Improving the NRTidal model for binary neutron star systems
Improving the NRTidal model for binary neutron star systems
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DOI：
10.1103/physrevd.100.044003
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发表时间：
2019-08-01
影响因子：
5
通讯作者：
Tichy, Wolfgang
中科院分区：
文献类型：
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作者：
Dietrich, Tim;Samajdar, Anuradha;Tichy, Wolfgang
准确和快速的引力波形(GW)模型对于提取有关产生GW的致密双星系统的性质的信息至关重要。在前人工作的基础上，我们提出了双中子星(BNS)波形的NRTdal模型的一个扩展。升级是(I)新的封闭形式的潮汐对GW相的贡献，它包含了更多的分析知识，并被校准为比以前更准确的数值相对论数据；(Ii)对GW振幅的潮汐校正；以及(Iii)在四极和八极数量级加入依赖于状态方程的有限尺寸效应的自旋部门的扩展；这些以自旋-自旋尾项和自旋立方项出现，两者都在3.5Pn。我们将新的描述添加到进动双星黑洞波形模型IMRPhenomPv2中，得到了频域进动双中子星模型。此外，我们还扩展了SEOBNRv4_ROM和IMRPhenomD对齐-自旋双核黑洞波形模型，并引入了改进的潮汐位相修正。针对新的IMRPhenomPv2_NRTidalv2近似式，我们通过与数值相对论波形以及潮汐有效一体和数值相对论数据相结合的混合波形的比较来检验该模型。我们还检查了在BNS参数空间的大范围内与潮汐有效一体模型的一致性。
Accurate and fast gravitational waveform (GW) models are essential to extract information about the properties of compact binary systems that generate GWs. Building on previous work, we present an extension of the NRTidal model for binary neutron star (BNS) waveforms. The upgrades are (i) a new closed-form expression for the tidal contribution to the GW phase which includes further analytical knowledge and is calibrated to more accurate numerical relativity data than previously available; (ii) a tidal correction to the GW amplitude; and (iii) an extension of the spin-sector incorporating equation-of-state-dependent finite size effects at quadrupolar and octupolar order; these appear in the spin-spin tail terms and cubic-in-spin terms, both at 3.5 PN. We add the new description to the precessing binary black hole waveform model IMRPhenomPv2 to obtain a frequency-domain precessing binary neutron star model. In addition, we extend the SEOBNRv4_ROM and IMRPhenomD aligned-spin binary black hole waveform models with the improved tidal phase corrections. Focusing on the new IMRPhenomPv2_NRTidalv2 approximant, we test the model by comparing with numerical relativity waveforms as well as hybrid waveforms combining tidal effective-one-body and numerical relativity data. We also check consistency against a tidal effective-one-body model across large regions of the BNS parameter space.