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Paper Citation Record · LEDGER

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks

As of 15 August 2026, this Paper Citation Record lists 100 of 132 outbound references and 2 inbound Pith citation observations for arXiv:2502.03522.

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

pith.paper-citation-record.v1
2502.03522 v2

Coverage vector

measured 100 of 132 reference resolution

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:28:42.298112Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-02T15:27:05.228959Z

Reference resolution

100 of 132 outbound references displayed

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External citation measurements

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Outbound references

Observation 6a49782d-7b9e-46f5-85ff-6073fa0385de · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks , " * write output.state after.block = add.period write newline

Reference 1

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Observation b7ee8d06-2abe-42fe-9815-2959e3e8f00f · outbound

This paper cites write newline.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks write newline

Reference 2

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Observation a4af3a0f-728e-4495-9f18-fa8926fbb157 · outbound

This paper cites 2020, Astronomy & Astrophysics, 641, A6, 10.1051/0004-6361/201833910.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2020, Astronomy & Astrophysics, 641, A6, 10.1051/0004-6361/201833910

Reference 4

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Observation 3d730d9d-0479-48dc-b53e-bb95bba09ee3 · outbound

This paper cites 2019, Monthly Notices of the Royal Astronomical Society, 10.1093/mnras/stz1960.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2019, Monthly Notices of the Royal Astronomical Society, 10.1093/mnras/stz1960

Reference 5

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Observation 74312db3-673b-4c35-9a48-1daf66eb0b8c · outbound

This paper cites 2023, Monthly Notices of the Royal Astronomical Society, 525, 3662–3681, 10.1093/mnras/stad2458.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2023, Monthly Notices of the Royal Astronomical Society, 525, 3662–3681, 10.1093/mnras/stad2458

Reference 6

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Observation dc21dbe4-5041-4bb5-9ea4-ca0fd08f3714 · outbound

This paper cites 2021 a , Journal of Cosmology and Astroparticle Physics, 2021, 043, 10.1088/1475-7516/2021/10/043.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021 a , Journal of Cosmology and Astroparticle Physics, 2021, 043, 10.1088/1475-7516/2021/10/043

Reference 7

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Observation 00d4483a-6584-4a68-a9db-490b020853a5 · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 8

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Observation 2bb6c0b9-0517-40e4-9005-f3e9e6fbf64e · outbound

This paper cites 2020, Astronomy & Astrophysics, 642, A191, 10.1051/0004-6361/202038071.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2020, Astronomy & Astrophysics, 642, A191, 10.1051/0004-6361/202038071

Reference 9

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Observation 6965915c-38ab-4de5-bc0c-f979b7bef00f · outbound

This paper cites D., Bolton, J.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks D., Bolton, J

Reference 10

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Observation b0613db2-6c53-4963-9c98-47e3a4fa8dd6 · outbound

This paper cites W., Price-Whelan, A.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks W., Price-Whelan, A

Reference 11

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Observation ec04b9c1-0814-4a9a-b362-96484f5dc938 · outbound

This paper cites Stellar Streams in the Gaia Era.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Stellar Streams in the Gaia Era

Reference 12

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Observation 1bacf202-48d7-4b49-abd9-0ae3a0192e4e · outbound

This paper cites 2014, The Astrophysical Journal, 795, 95, 10.1088/0004-637x/795/1/95.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2014, The Astrophysical Journal, 795, 95, 10.1088/0004-637x/795/1/95

Reference 13

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Observation 99ae658c-3f14-43ae-a4e5-6887ee7f253f · outbound

This paper cites 2015, The Astrophysical Journal Supplement Series, 216, 29, 10.1088/0067-0049/216/2/29.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2015, The Astrophysical Journal Supplement Series, 216, 29, 10.1088/0067-0049/216/2/29

Reference 14

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Observation 9b3a97d3-c492-43c1-89ac-28838401d99d · outbound

This paper cites 2016, Physical Review Letters, 116, 10.1103/physrevlett.116.121301.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2016, Physical Review Letters, 116, 10.1103/physrevlett.116.121301

Reference 15

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Observation 76e2af51-3f97-4bb2-acdb-6df9e30c1af0 · outbound

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 16

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Observation 55ad7a10-e7ec-4172-b741-21d7ca179e9f · outbound

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 17

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Observation 3a327f19-0888-4ea4-b06b-b7a3afb37a55 · outbound

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 18

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 19

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Observation 404b7513-f968-4aec-aaa4-6786f43f4580 · outbound

This paper cites V., Dutton, A.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks V., Dutton, A

Reference 20

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Observation 6a59a257-1f19-457d-9174-ab9d998821f4 · outbound

This paper cites 2019, Astronomy and Computing, 28, 100307, 10.1016/j.ascom.2019.100307.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2019, Astronomy and Computing, 28, 100307, 10.1016/j.ascom.2019.100307

Reference 21

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Observation a5aecf57-2115-471c-8973-abdab3c79512 · outbound

This paper cites F., Piedipalumbo, E., & Tortora, C.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks F., Piedipalumbo, E., & Tortora, C

Reference 22

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 23

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Observation 46a34e71-7f76-4ce0-8d7a-a10bbac9dd2a · outbound

This paper cites G., Grillmair, C.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks G., Grillmair, C

Reference 24

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Observation 96286e30-c9db-4f95-993e-6885bfb21501 · outbound

This paper cites P., & Wells, M.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks P., & Wells, M

Reference 25

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Observation 237d084d-c9b8-4e06-82a7-a9f70f35e239 · outbound

This paper cites Learning Reionization History from Quasars with Simulation-Based Inference.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Learning Reionization History from Quasars with Simulation-Based Inference

Reference 26

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Observation 5925e032-667d-406d-a848-f378d4d5842e · outbound

This paper cites Improved particle spray algorithm for modeling globular cluster streams.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Improved particle spray algorithm for modeling globular cluster streams

Reference 27

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Observation fce8db8b-62bb-4a05-b78a-85f6b8af241a · outbound

This paper cites K., Witte, S.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks K., Witte, S

Reference 28

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Observation e80c672b-f015-427e-9c00-42e894e1b7d2 · outbound

This paper cites R., Gelman, A., & Rubin, D.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks R., Gelman, A., & Rubin, D

Reference 29

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Observation 6476ffac-97d0-4e9d-8d48-a128dec6b283 · outbound

This paper cites Report of the Topical Group on Particle Dark Matter for Snowmass 2021.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Report of the Topical Group on Particle Dark Matter for Snowmass 2021

Reference 30

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Observation 34d030c7-3952-42ff-8371-fb6dd4509b1b · outbound

This paper cites P., Koposov, S.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks P., Koposov, S

Reference 31

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Observation fae41172-5b86-492f-b4b1-5eacd0474d25 · outbound

This paper cites Discovering Symbolic Models from Deep Learning with Inductive Biases.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Discovering Symbolic Models from Deep Learning with Inductive Biases

Reference 32

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Observation fe4a15ca-bf4b-4a82-b735-003bb90a1606 · outbound

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 33

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 34

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source=arxiv_source observed=2026-08-09T04:39:46.085709Z digest=sha256:aadbd49866e73187ee98a6d569c14673705e00a21f45898d6ca05bfd86b30c96

Observation 91dd568a-3558-406a-8022-c4bed36a99ac · outbound

This paper cites Truncated proposals for scalable and hassle-free simulation-based inference.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Truncated proposals for scalable and hassle-free simulation-based inference

Reference 35

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Observation 1702530d-ca47-4613-8f84-b7f7bc06105c · outbound

This paper cites 2007, The Astrophysical Journal, 667, 859–877, 10.1086/520573.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2007, The Astrophysical Journal, 667, 859–877, 10.1086/520573

Reference 36

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Observation 0e58e71a-87f8-4605-a606-3a4d4cada5e2 · outbound

This paper cites 2008, Nature, 454, 735–738, 10.1038/nature07153.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2008, Nature, 454, 735–738, 10.1038/nature07153

Reference 37

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Observation 3efa5d65-f8df-45b6-9d63-815590aa22d4 · outbound

This paper cites J., & Gratton, R.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks J., & Gratton, R

Reference 38

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source=arxiv_source observed=2026-08-09T04:39:46.228717Z digest=sha256:695b422d8669e395e5bc3e4d993eb4b3eec5519e511e01d9529827c9ac6a03a6

Observation e05f2844-2ef5-4798-955f-b3c2221f71a9 · outbound

This paper cites Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

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source=arxiv_source observed=2026-08-09T04:39:46.233617Z digest=sha256:a37308e4aa4d3b514a231dfebdb348b5592c8d1f741868a62e1b8366dba5ec47

Observation f79714b3-51ec-41a6-b90c-b05a2c1d66cc · outbound

This paper cites O., & Hart, P.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks O., & Hart, P

Reference 40

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source=arxiv_source observed=2026-08-09T04:39:46.238685Z digest=sha256:0120b2dfa5617e1f81ad31630250da41b6a580f083edf48bfee49d817fab5627

Observation 83329562-c120-4e1d-a642-377894d979cf · outbound

This paper cites 2021, Monthly Notices of the Royal Astronomical Society, 507, 1746–1761, 10.1093/mnras/stab1762.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, Monthly Notices of the Royal Astronomical Society, 507, 1746–1761, 10.1093/mnras/stab1762

Reference 41

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source=arxiv_source observed=2026-08-09T04:39:46.260526Z digest=sha256:10769e9ba1fe122b990f2b1d7a9a23233a197a1a628149f02178f77eecc1a2a9

Observation de3b2452-1969-42ad-9de5-98b71c49d11f · outbound

This paper cites 2015, Monthly Notices of the Royal Astronomical Society, 450, 1136–1149, 10.1093/mnras/stv655.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2015, Monthly Notices of the Royal Astronomical Society, 450, 1136–1149, 10.1093/mnras/stv655

Reference 42

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source=arxiv_source observed=2026-08-09T04:39:46.344228Z digest=sha256:5f8cda35f6e9aa017d9509115de8123c1f40c42bbd01fcca1adf30465c83fe43

Observation 3aa46913-46ba-4ab4-8832-56fde35abc8f · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 43

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source=arxiv_source observed=2026-08-09T04:39:46.367498Z digest=sha256:2265048dc5c4c60203ffccf80f118f7ee2d7dfb990b16cc4229f4079166f3b9a

Observation d10289c9-ef4b-42fb-9c20-b1cb3a4fa3f3 · outbound

This paper cites E., & Belokurov , V.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks E., & Belokurov , V

Reference 44

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source=arxiv_source observed=2026-08-09T04:39:46.372895Z digest=sha256:558027d57a74d9cf6f74f7b44bea002ccae1643e5ea9c5c07144bff3c9d40b81

Observation 2cc1c973-5fe3-48d9-a29e-d242b73b5048 · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 45

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source=arxiv_source observed=2026-08-09T04:39:46.378831Z digest=sha256:0e26c5bbc1d5b03d90a23b3c98731bf55e5bae446185a314623bac6030b222cd

Observation bd5a01a5-2437-4446-be27-8c925b704dca · outbound

This paper cites A., Huang, S., & Weinberg, M.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks A., Huang, S., & Weinberg, M

Reference 46

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source=arxiv_source observed=2026-08-09T04:39:46.384185Z digest=sha256:b43bba345ae011080790ceeeb79ec9772d191ab8336caa67a2f40acabe92858b

Observation 9c956d7b-37a1-45c2-ad9d-a2535ce167cd · outbound

This paper cites T., Naidu, R.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks T., Naidu, R

Reference 47

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source=arxiv_source observed=2026-08-09T04:39:46.429401Z digest=sha256:3a55a2d5ebae8437d3cfa23909a760a26b16ee694cd39e270d5e413776954aa3

Observation 8977b7d5-a214-45a9-844c-973f890e3327 · outbound

This paper cites 2016, Deep Learning (MIT Press).

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2016, Deep Learning (MIT Press)

Reference 48

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source=arxiv_source observed=2026-08-09T04:39:46.515549Z digest=sha256:dfadb377f14c2bb1a109d4e34c3cf3defaf9e7fc5d21de3033deba7d8274d62a

Observation c30a4da1-4298-4576-9f27-8221e6e71e48 · outbound

This paper cites Automatic Posterior Transformation for Likelihood-Free Inference.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Automatic Posterior Transformation for Likelihood-Free Inference

Reference 49

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source=arxiv_source observed=2026-08-09T04:39:46.594035Z digest=sha256:c788ca3f87ec293315b2d2102dbad627187c835f7ed41ab9cbc15f42cf373f83

Observation 67b3e9fb-7d48-4c6c-b4ca-b5008c9a0a4b · outbound

This paper cites J., & Dionatos, O.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks J., & Dionatos, O

Reference 50

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source=arxiv_source observed=2026-08-09T04:39:46.599366Z digest=sha256:d701d2ab0e8082dd876f675c6598176525e913358cd3ff395c46ff427cc1484c

Observation fe796fdd-2dce-4b62-bfc0-206e537c0af9 · outbound

This paper cites U., Cor, J., & er.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks U., Cor, J., & er

Reference 51

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source=arxiv_source observed=2026-08-09T04:39:46.604275Z digest=sha256:c7acd25d1db80b0113702bc0fd8cbedb8d9591049cef46c374d0ab7b2f0591c0

Observation ebb8905a-b3f4-4ebf-b2d8-e49db5df9ae5 · outbound

This paper cites 2021, Monthly Notices of the Royal Astronomical Society, 507, 1999–2011, 10.1093/mnras/stab2181.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, Monthly Notices of the Royal Astronomical Society, 507, 1999–2011, 10.1093/mnras/stab2181

Reference 52

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source=arxiv_source observed=2026-08-09T04:39:46.609416Z digest=sha256:4d793753891b7bbbd57ee5c576218fa7ead0f46fa0c24cc40829c69edd3756c0

Observation e43ffbdc-ba74-42bb-907b-be88e7045a52 · outbound

This paper cites Likelihood-free MCMC with Amortized Approximate Ratio Estimators.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Likelihood-free MCMC with Amortized Approximate Ratio Estimators

Reference 53

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source=arxiv_source observed=2026-08-09T04:39:46.614742Z digest=sha256:eaf6ad6f6a7e6c51d8859ec6084995c29d613382d2c1114e2f0ca3b30da5ecd5

Observation 64ccf801-d810-4a6d-be56-45f3c08aea89 · outbound

This paper cites 1990, The Astrophysical Journal, 356, 359, 10.1086/168845.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 1990, The Astrophysical Journal, 356, 359, 10.1086/168845

Reference 54

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source=arxiv_source observed=2026-08-09T04:39:46.620329Z digest=sha256:7925f3b48aa552e7b3664476a1267a6afe73d30838eca1bfaee8719c742cc413

Observation 3908b877-005f-43da-9f4e-8671f8d6556b · outbound

This paper cites Inferring dark matter subhalo properties from simulated subhalo-stream encounters.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Inferring dark matter subhalo properties from simulated subhalo-stream encounters

Reference 55

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source=arxiv_source observed=2026-08-09T04:39:46.625283Z digest=sha256:6bbb38322943eeb91cef72767320cdb3f3bfde1cc41ddb2ea841dc7e526d670d

Observation 6917110d-5f79-42c2-be4b-98ff0779fae9 · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-08-09T04:39:46.630192Z digest=sha256:01f8671b6d8262e35a3e49535b67e64f7941ff9ba69954dcdeab797da21f5cf7

Observation c8037c8d-e805-45b9-ace5-5499d0da2217 · outbound

This paper cites F., Wetzel, A., Kereš, D., et al.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks F., Wetzel, A., Kereš, D., et al

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no resolver link, observed 2026-08-09T04:39:46.634837Z

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source=arxiv_source observed=2026-08-09T04:39:46.634837Z digest=sha256:0891b688976dee2adafdb8d0553ab64fc3a9514bf2560b0d207748ff1cdfbae4

Observation ffdb1d51-779c-4f86-9093-de4adc7de767 · outbound

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Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 1989, Neural networks, 2, 359

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source=arxiv_source observed=2026-08-09T04:39:46.640091Z digest=sha256:f3441b2f9ce77e5b2999a29d822184f6c1e610487c971e1f85e5c9a0f3245f7c

Observation 5d9d1477-f835-4ddc-8a1f-c7968a3aa40f · outbound

This paper cites 2021, in First International Meeting for Applied Geoscience & Energy Expanded Abstracts (Society of Exploration Geophysicists), 10.1190/segam2021-3584127.1.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, in First International Meeting for Applied Geoscience & Energy Expanded Abstracts (Society of Exploration Geophysicists), 10.1190/segam2021-3584127.1

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verified exact
doi, observed 2026-08-09T04:39:48.178748Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T04:39:46.645376Z digest=sha256:2726428cc2478fd937e61e6afae7c026376e106be69a1a3b05c8770c7d15aea4

Observation a6ad3a8e-6b37-408e-8de2-07ceccc45b7c · outbound

This paper cites 2021, , 914, 123, 10.3847/1538-4357/abfcc2.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, , 914, 123, 10.3847/1538-4357/abfcc2

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source=arxiv_source observed=2026-08-09T04:39:46.650526Z digest=sha256:2094abd44f529ea2f001ad3218207eced5b317f8cf21d1cb8a6e8bd48c34e872

Observation 1a797667-43bb-426a-b3ce-709b58e2158a · outbound

This paper cites A., Lewis , G.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks A., Lewis , G

Reference 61

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source=arxiv_source observed=2026-08-09T04:39:46.655104Z digest=sha256:a2e5afe3a8e53374cbbd8a01318d76ad2a002d4d3a8bb5f5a82c6ea2f1a26119

Observation 42ecfa0f-0d91-45ab-a3cc-665378b5b8bc · outbound

This paper cites A., Malhan , K., & Martin , N.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks A., Malhan , K., & Martin , N

Reference 62

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source=arxiv_source observed=2026-08-09T04:39:46.660164Z digest=sha256:9d53c9602cddda40756f95133f0d50adb810c8cd12ebf1fd24a805bb3f84d4ed

Observation 97a03471-f35d-4bfc-81d8-8ad6457cd5fe · outbound

This paper cites 2018, Monthly Notices of the Royal Astronomical Society, 480, 5342–5351, 10.1093/mnras/sty2226.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2018, Monthly Notices of the Royal Astronomical Society, 480, 5342–5351, 10.1093/mnras/sty2226

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source=arxiv_source observed=2026-08-09T04:39:46.681887Z digest=sha256:f3cbfe9a8c8a22bf8582ebbf3eb383e25db0b03ca31d6b88a3483423b373169b

Observation 3e845b6a-94c2-4689-a6d8-6a0a3b98ada6 · outbound

This paper cites V., Spergel, D.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks V., Spergel, D

Reference 64

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source=arxiv_source observed=2026-08-09T04:39:46.811389Z digest=sha256:603bd30e1c6b2af7e3ccc56ebe3c1e178abe10487672e2528635ba6b945e28f4

Observation 330ca574-bb97-47ca-b9e6-b8e8ac0222df · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Adam: A Method for Stochastic Optimization

Reference 65

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no resolver link, observed 2026-08-09T04:39:46.942989Z

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source=arxiv_source observed=2026-08-09T04:39:46.942989Z digest=sha256:19fcb1a2bd04c1c35cb6203197b5ee20dbb4fbc7c7ecdcd2937427c32b9d43d4

Observation a78a151c-9681-4f72-a62f-c31d8f4fb620 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 66

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source=arxiv_source observed=2026-08-09T04:39:47.006752Z digest=sha256:886c53d746188a0eaab7bd01354f9221aef2c9e695ce743fe7ce06b96ea9a5d1

Observation c0c3a43e-7ccf-4434-992c-d579769d9664 · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 67

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source=arxiv_source observed=2026-08-09T04:39:47.011642Z digest=sha256:68f12820856fe89b6c190a5e8625c8a95c4cc6a7b3bfe9e0989b5632d08a4ad1

Observation 8c84d2b1-3478-4140-89b2-06b45ab71a24 · outbound

This paper cites E., Irwin , M., Belokurov , V., et al.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks E., Irwin , M., Belokurov , V., et al

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source=arxiv_source observed=2026-08-09T04:39:47.017437Z digest=sha256:a5fc03c82e057256c90ed02bb5cff65c938a85221b4b4e8d8c1a97460bc87c67

Observation 27dd40de-4a0d-4ecf-912f-cd7770a4867c · outbound

This paper cites E., Rix , H.-W., & Hogg , D.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks E., Rix , H.-W., & Hogg , D

Reference 69

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no resolver link, observed 2026-08-09T04:39:47.023321Z

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source=arxiv_source observed=2026-08-09T04:39:47.023321Z digest=sha256:844f96d79303e7dd31538e206d04da371d6d3bcc4db12c5a1e152f2883b56bf2

Observation cc28f6cc-66b2-4f4d-8c6a-4c35c90b9247 · outbound

This paper cites H., & Helmi, A.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks H., & Helmi, A

Reference 70

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verified exact
doi, observed 2026-08-09T04:39:48.063218Z

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source=arxiv_source observed=2026-08-09T04:39:47.029323Z digest=sha256:f9e732463155804cdd83150d1b3a3eac3fd43db8710d59836df5fb784f7c43b1

Observation 8c1133c9-4df6-4f7d-abbb-0ee94220365d · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 72

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source=arxiv_source observed=2026-08-09T04:39:47.040064Z digest=sha256:8a622b1aed62196c4c7ec1fedbeb9e0f4ab7823d44901edc44cc08e92bf84926

Observation 3a849a72-62c1-4f43-81ba-4da725125e48 · outbound

This paper cites 2018, Physical Review D, 98, 10.1103/physrevd.98.063511.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2018, Physical Review D, 98, 10.1103/physrevd.98.063511

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source=arxiv_source observed=2026-08-09T04:39:47.047421Z digest=sha256:59240667d1ff436159823b8a042cd03290db28eb0617f4168d83cc95493469a3

Observation 8e283771-4c7e-4775-9b79-b8e6976c0ff3 · outbound

This paper cites 2023, Machine Learning: Science and Technology, 4, 01LT01, 10.1088/2632-2153/acbb53.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2023, Machine Learning: Science and Technology, 4, 01LT01, 10.1088/2632-2153/acbb53

Reference 74

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source=arxiv_source observed=2026-08-09T04:39:47.052901Z digest=sha256:4c3518efbf1de3e86b2541b2ff9cefe1fe91328ad11d5e11ebf59d661035d729

Observation f3034ad0-3862-4061-b0a4-6c3353ccfb9d · outbound

This paper cites 2024, Physical Review D, 109, 10.1103/physrevd.109.083536.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2024, Physical Review D, 109, 10.1103/physrevd.109.083536

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source=arxiv_source observed=2026-08-09T04:39:47.058056Z digest=sha256:4e18ed24f1c7eff6f52ef0432f3127e2caacafeb411260178a706d8f68c53f45

Observation 450b1e53-c2ca-49b0-9a28-dc8a8c190130 · outbound

This paper cites S., Koposov, S.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks S., Koposov, S

Reference 76

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source=arxiv_source observed=2026-08-09T04:39:47.063637Z digest=sha256:8e8c5b566f481e8e139c723f6ea43ff0449a1853a0aab2eb56242027314c085d

Observation f732943b-d1bf-47cf-88c1-d171a51f00d6 · outbound

This paper cites S., Koposov, S.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks S., Koposov, S

Reference 77

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source=arxiv_source observed=2026-08-09T04:39:47.069439Z digest=sha256:cd9d9fe60ae799305457d32987a439b3a329a471df01aef71473e19855f72c96

Observation 0e4bde02-7791-41af-bace-4a2bd3c6296a · outbound

This paper cites 2023, Monthly Notices of the Royal Astronomical Society, 524, 6167–6180, 10.1093/mnras/stad2262.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2023, Monthly Notices of the Royal Astronomical Society, 524, 6167–6180, 10.1093/mnras/stad2262

Reference 78

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Observation 9872eca1-0d41-4518-9a90-8dfa01256067 · outbound

This paper cites Towards Neural Scaling Laws on Graphs.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Towards Neural Scaling Laws on Graphs

Reference 79

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Observation fdd18889-ad6a-4586-9522-4187be56f4e2 · outbound

This paper cites 2021, in Proceedings of Machine Learning Research, Vol.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, in Proceedings of Machine Learning Research, Vol

Reference 80

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source=arxiv_source observed=2026-08-09T04:39:47.083409Z digest=sha256:d3780b08d6c6b0d9d3b03f248256b143f523077f7b2b4a90e7894e2aae3a2e73

Observation 0d1f3818-670f-489d-b957-2795cac0d195 · outbound

This paper cites an unresolved cited work.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Unresolved cited work

Reference 81

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source=arxiv_source observed=2026-08-09T04:39:47.088234Z digest=sha256:95fb084e4d9064dd3579e1223b429180cac82d994f608abcb9b7e71b940bb1c6

Observation 5416e11f-acd5-4662-aea5-9a1c56d665cb · outbound

This paper cites V., Kang, X., Fontanot, F., et al.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks V., Kang, X., Fontanot, F., et al

Reference 82

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source=arxiv_source observed=2026-08-09T04:39:47.092850Z digest=sha256:d1c78db6e0236fd5eef60fe28b096df534378b10e3090f3a319be45dc3dbed3c

Observation 52165555-de14-423f-b033-730107da1839 · outbound

This paper cites A., Carlberg, R.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks A., Carlberg, R

Reference 83

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source=arxiv_source observed=2026-08-09T04:39:47.097446Z digest=sha256:21edb2898e8757056811bd29afa12c8f1d0b788120ca1501bebd48513bd49903

Observation 32aa26ea-b5ab-49c9-b77c-7c3515824c63 · outbound

This paper cites 2024, The Astrophysical Journal, 964, 104, 10.3847/1538-4357/ad1885.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2024, The Astrophysical Journal, 964, 104, 10.3847/1538-4357/ad1885

Reference 84

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source=arxiv_source observed=2026-08-09T04:39:47.102866Z digest=sha256:90d3dae3a53e012dcb7fb5378d9c05ced57e3d65cf80126d2037473a62df1c41

Observation 77cd88aa-8fa5-4d6a-8f70-a77cfa52c0bb · outbound

This paper cites M., & Brinkmann, J.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks M., & Brinkmann, J

Reference 85

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source=arxiv_source observed=2026-08-09T04:39:47.108624Z digest=sha256:8f658c8fdc268cadd06099e1448a705c60e67090011ca63b4c906255f319c896

Observation 5ccb4b68-868f-4d65-a5e2-f5cc87d18b4c · outbound

This paper cites 2010, Reports on Progress in Physics, 73, 086901, 10.1088/0034-4885/73/8/086901.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2010, Reports on Progress in Physics, 73, 086901, 10.1088/0034-4885/73/8/086901

Reference 86

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source=arxiv_source observed=2026-08-09T04:39:47.113584Z digest=sha256:33e9ac2a8a64ba755e1e4cb3305dda83ff97b6e0b35b6ab2a12f42125fd7efb7

Observation 7702134c-603d-49f1-8372-6f7aaa295641 · outbound

This paper cites 2000, The Astrophysical Journal, 543, 1–23, 10.1086/317079.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2000, The Astrophysical Journal, 543, 1–23, 10.1086/317079

Reference 87

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no resolver link, observed 2026-08-09T04:39:47.118488Z

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source=arxiv_source observed=2026-08-09T04:39:47.118488Z digest=sha256:5f2127bf33ca8cb23a885a0b85a95e27e7b3093bce6f79c7c6b59d4944dc314a

Observation eae673e2-4137-449f-a2cd-7a5d93d32d1b · outbound

This paper cites D., Beckman, R.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks D., Beckman, R

Reference 88

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no resolver link, observed 2026-08-09T04:39:47.123443Z

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source=arxiv_source observed=2026-08-09T04:39:47.123443Z digest=sha256:172cc0d23ec0415d8f313ced3a3298809d5fd8a4e826ad0a457eb2763e978fa2

Observation 1cb53274-00b7-4e24-9218-ae4a11134c17 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Efficient Estimation of Word Representations in Vector Space

Reference 89

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no resolver link, observed 2026-08-09T04:39:47.128735Z

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source=arxiv_source observed=2026-08-09T04:39:47.128735Z digest=sha256:a5dcf1c6b6c7df10f531196f9b482f2ae29f0ca01728795300b7c8816b3f1b8c

Observation ba8e05af-a398-424f-927d-34e191f22549 · outbound

This paper cites Contrastive Neural Ratio Estimation for Simulation-based Inference.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Contrastive Neural Ratio Estimation for Simulation-based Inference

Reference 90

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no resolver link, observed 2026-08-09T04:39:47.135088Z

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source=arxiv_source observed=2026-08-09T04:39:47.135088Z digest=sha256:17ee32dcb696f0dbdce0e5f5fed07c0f1b970545c1d2f2bed0934dd3af103fc2

Observation d36ae0e3-f299-45cb-8783-0fde511f8db3 · outbound

This paper cites 2022, Machine Learning: Science and Technology, 3, 01LT03, 10.1088/2632-2153/ac494a.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2022, Machine Learning: Science and Technology, 3, 01LT03, 10.1088/2632-2153/ac494a

Reference 92

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doi, observed 2026-08-09T04:39:47.886196Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T04:39:47.145447Z digest=sha256:f7a716337a0904b8dc3e25dc81a6874b78a73f8e17fa17788929a2be0a0731cc

Observation 1f036873-7384-4d82-b045-d5164944a441 · outbound

This paper cites Nagai, R.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks Nagai, R

Reference 93

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source=arxiv_source observed=2026-08-09T04:39:47.150403Z digest=sha256:1c4a331f8c6aa0d029b11ce2d5a61c7678dcac1161e05c72e32620144a951851

Observation f93b02e9-791d-4ca7-b0ea-ad7501d0f642 · outbound

This paper cites 2021, Physical Review Letters, 126, 10.1103/physrevlett.126.091101.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2021, Physical Review Letters, 126, 10.1103/physrevlett.126.091101

Reference 94

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source=arxiv_source observed=2026-08-09T04:39:47.155260Z digest=sha256:9bae1c325126d4fe068a9c282891a31c5391efd3537c15d02460265938d37730

Observation 4c64aeb5-61fb-43d0-a131-88a01a0aeb68 · outbound

This paper cites O., Birrer , S., Gilman , D., et al.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks O., Birrer , S., Gilman , D., et al

Reference 95

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no resolver link, observed 2026-08-09T04:39:47.160415Z

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source=arxiv_source observed=2026-08-09T04:39:47.160415Z digest=sha256:78f5fa9b7feb115c017c61b50c7555e2ae6d4eec01bd40c73c31adac65c903f0

Observation 3cfb8592-3969-40c7-88b1-82cbcd65a4c3 · outbound

This paper cites F., Frenk, C.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks F., Frenk, C

Reference 96

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source=arxiv_source observed=2026-08-09T04:39:47.165360Z digest=sha256:91f0350c81be037af4207f1cc293a6c81ae5e8fbf3df8308430e75b38eb34721

Observation 601edada-b569-4e27-ac34-ab028b20d725 · outbound

This paper cites 2024, Astronomy & Astrophysics, 689, A153, 10.1051/0004-6361/202348485.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2024, Astronomy & Astrophysics, 689, A153, 10.1051/0004-6361/202348485

Reference 97

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no resolver link, observed 2026-08-09T04:39:47.170497Z

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source=arxiv_source observed=2026-08-09T04:39:47.170497Z digest=sha256:c89a40557eee02696acc271e8e0fd7c749a1689d758267479f322c441b6d7529

Observation 0fc4a4ba-3ea6-4548-a566-20f83a1a59c7 · outbound

This paper cites J., & Carlin, J.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks J., & Carlin, J

Reference 98

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no resolver link, observed 2026-08-09T04:39:47.175266Z

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source=arxiv_source observed=2026-08-09T04:39:47.175266Z digest=sha256:7ee55b1e52e6db24212b93745dc901e47c505cabf712abd24b0942ddae699850

Observation 7e727f6d-2100-44d0-b9c7-846907f07333 · outbound

This paper cites G., et al.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks G., et al

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doi, observed 2026-08-09T04:39:47.817570Z

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source=arxiv_source observed=2026-08-09T04:39:47.180161Z digest=sha256:5450ccddfce43fa393520b90fdec3b073891e5ac540418ebe46abd984747b5c2

Observation dace2466-9200-4180-9b92-17b4ea7677ea · outbound

This paper cites How much information can be extracted from galaxy clustering at the field level?.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks How much information can be extracted from galaxy clustering at the field level?

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source=arxiv_source observed=2026-08-09T04:39:47.184947Z digest=sha256:c084e529ed95de9240fb28bd961a32f765dc121e6f175db43fcc60130931c013

Observation 7c46450f-7f47-4b5b-b4e4-f18abb2189ae · outbound

This paper cites 2023, Physical Review D, 107, 10.1103/physrevd.107.043015.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2023, Physical Review D, 107, 10.1103/physrevd.107.043015

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source=arxiv_source observed=2026-08-09T04:39:47.191772Z digest=sha256:2f28d8e3886356f874c47e83944879843b110cae308dff67d1d00e8b8ee565e0

Observation 5f1dc48a-f140-42c8-b02e-498d06077713 · outbound

This paper cites 2022, The Astrophysical Journal, 940, 22, 10.3847/1538-4357/ac93ee.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks 2022, The Astrophysical Journal, 940, 22, 10.3847/1538-4357/ac93ee

Reference 102

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no resolver link, observed 2026-08-09T04:39:47.197349Z

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source=arxiv_source observed=2026-08-09T04:39:47.197349Z digest=sha256:09050791af356fd017f5296e0150db79b7385a97328bd1e30e97677df8539b0e

Observation 9d412242-5731-4086-9b27-e65601c00663 · outbound

This paper cites K., Rockosi , C.

Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks K., Rockosi , C

Reference 103

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source=arxiv_source observed=2026-08-09T04:39:47.202554Z digest=sha256:6fb4fcd18118d0e2bf15d30294e22c7f478cda812f63a7e1a3de8aaef4105b88

Pith citing papers

Observation eec3379d-b068-4c53-86f9-17c75e37e3d8 · inbound

The Milky Way - Large Magellanic Cloud Interaction with Simulation Based Inference cites this paper.

The Milky Way - Large Magellanic Cloud Interaction with Simulation Based Inference Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks

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no resolver link, observed 2026-08-04T11:28:42.298112Z

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source=arxiv_source observed=2026-08-04T11:28:42.298112Z digest=sha256:43d89972f3908e5cde10eb8785c3dc606b4048717012bf4c95e2e0ec19c8b9b1

Observation 2e5bb97f-793a-4f8c-8d8f-28374c31bc45 · inbound

The Atacama Cosmology Telescope: Probing new signatures of ultralight axions with gravitational lensing cites this paper.

The Atacama Cosmology Telescope: Probing new signatures of ultralight axions with gravitational lensing Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks

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arxiv_id, observed 2026-07-02T15:27:05.231585Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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