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arxiv: 1004.4209 · v2 · pith:QDAFWA3Pnew · submitted 2010-04-23 · 🌀 gr-qc

Gravitational memory in binary black hole mergers

classification 🌀 gr-qc
keywords memoryblackbinaryduringgravitationalholesmergernonlinear
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In addition to the dominant oscillatory gravitational wave signals produced during binary inspirals, a non-oscillatory component arises from the nonlinear "memory" effect, sourced by the emitted gravitational radiation. The memory grows significantly during the late inspiral and merger, modifying the signal by an almost step-function profile, and making it difficult to model by approximate methods. We use numerical evolutions of binary black holes to evaluate the nonlinear memory during late-inspiral, merger and ringdown. We identify two main components of the signal: the monotonically growing portion corresponding to the memory, and an oscillatory part which sets in roughly at the time of merger and is due to the black hole ringdown. Counter-intuitively, the ringdown is most prominent for models with the lowest total spin. Thus, the case of maximally spinning black holes anti-aligned to the orbital angular momentum exhibits the highest signal-to-noise (SNR) for interferometric detectors. The largest memory offset, however, occurs for highly spinning black holes, with an estimated value of h^tot_20 \approx 0.24 in the maximally spinning case. These results are central to determining the detectability of nonlinear memory through pulsar timing array measurements.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Toward claiming a detection of gravitational memory

    gr-qc 2026-01 unverdicted novelty 6.0

    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.

  2. Finding Supermassive Black Hole Binary Mergers in Pulsar Timing Array Data

    astro-ph.HE 2025-10 conditional novelty 6.0

    A complete SMBHB waveform model enables unified PTA searches for mergers and memory signals, with parameter recovery shown on simulated data for 10^8-10^10 solar mass systems.