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.
A Characteristic Extraction Tool for Gravitational Waveforms
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abstract
We develop and calibrate a characteristic waveform extraction tool whose major improvements and corrections of prior versions allow satisfaction of the accuracy standards required for advanced LIGO data analysis. The extraction tool uses a characteristic evolution code to propagate numerical data on an inner worldtube supplied by a 3+1 Cauchy evolution to obtain the gravitational waveform at null infinity. With the new extraction tool, high accuracy and convergence of the numerical error can be demonstrated for an inspiral and merger of mass M binary black holes even for an extraction worldtube radius as small as R = 20M. The tool provides a means for unambiguous comparison between waveforms generated by evolution codes based upon different formulations of the Einstein equations and based upon different numerical approximations.
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gr-qc 2years
2026 2verdicts
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Hierarchical Bayesian inference on GWTC-5.0 constrains the memory enhancement factor to 0.26 with large uncertainties consistent with the GR value of 1 and forecasts that 2000 detections are needed for a 1σ constraint away from zero.
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Toward claiming a detection of gravitational memory
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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Constraining Gravitational Wave Memory with Hierarchical Inference
Hierarchical Bayesian inference on GWTC-5.0 constrains the memory enhancement factor to 0.26 with large uncertainties consistent with the GR value of 1 and forecasts that 2000 detections are needed for a 1σ constraint away from zero.