Unveiling the electrodynamic nature of spacetime collisions

ORAL

Abstract

Gravitational waves from merging binary black holes present exciting opportunities for understanding fundamental aspects of gravity, including nonlinearities in the strong-field regime. One challenge in studying and interpreting the dynamics of binary black hole collisions is the intrinsically geometrical nature of spacetime, which in many ways is unlike that of other classical field theories. By exactly recasting Einstein's equations into a set of coupled nonlinear Maxwell equations closely resembling classical electrodynamics, we visualize the intricate dynamics of gravitational electric and magnetic fields during the inspiral, merger, and ring-down of a binary black hole collision.

*ERM is grateful for discussions with Cynthia Keeler, Mark Scheel and Anatoly Spitkovsky.SB acknowledges support through Caltech's SURF program. JW acknowledges partial support through the David and Barbara Groce graduate fellowship. ERM acknowledges partial support by the National Science Foundation under grants No. PHY-2309210 and AST-2307394.ERM acknowledges the use of Delta at the National Center for Supercomputing Applications (NCSA) through allocation PHY210074 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services \& Support (ACCESS) program, which is supported by National Science Foundation grants \#2138259, \#2138286, \#2138307, \#2137603, and \#2138296. Additional simulations were performed on the NSF Frontera supercomputer under grant AST21006. ERM also acknowledges support through DOE NERSC supercomputer Perlmutter under grant m4575, which uses resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award NP-ERCAP0028480.

Publication: Phys. Rev. Lett. 135, 101401 (2025)
https://doi.org/10.48550/arXiv.2504.15978

Presenters

  • Jiaxi Wu

    • Caltech

Authors

  • Jiaxi Wu

    • Caltech
  • Elias Roland Most

    • Caltech
  • Siddharth Boyeneni

    • Caltech