Gravitational memory from hairy binary black hole mergers in scalar-Gauss-Bonnet gravity differs from GR by a few percent due to altered nonlinear dynamics, with direct scalar contributions suppressed, and including memory increases GR-sGB mismatch by more than an order of magnitude.
Cauchy-characteristic extraction in numerical relativity
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abstract
We treat the calculation of gravitational radiation using the mixed timelike-null initial value formulation of general relativity. The determination of an exterior radiative solution is based on boundary values on a timelike worldtube $\Gamma$ and on characteristic data on an outgoing null cone emanating from an initial cross-section of $\Gamma$. We present the details of a 3-dimensional computational algorithm which evolves this initial data on a numerical grid, which is compactified to include future null infinity as finite grid points. A code implementing this algorithm is calibrated in the quasispherical regime. We consider the application of this procedure to the extraction of waveforms at infinity from an interior Cauchy evolution, which provides the boundary data on $\Gamma$. This is a first step towards Cauchy-characteristic matching in which the data flow at the boundary $\Gamma$ is two-way, with the Cauchy and characteristic computations providing exact boundary values for each other. We describe strategies for implementing matching and show that for small target error it is much more computationally efficient than alternative methods.
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A framework using scale separation in the Isaacson description defines observable gravitational memory rise for compact binary coalescences, providing a basis for hypothesis testing in LISA data.
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Gravitational Memory from Hairy Binary Black Hole Mergers
Gravitational memory from hairy binary black hole mergers in scalar-Gauss-Bonnet gravity differs from GR by a few percent due to altered nonlinear dynamics, with direct scalar contributions suppressed, and including memory increases GR-sGB mismatch by more than an order of magnitude.
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Toward claiming a detection of gravitational memory
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