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arXiv 2010.04151astro-ph.HE
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超紧凑脉冲双星系统的可探测性

On the detectability of ultra-compact binary pulsar systems

Nihan Pol, Maura McLaughlin, Duncan R. Lorimer, Nathan Garver-Daniels

摘要:

使用神经网络,我们集成的能力,占多普勒拖尾由于脉冲星的轨道运动与脉冲星人口合成包\psrpoppy \发展精确的建模所观察到的脉冲星人口。作为第一个应用程序,我们表明,二进制中子星系统的两个组件具有高度不等的质量,平均而言,更容易检测比系统的质量对称。然后,我们调查人口的超紧凑($1.5 \, {\rm min} \leq P_{\rm b} \leq 15\,\rm min$)中子星-白矮星(NS-WD)和双中子星(DNS)系统,这是有前途的来源激光干涉仪空间天线引力波探测器。鉴于迄今为止在无线电勘测中没有检测到这些系统,我们估计银河系中分别向地球发射的超紧凑NS-WD和DNS系统的置信度上限为$\sim$ 1450和$\sim$ 1100。我们还表明,使用调查积分时间在20~s到200~s的范围内与时域rescue将最大化的信噪比,以及这些超紧凑的双星系统的检测概率。在所有大尺度射电脉冲星巡天中,目前正在阿雷西博射电望远镜上进行的巡天,在未来几年内,使用当前的积分时间,$\sim$有$\sim$ 50- 80%的机会探测到至少一个这样的系统,使用最佳积分时间,$\sim$有$\sim$ 80- 95%的机会探测到至少一个这样的系统。

英文摘要:

Using neural networks, we integrate the ability to account for Doppler smearing due to a pulsar's orbital motion with the pulsar population synthesis package \psrpoppy\ to develop accurate modeling of the observed binary pulsar population. As a first application, we show that binary neutron star systems where the two components have highly unequal mass are, on average, easier to detect than systems which are symmetric in mass. We then investigate the population of ultra-compact ($1.5 \, {\rm min} \leq P_{\rm b} \leq 15\,\rm min$) neutron star--white dwarf (NS--WD) and double neutron star (DNS) systems which are promising sources for the Laser Interferometer Space Antenna gravitational-wave detector. Given the non-detection of these systems in radio surveys thus far, we estimate a 95\% confidence upper limit of $\sim$1450 and $\sim$1100 ultra-compact NS--WD and DNS systems in the Milky Way that are beaming towards the Earth respectively. We also show that using survey integration times in the range 20~s to 200~s with time-domain resampling will maximize the signal-to-noise ratio as well as the probability of detection of these ultra-compact binary systems. Among all the large scale radio pulsar surveys, those that are currently being carried out at the Arecibo radio telescope have $\sim$50--80\% chance of detecting at least one of these systems using current integration integration times and $\sim$80--95\% using optimal integration times in the next several years.

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