General Relativistic Simulations of Binary Compact Objects

Florida Atlantic University, Boca Raton FL

Investigators

Abstract

Using the moving puncture approach, it is now possible to evolve compact-object binaries through many orbits, merger and the ringdown of the final black hole. The main task has become to accurately model different physical problems. We will use this method to explore more physically realistic situations. In particular, we plan to address several key physics issues such as: (i) How important is neutron star spin in the evolution of neutron star binaries? (ii) How can we best join a very long post-Newtonian in-spiral waveform and a numerically obtained waveform from a compact object binary? (iii) Up to which frequency can post-Newtonian waveforms be trusted, and how does this frequency depend on spins and mass ratios? (iv) Can we get significantly better waveforms if we use more realistic initial data with less artificial "junk" radiation? The NSF's LIGO gravitational wave detector is among a number of new facilities all over the world which are designed to directly detect and measure gravitational waves. These waves will come from a variety of astrophysical sources and will open a new window to the universe. One of the most promising sources for these detectors are the in-spirals and mergers of compact-object binaries (i.e., systems containing black holes or neutron stars). As the two objects get close, fully non-linear numerical simulations of the Einstein equations are required to make predictions about the final part of the in-spiral and subsequent merger. The gravitational waveforms produced by our simulations will be valuable for other scientific groups such as the LIGO collaboration. The planned research will involve at least one graduate student at FAU and one postdoc at the University of Jena. Thus the planned research will have educational benefits for the students and postdocs involved. They will not only learn about the science related to this project, but also more broadly about programming supercomputers and data management.