NMMA: A nuclear-physics and multi-messenger astrophysics framework to analyze binary neutron star mergers

P. T. H. Pang,Tim Dietrich, M. W. Coughlin,Mattia Bulla,Ingo Tews,Mouza Almualla,Tyler Barna,Weizmann Kiendrebeogo,Nina Kunert, Gargi Mansingh, Brandon Reed,Niharika Sravan, A. M. Toivonen, S. Antier, Robert O. Vandenberg, J. Heinzel,Vsevolod Nedora, Pouyan Salehi, Rakesh Kumar Sharma,Rahul Somasundaram, C. Van Den Broeck

arXiv (Cornell University)(2022)

引用 0|浏览0
暂无评分
摘要
The multi-messenger detection of the gravitational-wave signal GW170817, the corresponding kilonova AT2017gfo and the short gamma-ray burst GRB170817A, as well as the observed afterglow has delivered a scientific breakthrough. For an accurate interpretation of all these different messengers, one requires robust theoretical models that describe the emitted gravitational-wave, the electromagnetic emission, and dense matter reliably. In addition, one needs efficient and accurate computational tools to ensure a correct cross-correlation between the models and the observational data. For this purpose, we have developed the NMMA (Nuclear-physics and Multi-Messenger Astrophysics) framework. The code allows incorporation of nuclear-physics constraints at low densities as well as X-ray and radio observations of isolated neutron stars. It also enables us to classify electromagnetic observations, e.g., to distinguish between supernovae and kilonovae. In previous works, the NMMA code has allowed us to constrain the equation of state of supranuclear dense matter, to measure the Hubble constant, and to compare dense-matter physics probed in neutron-star mergers and in heavy-ion collisions. The extension of the NMMA code presented here is the first attempt of analysing the gravitational-wave signal, the kilonovae, and the GRB afterglow simultaneously, which reduces the uncertainty of our constraints. Incorporating all available information, we estimate the radius of a 1.4 solar mass neutron star to be $R=11.98^{+0.35}_{-0.40}$ km.
更多
查看译文
关键词
neutron,nuclear-physics,multi-messenger
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要