Cauchy Characteristic Matching
APA
Ma, S. (2023). Cauchy Characteristic Matching. Perimeter Institute. https://pirsa.org/23090094
MLA
Ma, Sizheng. Cauchy Characteristic Matching. Perimeter Institute, Sep. 14, 2023, https://pirsa.org/23090094
BibTex
@misc{ pirsa_PIRSA:23090094, doi = {10.48660/23090094}, url = {https://pirsa.org/23090094}, author = {Ma, Sizheng}, keywords = {Strong Gravity}, language = {en}, title = {Cauchy Characteristic Matching}, publisher = {Perimeter Institute}, year = {2023}, month = {sep}, note = {PIRSA:23090094 see, \url{https://pirsa.org}} }
Two major approaches are used when numerically solving the Einstein field equations. The first one is to use spatial Cauchy slices and treat the system as a standard Cauchy initial value problem. Cauchy-characteristic evolution (CCE) serves as the second approach, which evolves spacetime based on null hypersurfaces. The Cauchy formulation is suitable for the strong field region but is computationally expensive to extend to the wave zone, whereas the Characteristic approach is fast in the wave zone but fails near the binary system where the null surfaces are ill-defined. By combining those two techniques — simulating the inner region with Cauchy evolution and the outer region with CCE, Cauchy-Characteristic matching (CCM) enables us to take advantage of both methods. In this talk, I present our recent implementation of CCM based on a numerical relativity code SpECTRE. I also discuss how CCM improves the accuracy of Cauchy boundary conditions — a benefit that allows us to evolve less of the wave zone in the Cauchy code without losing precision.
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Zoom link https://pitp.zoom.us/j/98246275227?pwd=QWtmUDNkMlF6bXROLzBoYXVVTGpldz09