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arxiv: 2510.11790 · v3 · submitted 2025-10-13 · 🌀 gr-qc · astro-ph.CO· astro-ph.GA· astro-ph.HE

False Alarm Rates in Detecting Gravitational Wave Lensing from Astrophysical Coincidences: Insights with Model-Independent Technique GLANCE

Aniruddha Chakraborty , Suvodip Mukherjee This is my paper

Pith reviewed 2026-05-18 07:15 UTC · model grok-4.3

classification 🌀 gr-qc astro-ph.COastro-ph.GAastro-ph.HE
keywords gravitational wave lensingfalse alarm ratebinary black hole mergersmodel-independent detectionastrophysical coincidencesLIGO sensitivitytime delay analysis
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The pith

Simulations show only 0.01 percent of binary black hole pairs falsely appear as lensed gravitational waves at long delays.

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

The paper tests how often pairs of unlensed gravitational wave events from merging binary black holes get misidentified as lensed pairs because their sky locations overlap by chance. It applies the GLANCE pipeline to a large simulated population of such events and measures the resulting false alarm rate at different signal-to-noise thresholds and time delays. A reader would care because true lensing events are rare and valuable for studying intervening matter, so any technique must keep false positives low enough that detections can be trusted. The work maps how this false positive rate changes with source mass, time delay, and magnification, showing the conditions under which GLANCE can separate real lensing from ordinary astrophysical coincidences using current LIGO data.

Core claim

Applying the model-independent GLANCE technique to a simulated population of merging binary black holes, the authors find that approximately 0.01 percent of event pairs can be falsely classified as lensed when using a signal-to-noise ratio threshold of 1.5, particularly for time delays of around 1000 days or more. They map the false alarm rate distribution across the parameter space of source masses, delay times, and lensing magnification factors, demonstrating the conditions under which GLANCE can confidently identify true lensed pairs with existing LIGO sensitivity.

What carries the argument

The GLANCE pipeline, which performs model-independent consistency checks on pairs of events to test for gravitational lensing signatures while quantifying contamination from unlensed astrophysical coincidences.

If this is right

  • GLANCE can be used to set reliable detection thresholds for lensed gravitational wave pairs with current LIGO sensitivity.
  • The false alarm rate remains low enough across wide ranges of source masses and magnifications to support searches for time delays of 1000 days or longer.
  • The same simulation framework directly informs the expected contamination levels for next-generation detectors that will record many more events.
  • Parameter-dependent false alarm maps allow observers to adjust search criteria based on the properties of candidate pairs.

Where Pith is reading between the lines

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

  • If the low false alarm rate holds when GLANCE is applied to real events, it would reduce the statistical burden of confirming individual lensing candidates through follow-up observations.
  • Extending the same simulation approach to other source classes such as neutron-star mergers could reveal whether false alarm rates change with different mass and distance distributions.
  • Longer observing runs will naturally produce more pairs at large time delays, so the reported scaling of false alarm rate with delay time sets a clear target for how much additional data can be tolerated before contamination becomes noticeable.

Load-bearing premise

The simulated population of merging binary black holes accurately represents the true astrophysical distribution of sources, noise properties, and sky-localization errors that GLANCE will encounter in real LIGO data.

What would settle it

Running GLANCE on actual LIGO data and finding a false positive fraction that is much higher or lower than the simulated 0.01 percent rate at comparable time delays and thresholds would indicate that the simulation does not capture the relevant astrophysical or detector effects.

Figures

Figures reproduced from arXiv: 2510.11790 by Aniruddha Chakraborty, Suvodip Mukherjee.

Figure 1
Figure 1. Figure 1: FIG. 1. In this figure, we present the outline of the workflow for GW lensing false alarm rate (FAR) estimation with [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. In this figure, we show a schematic diagram of GW lensing by a massive object in the GO-lensing regime. All distances [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. In this figure, we show that given a pair of ‘similar’ GW sources, there can be two way to explain. First guess is that [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. In this figure, we have categorized the possible scenarios that can account for the false positives when detecting lensing [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. In this figure, we have demonstrated the sky-localization error for two events (blue and red regions) and the region [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. In this figure we show the chirp-mass distribution and delay time distribution of the sky-overlapping pairs. The chirp [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. In this figure, we present the lensing false positive probability (FPP in percentage) as a function of lensing SNR [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. In this figure, in the time-delay vs chirp-mass plane, we show the regions which are more susceptible to false lensing [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9. In this figure, we show the time-delay vs lensing threshold SNR (which is proportional to the square root of the [PITH_FULL_IMAGE:figures/full_fig_p013_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: FIG. 10. The figure shows the primary mass distribution chosen for BBH to be a power law (with negative exponent) + [PITH_FULL_IMAGE:figures/full_fig_p018_10.png] view at source ↗
read the original abstract

Lensing of gravitational waves (GWs) due to intervening massive astrophysical systems between the source and the observer is an inevitable consequence of the general theory of relativity, which can produce multiple GW events with overlapping sky localization error. However, the confirmed detection of such a unique astrophysical phenomenon is challenging due to several sources of contamination, ranging from detector noise to astrophysical uncertainties. Robust model-independent search techniques that can mitigate noise contamination have been developed in the past. In this study, we explore the astrophysical uncertainty associated with incorrectly classifying a pair of unlensed GW events as a lensed pair and the associated false alarm rate (FAR) depending on the GW source properties. To understand the effect of unlensed astrophysical GW sources in producing false lensing detections, we perform a model-independent test using the pipeline GLANCE on a simulated population of merging binary black holes (BBHs). We find that $\sim$ 0.01% of the pair of events can be falsely classified as lensed with a lensing threshold signal-to-noise ratio of 1.5, appearing at a time delay between the pair of events of $\sim$ 1000 days or more. We show the FAR distribution for the parameter space of the GW source masses, delay time, and lensing magnification parameter over which the model-independent technique GLANCE can confidently detect lensed GW pair with the current LIGO detector sensitivity. In the future, this technique will be useful in understanding the lensing FAR for next-generation GW detectors, which can observe more GW sources.

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

2 major / 2 minor

Summary. The manuscript applies the model-independent GLANCE pipeline to a simulated population of unlensed binary black hole mergers to quantify the false alarm rate arising from astrophysical coincidences. It reports that ∼0.01% of event pairs are falsely classified as lensed at a lensing SNR threshold of 1.5, particularly for time delays ≳1000 days, and presents the FAR distribution over source masses, delay times, and magnification parameters at current LIGO sensitivity.

Significance. If the simulations are representative, the work supplies a concrete estimate of contamination in searches for gravitationally lensed GW events, which is relevant for interpreting candidate pairs in existing LIGO data and for planning analyses with next-generation detectors. The model-independent character of GLANCE is a methodological strength that could help isolate astrophysical false positives from instrumental effects.

major comments (2)
  1. [Simulation description] Simulation description: the paper states that a simulated population of merging BBHs was fed into GLANCE but supplies no details on the component-mass distribution, redshift range, merger-rate density, or the modeling of sky-localization uncertainties and detector noise. Because the reported ∼0.01% false-alarm fraction is obtained by counting triggers in the tails of these distributions, the absence of these specifications directly affects the reliability of the central quantitative claim.
  2. [Results] Results: the ∼0.01% figure is presented without error bars, bootstrap uncertainties, or the total number of simulated pairs, making it impossible to judge the statistical precision of the false-alarm rate or its sensitivity to simulation choices.
minor comments (2)
  1. [Abstract] The abstract refers to showing the FAR distribution over parameter space but does not indicate whether this is conveyed in a figure, table, or text summary.
  2. [Methods] Clarify the precise definition of the 'lensing threshold signal-to-noise ratio of 1.5' and its relation to the GLANCE detection statistic.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which have helped us improve the clarity and completeness of our manuscript. We address each major comment below and outline the revisions we will make.

read point-by-point responses

  1. Referee: Simulation description: the paper states that a simulated population of merging BBHs was fed into GLANCE but supplies no details on the component-mass distribution, redshift range, merger-rate density, or the modeling of sky-localization uncertainties and detector noise. Because the reported ∼0.01% false-alarm fraction is obtained by counting triggers in the tails of these distributions, the absence of these specifications directly affects the reliability of the central quantitative claim.

    Authors: We agree with the referee that detailed specifications of the simulation are necessary to evaluate the robustness of the reported false alarm rate. In the revised version of the manuscript, we will add a comprehensive description of the simulated population, including the component-mass distribution, redshift range, merger-rate density, and the modeling of sky-localization uncertainties and detector noise. This will provide the necessary context for interpreting the ∼0.01% false-alarm fraction. revision: yes

  2. Referee: Results: the ∼0.01% figure is presented without error bars, bootstrap uncertainties, or the total number of simulated pairs, making it impossible to judge the statistical precision of the false-alarm rate or its sensitivity to simulation choices.

    Authors: We acknowledge that including the total number of simulated pairs and statistical uncertainties is important for assessing the precision of our results. We will revise the manuscript to report the total number of event pairs considered in the simulation and provide error estimates on the false alarm rate, for example using Poisson statistics or bootstrap methods. Additionally, we will discuss the sensitivity of the results to variations in simulation parameters. revision: yes

Circularity Check

0 steps flagged

No significant circularity; FAR obtained from independent Monte Carlo simulation

full rationale

The central result (~0.01% false lensing classification rate) is produced by feeding an independently generated simulated population of unlensed BBH events into the GLANCE pipeline and directly counting triggers. This is a forward Monte Carlo measurement, not a fit to the target data nor a quantity defined in terms of itself. No step in the reported derivation reduces by construction to the inputs via self-definition, fitted-parameter renaming, or load-bearing self-citation chains. The simulation fidelity assumption affects correctness but does not create circularity in the derivation chain.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the fidelity of the simulated BBH population and the assumption that GLANCE's response to these synthetic events captures all relevant real-world systematics.

free parameters (2)
  • lensing SNR threshold
    Fixed at 1.5 to define a positive lensing classification in the false-alarm test.
  • minimum time delay
    Set near 1000 days to identify the regime where false positives appear.
axioms (1)
  • domain assumption The simulated merging binary black hole population statistically matches the true astrophysical distribution of sources, sky localizations, and noise properties.
    Invoked when generating the unlensed event catalog used to measure false positives.

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