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arxiv: 1906.11936 · v1 · pith:23HC3V3Cnew · submitted 2019-06-27 · 🌌 astro-ph.HE

Prospects for Memory Detection with Low-Frequency Gravitational Wave Detectors

Kristina Islo , Joseph Simon , Sarah Burke-Spolaor , Xavier Siemens This is my paper

Pith reviewed 2026-05-25 14:04 UTC · model grok-4.3

classification 🌌 astro-ph.HE
keywords gravitational wave memorysupermassive black hole binariesLISApulsar timing arraysdetectabilitymerger rates
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The pith

LISA should detect one to ten gravitational wave memory events from supermassive black hole mergers in its four-year mission.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper calculates the chances of detecting gravitational wave memory, a permanent shift in spacetime left by passing waves, from merging supermassive black holes. It concludes that pulsar timing arrays currently have little chance of detection, while LISA should see one to ten such events above a signal-to-noise ratio of five in four years. A sympathetic reader would care because these memory signals encode the cumulative effect of gravitational wave emission, providing a complementary view to standard oscillatory signals and insights into black hole populations.

Core claim

The central claim is that while pulsar timing arrays have poor prospects for detecting memory from supermassive black hole binary coalescences, LISA is likely to see between 1 and 10 such memory events with SNR exceeding 5 within its planned 4-year mission.

What carries the argument

Population synthesis models of supermassive black hole binary mergers combined with signal-to-noise ratio calculations for memory waveforms in LISA and pulsar timing arrays.

If this is right

  • Memory detection would offer a new observational channel for supermassive black hole binaries distinct from the chirp signals.
  • Successful detection would validate the theoretical prediction of gravitational wave memory.
  • The number of detections would constrain the merger rate and mass distribution of supermassive black holes.
  • Non-detection in LISA would imply lower merger rates than assumed in the models.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If LISA detects these events, it could help resolve uncertainties in black hole merger models by providing direct counts.
  • Extending the mission duration would increase the expected number of memory detections proportionally.
  • Combining memory detections with standard gravitational wave observations might allow better characterization of source parameters.

Load-bearing premise

The population synthesis model accurately represents the true rates, masses, and redshifts of supermassive black hole binary mergers.

What would settle it

Observing zero memory events with SNR greater than 5 in the actual LISA data after four years would falsify the prediction of 1 to 10 events.

Figures

Figures reproduced from arXiv: 1906.11936 by Joseph Simon, Kristina Islo, Sarah Burke-Spolaor, Xavier Siemens.

Figure 1
Figure 1. Figure 1: of Begelman et al.) and consider 1.0 ≤ α ≤ 3.0. Addition of lower-mass black holes: Previous simulations of SMBHB populations (such as that in Simon & Burke￾Spolaor) only include progenitor galaxy mass greater than 1010 M which corresponds to individual black hole mass of ∼ 107 M . Lower galaxy masses are likely not relevant PTA￾band sources, but 105 − 107 M black hole binaries can pro￾duce GW memory signa… view at source ↗
Figure 2
Figure 2. Figure 2: shows the SNR for a memory burst produced by SMBHBs of total binary mass Mtot coalescing at redshift z. Expected SNR ranges from 100 to 10,000 with the high￾est SNR events coming from binaries at z < 0.5 and with 105 M < Mtot < 107 M . Our approximated memory model only minimally diverges at higher redshift from the LISA SNRs reported in Favata (2009). Analysis of LISA merg￾ers within the same range of mas… view at source ↗
Figure 3
Figure 3. Figure 3: Cumulative memory burst rate for bursts with strain am￾plitude at or above strain amplitude ∆h (mem) + as in (7) for 100 real￾izations of SMBHB populations. Bold lines in models A and B in￾dicate the mean across simulations using 1.0 ≤ α ≤ 3.0; the shaded regions encapsulates 1 − σ range across these sub-models. Models C and D show a median rate and 1 −σ interval [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Mean number of memory bursts per SNR bin from 100 realizations of SMBHB populations assuming outlined models. Shaded regions encapsulate 1 − σ intervals. Bold lines in models A and B indicate the mean across median rates using 1.0 ≤ α ≤ 3.0; the shaded regions encapsulates 1 −σ range across these sub-models. Models C and D show a median rate and 1 −σ interval. NB: The axes’ units [PITH_FULL_IMAGE:figures/… view at source ↗
Figure 5
Figure 5. Figure 5: Mean memory burst rate by burst redshift and MBBH reduced mass. Upper panel is model A with α = 3.0; bottom panel is model C. Total number of memory events 3.3 and 0.4 per year, respectively. space to include more lower-mass SMBHBs beyond z = 3 will boost our estimates. Here, we restricted our restricted ourselves to within currently resolvable astrophysical param￾eter values. In this context, if < 106 M b… view at source ↗
read the original abstract

Gravitational wave memory is theorized to arise from the integrated history of gravitational wave emission, and manifests as a spacetime deformation in the wake of a propagating gravitational wave. We explore the detectability of the memory signals from a population of coalescencing supermassive black hole binaries with pulsar timing arrays and the Laser Interferometer Space Antenna (LISA). We find that current pulsar timing arrays have poor prospects, but it is likely that between 1 and 10 memory events with signal-to-noise ratio in excess of 5 will occur within LISA's planned 4-year mission.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The paper calculates prospects for detecting gravitational-wave memory from supermassive black-hole binary mergers. It concludes that existing pulsar-timing arrays have negligible sensitivity, while LISA is expected to register between 1 and 10 memory events with SNR > 5 during its nominal 4-year mission. The forecast is obtained by folding a chosen population-synthesis model (merger-rate density, mass function, redshift distribution) into the memory strain integral and counting events above the SNR threshold.

Significance. A robust prediction of 1–10 detectable memory events would constitute a concrete, falsifiable target for LISA data analysis and would link memory searches to the still-uncertain SMBHB merger rate. The manuscript does not, however, demonstrate that the quoted interval survives plausible variations in the input rate density; therefore the result, while interesting, remains tied to a single population model rather than constituting a model-independent forecast.

major comments (1)
  1. [section presenting the LISA event-rate calculation (implicit in the abstract and results)] The central numerical claim (1–10 events with SNR>5) is obtained by integrating a single, fixed merger-rate density over the memory SNR formula. Because the expected count scales linearly with the rate density, any factor-of-three uncertainty—common in the SMBHB literature—moves the predicted number across or below the quoted interval. No marginalization, alternative rate models, or sensitivity plot is provided, so the interval is model-specific rather than a robust prediction.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their review and for identifying the model dependence of the LISA event-rate forecast. We address the major comment below.

read point-by-point responses

  1. Referee: [section presenting the LISA event-rate calculation (implicit in the abstract and results)] The central numerical claim (1–10 events with SNR>5) is obtained by integrating a single, fixed merger-rate density over the memory SNR formula. Because the expected count scales linearly with the rate density, any factor-of-three uncertainty—common in the SMBHB literature—moves the predicted number across or below the quoted interval. No marginalization, alternative rate models, or sensitivity plot is provided, so the interval is model-specific rather than a robust prediction.

    Authors: We agree that the predicted event count scales linearly with the assumed merger-rate density and that our calculation is performed for a single, fixed population-synthesis model. The 1–10 range quoted in the abstract and results arises from integrating that model over the distributions of binary masses and redshifts. The manuscript already states that a chosen population-synthesis model is employed, so the forecast is presented as model-specific rather than model-independent. We will revise the text to (i) explicitly note the linear scaling with rate normalization and (ii) reference the factor-of-a-few uncertainties typical in the SMBHB literature, allowing readers to rescale the prediction for their preferred rate density. A full marginalization or sensitivity plot across alternative rate models would require additional population-synthesis calculations beyond the scope of the present work. revision: partial

Circularity Check

0 steps flagged

No significant circularity; forecast uses external population models as inputs

full rationale

The paper's central numerical claim (1-10 LISA events with SNR>5) is obtained by integrating an assumed SMBHB population synthesis model through the memory SNR calculation. This is a standard forward-model forecast, not a derivation that reduces to its own outputs by construction. No equations or sections exhibit self-definitional loops, fitted parameters from this work renamed as predictions, or load-bearing self-citations whose content is unverified. The result is model-dependent by design, but the derivation chain remains independent of the target count and does not tautologically reproduce its inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review supplies no explicit free parameters, axioms, or invented entities; the central numerical claim necessarily rests on an unstated population model whose details are unavailable.

pith-pipeline@v0.9.0 · 5625 in / 1090 out tokens · 22055 ms · 2026-05-25T14:04:31.015365+00:00 · methodology

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Forward citations

Cited by 4 Pith papers

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

  1. Search for Gravitational Wave Memory in PPTA and EPTA Data: A Complete Signal Model

    gr-qc 2025-12 unverdicted novelty 7.0

    Searches rule out SMBHB mergers with chirp mass 10^10 solar masses up to 700 Mpc and generic memory bursts with strain amplitudes above 10^-14 at 95% credibility.

  2. 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.

  3. Probing soft signals of gravitational-wave memory with space-based interferometers

    gr-qc 2026-03 conditional novelty 5.0

    Space-based detectors can measure soft displacement-memory signals from gravitational waves at SNR greater than or equal to 10.

  4. Unveiling the Gravitational Universe at \mu-Hz Frequencies

    astro-ph.IM 2019-08 unverdicted novelty 5.0

    Proposal for a μ-Hz space-based gravitational wave interferometer to observe massive black hole binaries in early inspiral and low-frequency galactic binaries.

Reference graph

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