Searching for lensed gravitational waves with unlensed templates

Gravitational lensing can split the signal of a binary merger into two images, which either overlap and interfere or arrive as separate events.

By Wadekar, Zackay, Cheung +7Oct 19, 2026

Score████░░░░░░4.3

Key numbers

150 times faster than an explicit
4x for the strongly down-ranked
67 % captured by unlensed templates

Caveats

Preprint; not yet peer reviewed.

VerdictWorth a reader's time today.

Read the original PDF Code

Abstract

Gravitational lensing can split the signal of a binary merger into two images, which either overlap and interfere or arrive as separate events. We show that the matched-filter output of every two-image template can be straightforwardly constructed from the signal-to-noise ratio (SNR) time series that searches already compute with unlensed templates. This enables a marginalized detection statistic that increases search sensitivity without additional matched filtering and is more than 150 times faster than an explicit lensed template bank. For overlapping images in the geometric-optics regime, our two-image method recovers gtrsim97% of the optimal SNR from point-mass and singular isothermal lenses, compared with as little as 67% captured by unlensed templates, with substantial gains also for Chang-Refsdal and cored isothermal lenses. Overlapping lensed signals moreover fail the signal-consistency test that is used to down-rank noise transients. Our two-image method restores the consistency and increases the sensitive volume by roughly $2$-4× for the strongly down-ranked signals. For separated images, our method enables an efficient coherent search for pairs in which neither image is significant alone. Near fold caustics, this increases the sensitive volume by factors of 1.8-2.6 over requiring two independent detections, and up to 1.6 over a targeted counterpart search. Our method is applicable to any matched-filtering search.

Digvijay Wadekar, Barak Zackay, Mark Ho-Yeuk Cheung, Tousif Islam, Javier Roulet, Ajit Kumar Mehta, Tejaswi Venumadhav, Jonathan Mushkin, Miguel Zumalacarregui, Matias Zaldarriaga

The editor's rubric

Heuristic review

Leverage3 / 5: A method or resource many groups across the field will adopt within a year.; 18% of this desk’s rubric
Magnitude3 / 5: Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.; 20% of this desk’s rubric
Evidence3 / 5: Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.; 22% of this desk’s rubric
Novelty2 / 5: A new combination of known ideas.; 22% of this desk’s rubric
Trajectory2 / 5: Some room to improve with obvious engineering.; 10% of this desk’s rubric
Stakes2 / 5: Benefits a professional community (practitioners, clinicians, engineers).; 8% of this desk’s rubric

Dimension	Level	Weight	What that level means
Leverage	███░░ 3	18%	A method or resource many groups across the field will adopt within a year.
Magnitude	███░░ 3	20%	Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
Evidence	███░░ 3	22%	Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
Novelty	██░░░ 2	22%	A new combination of known ideas.
Trajectory	██░░░ 2	10%	Some room to improve with obvious engineering.
Stakes	██░░░ 2	8%	Benefits a professional community (practitioners, clinicians, engineers).

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we report); gains (x-fold); verification (false alarm rate, independent replication, code released); scale (efficient).

How the score was computed

rank-2026-10-18

Score████░░░░░░4.3

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit: 5.2 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.5 / 10; Shrunk toward the desk prior by editor confidence (40%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 91%; Half-life decay since publication.

No attention signals recorded yet.

The record

Reviewed by heuristic-v7 on Oct 20, 2026, 07:29 UTC. Paper type: method.
Categories: gr-qc, astro-ph.CO, astro-ph.GA, astro-ph.IM
TOP, No.4 in the Physics edition of October 20, 2026.