标题： 在真实脉冲星计时阵列数据集中分离确定性与随机引力波信号 显示英文标题

标题： Separating deterministic and stochastic gravitational wave signals in realistic pulsar timing array datasets

摘要： 最近通过脉冲星计时阵列的观测表明存在引力波信号，这些信号很可能来自超大质量黑洞双星。 这些双星可以产生两种类型的信号：随机引力波背景（GWB）或确定性的连续引力波（CGW）。 正确分离这些信号对于准确的信号恢复和解释至关重要。 本文研究了当前分析流程中GWB和CGW信号之间的相互作用，重点探讨当这些信号单独或一起分析时出现的误解释和参数估计偏差。 我们基于欧洲PTA 24.8年数据集进行了若干模拟。 首先，我们注入了GWB或CGW。 我们比较了使用不同搜索模型的参数估计，包括仅地球项、结合地球项和脉冲星项的CGW模板，以及相关（HD）或不相关（CURN）幂律GWB模板。 我们的研究结果表明，当独立搜索时，GWB和CGW信号可能会被误认为彼此，只有联合搜索才能恢复真实存在的信号。 对于同时包含GWB和CGW的数据集，未能考虑CGW会导致GWB的恢复出现偏差。 然而，联合搜索可以无显著偏差地恢复GWB和CGW的参数。 在对这些多组分数据集进行联合搜索时，必须注意所使用的方法，因为CGW的脉冲星项可能被误认为是CURN。 通过直接搜索HD相关GWB加上CGW可以避免这种情况。 我们的研究强调了联合搜索的重要性，以确保在存在强CGW的情况下无偏恢复GWB参数，这对于解释最近在PTA数据中发现的信号至关重要，并代表了迈向未来更敏感数据集中解开随机和确定性GW信号的稳健框架的重要一步。 显示英文摘要

摘要： Recent observations by pulsar timing arrays indicate the presence of gravitational wave signals, likely from supermassive black hole binaries. These binaries can produce two types of signals: a stochastic gravitational wave background (GWB) or deterministic continuous gravitational waves (CGW). Correctly separating these signals is essential for accurate signal recovery and interpretation. This paper investigates the interaction between GWB and CGW signals within current analysis pipelines, focusing on misinterpretations and biases in parameter estimation when these signals are analyzed separately or together. We conducted several simulations based on the European PTA 24.8-year dataset. First, we injected either a GWB or a CGW. We compared parameter estimation using different search models, including Earth term only, combined Earth and pulsar term CGW templates, and correlated (HD) or uncorrelated (CURN) power law GWB templates. Our findings show that, when searched independently, the GWB and CGW signals can be misinterpreted as each other, and only a combined search can recover the true signal present. For datasets containing both a GWB and a CGW, failure to account for the CGW biases the recovery of the GWB. However, a combined search allows for the recovery of both GWB and CGW parameters without significant bias. Care must be taken with the method used to perform combined searches on these multi-component datasets, as the CGW pulsar term can be misinterpreted as a CURN. This can be avoided by direct searches for an HD correlated GWB plus a CGW. Our study underscores the importance of combined searches to ensure unbiased recovery of GWB parameters in the presence of strong CGWs, which is crucial for interpreting signals recently found in PTA data and represents a step toward a robust framework for disentangling stochastic and deterministic GW signals in future, more sensitive datasets.