Paper Citation Record · LEDGER

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators

As of 12 July 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2604.07438.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2604.07438 v1

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Outbound references

Observation 6a7ecb6f-0654-4e7a-9ea3-616200660504 · outbound

This paper cites A., Marshall, P., & Oguri, M.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators A., Marshall, P., & Oguri, M

Reference 1

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.149480Z

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Observation c01a8efa-664f-40ed-9c5c-5b6392111077 · outbound

This paper cites P., & Turok, N.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators P., & Turok, N

Reference 2

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.155930Z

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Observation 1145235c-5fab-4f57-a223-73ba30e2de54 · outbound

This paper cites Constraining Effective Field Theories with Machine Learning.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Constraining Effective Field Theories with Machine Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:31:01.866476Z

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Observation 2daf26ea-7c4a-403b-943c-514a18771c3f · outbound

This paper cites Mining gold from implicit models to improve likelihood-free inference.Proceedings of the National Academy of Sciences, 117(10):5242–5249.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Mining gold from implicit models to improve likelihood-free inference.Proceedings of the National Academy of Sciences, 117(10):5242–5249

Reference 4

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.161971Z

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Observation 37ddfa1b-f320-4e85-94b8-ad099a377c03 · outbound

This paper cites 2019, ApJ, 886, 49, doi: 10.3847/1538-4357/ab4c41 Campeau-Poirier, `E., Perreault-Levasseur, L., Coogan, A., & Hezaveh, Y.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2019, ApJ, 886, 49, doi: 10.3847/1538-4357/ab4c41 Campeau-Poirier, `E., Perreault-Levasseur, L., Coogan, A., & Hezaveh, Y

Reference 5

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.089641Z

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Observation e7bd6336-e18f-42a9-9012-9ceb62a3dbd4 · outbound

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LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Unresolved cited work

Reference 6

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.100458Z

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Observation 1509782a-dda1-4a4a-91b5-dcd34a893292 · outbound

This paper cites One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:31:01.859408Z

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Observation f6fc0a4d-48f6-4154-bdea-ff41216581df · outbound

This paper cites Approximating Likelihood Ratios with Calibrated Discriminative Classifiers.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Approximating Likelihood Ratios with Calibrated Discriminative Classifiers

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T20:50:49.146323Z

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Observation e5b9c0c7-1ab2-4295-8a60-d51a5206fa0c · outbound

This paper cites 2007, title Formation and Evolution of Galaxy Dark Matter Halos and Their Substructure , , 667, 859, 10.1086/520573.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2007, title Formation and Evolution of Galaxy Dark Matter Halos and Their Substructure , , 667, 859, 10.1086/520573

Reference 9

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.059930Z

Source-reported events for the cited work

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Observation cf9c2bd2-2bb5-48eb-8cbf-66b071acf880 · outbound

This paper cites 2025a, arXiv e-prints, arXiv:2511.13669, doi: 10.48550/arXiv.2511.13669.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025a, arXiv e-prints, arXiv:2511.13669, doi: 10.48550/arXiv.2511.13669

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:50:49.067269Z

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Observation 06151a8f-e9fd-4bc2-aab2-e8ff526466d7 · outbound

This paper cites 2025b, AJ, 170, 44, doi: 10.3847/1538-3881/add99f.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025b, AJ, 170, 44, doi: 10.3847/1538-3881/add99f

Reference 11

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.063189Z

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Observation 0702fe5e-f139-4b55-b7dd-d9c3dcd3e01a · outbound

This paper cites Ferreira, Ultra-light dark matter, The Astronomy and Astrophysics Review29, 10.1007/s00159-021-00135-6 (2021).

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Ferreira, Ultra-light dark matter, The Astronomy and Astrophysics Review29, 10.1007/s00159-021-00135-6 (2021)

Reference 12

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.050944Z

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Observation 6a4a757c-e8fe-4765-9808-fec1510b1089 · outbound

This paper cites 2025, ApJ, 989, 226, doi: 10.3847/1538-4357/adee20.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, ApJ, 989, 226, doi: 10.3847/1538-4357/adee20

Reference 13

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.054018Z

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Observation 010cc75a-d208-4cad-a507-2c55841069f5 · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 14

Resolution: metadata mismatch; doi, observed 2026-05-10T20:50:49.073251Z

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Observation 91f2261b-1add-46a8-a235-c2365e22da6f · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 15

Resolution: metadata mismatch; doi, observed 2026-05-10T20:50:49.057025Z

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Observation 4e3e4c58-6eef-44bc-9b0f-4068d95b94fb · outbound

This paper cites Deep residual learning for image recognition.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Deep residual learning for image recognition

Reference 16

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Observation 2629c668-f013-4162-a492-ab05b7e7b65a · outbound

This paper cites D., Dalal, N., Marrone, D.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators D., Dalal, N., Marrone, D

Reference 17

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.104238Z

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Observation 0677d3c5-62ae-4627-bd36-b482473d5853 · outbound

This paper cites Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Parameter Results.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Parameter Results

Reference 18

Resolution: metadata mismatch; doi, observed 2026-05-10T20:50:49.039142Z

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Observation a6c4cdf8-e296-49ab-ae6a-4efffa86e5a7 · outbound

This paper cites 2018, title Modeling evolution of dark matter substructure and annihilation boost , , 97, 123002, 10.1103/PhysRevD.97.123002.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2018, title Modeling evolution of dark matter substructure and annihilation boost , , 97, 123002, 10.1103/PhysRevD.97.123002

Reference 19

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.030507Z

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Observation 9e207872-bbbb-4a98-8f68-1b99bedec5c0 · outbound

This paper cites B., Nightingale, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators B., Nightingale, J

Reference 20

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Observation e3ac5a60-5c43-4594-a708-a00902abc17e · outbound

This paper cites 85(6):1158--1161.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 85(6):1158--1161

Reference 21

Resolution: metadata mismatch; doi, observed 2026-05-10T20:50:49.125263Z

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Observation bd6acea8-4895-425a-9f97-c1f04e56be1e · outbound

This paper cites Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:50:49.133151Z

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Observation f532eecd-815d-49df-aaba-92102c4945d5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Adam: A Method for Stochastic Optimization

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T20:50:49.047881Z

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Observation 7884a8c8-3528-4ed0-8bd0-70bb01f84f3b · outbound

This paper cites 2007, ApJ, 671, 1135, doi: 10.1086/522878.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2007, ApJ, 671, 1135, doi: 10.1086/522878

Reference 24

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.122114Z

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Observation a3a7a052-b529-4236-b147-bcbfce3a166d · outbound

This paper cites 2022, A&A, 668, A166, doi: 10.1051/0004-6361/202244978 LSST Science Collaboration, Abell, P.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2022, A&A, 668, A166, doi: 10.1051/0004-6361/202244978 LSST Science Collaboration, Abell, P

Reference 25

Resolution: verified exact; doi, observed 2026-05-10T17:40:40.685040Z

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Observation ccc7bf6f-a73c-4773-9b9d-d4e414266025 · outbound

This paper cites F., Frenk C.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators F., Frenk C

Reference 26

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.042152Z

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Observation 8a135a7d-fc61-402e-9a50-6244f0d81095 · outbound

This paper cites 2025, JCAP, 2025, 053, doi: 10.1088/1475-7516/2025/05/053.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, JCAP, 2025, 053, doi: 10.1088/1475-7516/2025/05/053

Reference 27

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.114388Z

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Observation cb9ce653-909f-4ef6-bfc9-0406387bd1c0 · outbound

This paper cites K., & Poulin, V.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators K., & Poulin, V

Reference 28

Resolution: verified exact; doi, observed 2026-05-10T17:40:40.683152Z

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Observation dad5aff4-30ab-42d7-80ed-c49c243d323b · outbound

This paper cites 2014, ApJL, 793, L10, doi: 10.1088/2041-8205/793/1/L10 S´ ersic, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2014, ApJL, 793, L10, doi: 10.1088/2041-8205/793/1/L10 S´ ersic, J

Reference 29

Resolution: verified exact; doi, observed 2026-05-10T17:40:40.681398Z

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Observation 9e94068e-f0fe-4860-95e3-18104396f0cf · outbound

This paper cites I., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04416.x , http://adsabs.harvard.edu/abs/2001MNRAS.325..231O 325, 231.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators I., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04416.x , http://adsabs.harvard.edu/abs/2001MNRAS.325..231O 325, 231

Reference 30

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Observation 3d82a834-9b26-4adb-8fe8-c1e04dd3944c · outbound

This paper cites T., Ogilvie G.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators T., Ogilvie G

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T20:50:49.085945Z

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Observation 3068a543-c038-4cc6-be1e-9f1a981c938c · outbound

This paper cites Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:50:49.035219Z

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Observation c40033b9-2f51-42d1-be40-0d68d4695123 · outbound

This paper cites Likelihood-free inference with an improved cross-entropy estimator.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Likelihood-free inference with an improved cross-entropy estimator

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:40:40.693656Z

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Observation 493fc034-b6ab-4780-aaca-dd450bc904a1 · outbound

This paper cites B., 2015, @doi [ ] 10.1051/0004-6361/201526773 , http://adsabs.harvard.edu/abs/2015A.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators B., 2015, @doi [ ] 10.1051/0004-6361/201526773 , http://adsabs.harvard.edu/abs/2015A

Reference 34

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.107384Z

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Observation 37e2f5f9-e3cf-4240-88e9-2c6ec5717709 · outbound

This paper cites W., Montefalcone , G., McDonough , E., & Freese , K.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators W., Montefalcone , G., McDonough , E., & Freese , K

Reference 35

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Observation 611e7e46-69b6-4cd6-a14e-89cf2d54b8b8 · outbound

This paper cites J., Reeves J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators J., Reeves J

Reference 36

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Observation 7c8ab618-b946-4a5e-9e35-92177bc8e658 · outbound

This paper cites 2025, arXiv e-prints, arXiv:2510.20778, doi: 10.48550/arXiv.2510.20778.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, arXiv e-prints, arXiv:2510.20778, doi: 10.48550/arXiv.2510.20778

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:50:49.119024Z

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Observation d41f4944-722f-46c5-afe1-3d0937a97694 · outbound

This paper cites D., Bolton, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators D., Bolton, J

Reference 38

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.128270Z

Source-reported events for the cited work

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Observation 606b7294-dade-4eae-8f82-9c421e5e8099 · outbound

This paper cites G., Matarrese, S., & Riotto, A.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators G., Matarrese, S., & Riotto, A

Reference 39

Resolution: verified exact; doi, observed 2026-05-10T17:40:40.686862Z

Source-reported events for the cited work

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Observation 633a83bf-5af7-4730-a19c-627baa45a5e5 · outbound

This paper cites 2023, PhRvD, 108, 023502, doi: 10.1103/PhysRevD.108.023502.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2023, PhRvD, 108, 023502, doi: 10.1103/PhysRevD.108.023502

Reference 40

Resolution: verified exact; doi, observed 2026-05-10T17:40:40.688629Z

Source-reported events for the cited work

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Observation 3c6822f4-19b3-4c55-b301-d94e7eb8ca6f · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 41

Resolution: metadata mismatch; doi, observed 2026-05-10T20:50:49.093169Z

Source-reported events for the cited work

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Observation 5923ad35-a751-40d0-bce9-fe73777a1b4b · outbound

This paper cites A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:40:40.677063Z

Source-reported events for the cited work

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Observation e915fef1-3de6-4eb5-bcbd-011042d9901d · outbound

This paper cites C ¸ ., & Dvorkin, C.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators C ¸ ., & Dvorkin, C

Reference 43

Resolution: verified exact; doi, observed 2026-05-10T20:50:49.080627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-12T06:30:05.999651+00:00.

Pith citing papers

No inbound Pith citation observations are available.