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Ordering the confusion: A study of the impact of lens models on gravitational-wave lensing detection capabilities
General Relativity and Quantum Cosmology · Submitted 23 May 2022
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim We also show that slight variations in the profile of the lens model are tolerable but a model with incorrect assumptions about the underlying lens population causes significant errors compared to assuming no lens model at all.
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The abstract, sentence by sentence
When traveling from their source to the observer, gravitational waves can get deflected by massive objects along their travel path. When the lens is massive enough and the source aligns closely with the line-of-sight to the lens, the wave undergoes strong lensing, leading to several images with the same frequency evolution. These images are separated in time, magnified, and can undergo an overall phase shift. Searches for strongly-lensed gravitational waves are already ongoing. In essence, such searches look for events originating from the same sky location and having the same detector frame parameters. However, the agreement between these quantities can also happen by chance, leading to an important confusion background. To reduce the overlap between background and foreground, one can include lensing models, enforcing the lensing parameters to also be consistent with our expectations. In principle, such models should decrease the confusion background. However, when doing realistic searches, one does not know which model is the correct one. The use of an incorrect model could lead to the non-detection of genuinely lensed events. In this work, we investigate under realistic conditions how one can identify lensed events in the unlensed background. We focus on the impact of the addition of a model for the lens density profile and investigate the effect of potential errors in the modelling. We show that it is extremely difficult to identify lensing confidently without the addition of a lens model. We also show that slight variations in the profile of the lens model are tolerable but a model with incorrect assumptions about the underlying lens population causes significant errors compared to assuming no lens model at all. We also suggest some strategies to improve the confidence in the detection of strong lensing for gravitational waves.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | When traveling from their source to the observer, gravitational waves can get deflected by massive objects along their travel path. | background 1.00 | 0.04 | 0.01 | asserted 0.51 |
| s1 | When the lens is massive enough and the source aligns closely with the line-of-sight to the lens, the wave undergoes strong lensing, leading to several images with the same frequency evolution. | background 1.00 | 0.04 | 0.02 | asserted 0.95 |
| s2 | These images are separated in time, magnified, and can undergo an overall phase shift. | background 1.00 | 0.05 | 0.02 | asserted 0.74 |
| s3 | Searches for strongly-lensed gravitational waves are already ongoing. | background 1.00 | 0.05 | 0.02 | asserted 1.00 |
| s4 | In essence, such searches look for events originating from the same sky location and having the same detector frame parameters. | background 0.83 | 0.08 | 0.02 | asserted 0.99 |
| s5 | However, the agreement between these quantities can also happen by chance, leading to an important confusion background. | background 0.96 | 0.09 | 0.03 | asserted 0.85 |
| s6 | To reduce the overlap between background and foreground, one can include lensing models, enforcing the lensing parameters to also be consistent with our expectations. | method 0.71 | 0.06 | 0.06 | hedged possibility 0.97 |
| s7 | In principle, such models should decrease the confusion background. | background 0.88 | 0.06 | 0.06 | hedged possibility 0.74 |
| s8 | However, when doing realistic searches, one does not know which model is the correct one. | background 0.59 | 0.07 | 0.03 | asserted 0.99 |
| s9 | The use of an incorrect model could lead to the non-detection of genuinely lensed events. | background 0.80 | 0.06 | 0.06 | hedged possibility 1.00 |
| s10 | In this work, we investigate under realistic conditions how one can identify lensed events in the unlensed background. | contribution 1.00 | 0.73 | 0.05 | asserted 0.66 |
| s11 | We focus on the impact of the addition of a model for the lens density profile and investigate the effect of potential errors in the modelling. | contribution 0.81 | 0.57 | 0.05 | asserted 0.52 |
| s12 | We show that it is extremely difficult to identify lensing confidently without the addition of a lens model. | result 1.00 | 0.93 | 0.43 | asserted 1.00 |
| s13 | We also show that slight variations in the profile of the lens model are tolerable but a model with incorrect assumptions about the underlying lens population causes significant errors compared to assuming no lens model at all. | result 0.99 | 0.94 | 0.67 | asserted 1.00 |
| s14 | We also suggest some strategies to improve the confidence in the detection of strong lensing for gravitational waves. | future work 0.89 | 0.60 | 0.07 | hedged possibility 0.99 |
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The paper
Original abstract
When traveling from their source to the observer, gravitational waves can get deflected by massive objects along their travel path. When the lens is massive enough and the source aligns closely with the line-of-sight to the lens, the wave undergoes strong lensing, leading to several images with the same frequency evolution. These images are separated in time, magnified, and can undergo an overall phase shift. Searches for strongly-lensed gravitational waves are already ongoing. In essence, such searches look for events originating from the same sky location and having the same detector frame parameters. However, the agreement between these quantities can also happen by chance, leading to an important confusion background. To reduce the overlap between background and foreground, one can include lensing models, enforcing the lensing parameters to also be consistent with our expectations. In principle, such models should decrease the confusion background. However, when doing realistic searches, one does not know which model is the correct one. The use of an incorrect model could lead to the non-detection of genuinely lensed events. In this work, we investigate under realistic conditions how one can identify lensed events in the unlensed background. We focus on the impact of the addition of a model for the lens density profile and investigate the effect of potential errors in the modelling. We show that it is extremely difficult to identify lensing confidently without the addition of a lens model. We also show that slight variations in the profile of the lens model are tolerable but a model with incorrect assumptions about the underlying lens population causes significant errors compared to assuming no lens model at all. We also suggest some strategies to improve the confidence in the detection of strong lensing for gravitational waves.
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References
How the literature uses it
4 arXiv papers cite this in 4 sentences
What it cites · 19 sentences without a confident label
Uses the method or tool of 1 paper
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For the $$ scenario, we use the same approach as in [ref] , where the unlensed time delay is modeled as a Poissonian process.
Identifying strongly lensed gravitational wave signals from binary black hole mergers · Population analyses · 0.96
Uses data or values from 1 paper
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We use data from three different catalogs for the lensed models: the $$ time-delay distribution [ref] , the $$ time-delay and relative magnification distribution [ref] , and the $$ time-delay and relative magnification distribution [ref] [We used the code base from [ref] but adapted the detector networks and their sensitivity to match our situation.].
Identifying strongly lensed gravitational wave signals from binary black hole mergers · Population analyses · 0.93
Compares with 1 paper
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First, we have compared the performances of with the results of the posterior overlap method [ref] , showing that comparing the strains and ascertaining the match between all the parameters decreases significantly the false-alarm probability.
Identifying strongly lensed gravitational wave signals from binary black hole mergers · Conclusions · 0.99
Cites as support 1 paper
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This should decrease the confusion region where the background and the foreground overlap and hence the FAP [ref] .
Identifying strongly lensed gravitational wave signals from binary black hole mergers · Including the correct model · 0.96
Cites as background 6 papers
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In parallel with the characterization of the FAP, there have also been efforts to find the expected characteristics of strongly-lensed GWs [ref] .
Identifying strongly lensed gravitational wave signals from binary black hole mergers · Introduction · 0.96
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This does not include any selection effects which would include information about the population effects in the lensed and unlensed hypotheses; see [ref] for more information on selection effects.
Bayesian statistical framework for identifying strongly lensed gravitational-wave signals · Bayesian analysis for strong gravitational wave lensing · 0.92
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Finally, the wave can also undergo an overall phase shift, called the Morse phase, translated by a discrete Morse factor $n_j$ [ref] .
On the waveforms of gravitationally lensed gravitational waves · Strong gravitational wave lensing · 0.99
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