A new numerical relativity-inspired method achieves exponential convergence for scalar self-force calculations in Kerr spacetime on circular equatorial orbits up to near-extremal spins and the ISCO.
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A Gaussian Process Regression model trained on an archive of eccentricity-reduced binary black hole simulations predicts initial conditions that achieve low eccentricity with zero or one iteration.
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Self-force calculations with numerical relativity methods
A new numerical relativity-inspired method achieves exponential convergence for scalar self-force calculations in Kerr spacetime on circular equatorial orbits up to near-extremal spins and the ISCO.
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Data-Driven Acceleration of Eccentricity Reduction for Binary Black Hole Simulations
A Gaussian Process Regression model trained on an archive of eccentricity-reduced binary black hole simulations predicts initial conditions that achieve low eccentricity with zero or one iteration.