glitch size and find that realistic matched-filter searches in the fourth LIGO-Virgo-KAGRA observing run(O4) could make a detection, or set constraints below these indirect upper limits, for equivalents of 36 out of 726 previously observed glitches, and 74 in the O5 run. With the third-generation Einstein Telescope or Cosmic Explorer, 35-40% of glitches would be accessible. When specialising to a scenario where transient mountains produce the post-glitch GW emission, following the Yim & Jones model, the indirect upper limits are stricter. Out of the smaller set of 119 glitches with measured healing parameter, as needed for predictions under that model, only 6 glitches would have been within reach for O4 and 14 for O5, with a similar percentage as before with third generation detectors. We also discuss how this model matches the observed glitch population.