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Paper Citation Record · LEDGER

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks

As of 8 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 1 inbound Pith citation observation for arXiv:2506.02957.

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

pith.paper-citation-record.v1
2506.02957 v1

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:16:00.434563Z

measured 91 of 91 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T02:27:16.846091Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

90 of 90 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved85
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06164b13-f8db-416d-946f-56b06e72788c · outbound

This paper cites JH cBP ]D aW Z *+b tWwͽ 99- /栚Jd1qI,R'@ RNTT8`w w Bg 5-H.8M( B| I @B|jTWC# B\ *ܤi*|'. |, nȳ P N X > υ 9J v : L 3 *># rs sXæ) Q r CA 6(. +13S Gm r. `B<F c0 !ND > h8 U.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks JH cBP ]D aW Z *+b tWwͽ 99- /栚Jd1qI,R'@ RNTT8`w w Bg 5-H.8M( B| I @B|jTWC# B\ *ܤi*|'. |, nȳ P N X > υ 9J v : L 3 *># rs sXæ) Q r CA 6(. +13S Gm r. `B<F c0 !ND > h8 U

Reference 1

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Observation ad16935c-ae90-4c88-bca4-ae3259d1c063 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-07T11:15:52.647879Z digest=sha256:9b6bf60ceaa9728b0e650e8c61efaf92c8232ea1685484acfcc375d0446ccfe6

Observation 42183bcd-4f0b-4c49-9293-1df3ebc50a7f · outbound

This paper cites 2010, , 81, 123530, 10.1103/PhysRevD.81.123530.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2010, , 81, 123530, 10.1103/PhysRevD.81.123530

Reference 4

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source=arxiv_source observed=2026-08-07T11:15:52.833585Z digest=sha256:3d9effbe4706ea5c0500507401c84d52b8f0a550cadc8fbc03a0aa3146a05c3c

Observation 8b25d2cb-9091-4ead-8683-1c13811b4688 · outbound

This paper cites A hands-on introduction to Physics-Informed Neural Networks for solving partial differential equations with benchmark tests taken from astrophysics and plasma physics.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks A hands-on introduction to Physics-Informed Neural Networks for solving partial differential equations with benchmark tests taken from astrophysics and plasma physics

Reference 5

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source=arxiv_source observed=2026-08-07T11:15:52.904609Z digest=sha256:190fb0491c02b21e364f4ee16f0a4eafb6d7f197f625230630936cf20a18ef52

Observation fadf6b2b-fb42-439c-922b-e58b609a5dc9 · outbound

This paper cites G., Pearlmutter, B.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks G., Pearlmutter, B

Reference 6

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source=arxiv_source observed=2026-08-07T11:15:52.996876Z digest=sha256:464a06a9de40630195f74a901207112e6043821340eb213f9c5ce754f8ebe1c4

Observation f98312b7-b885-4d93-99e4-06d88fde3a57 · outbound

This paper cites 2002, , 367, 1, 10.1016/S0370-1573(02)00135-7.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2002, , 367, 1, 10.1016/S0370-1573(02)00135-7

Reference 7

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source=arxiv_source observed=2026-08-07T11:15:53.084460Z digest=sha256:815c88afda522339d3efc182adfd75d731d1575c0a35021b6fcc0b1daba21ab2

Observation a5bc5a73-1d97-438f-98b5-656f029825b6 · outbound

This paper cites 2021, MNRAS, 509, 1323, 10.1093/mnras/stab3088.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, MNRAS, 509, 1323, 10.1093/mnras/stab3088

Reference 8

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source=arxiv_source observed=2026-08-07T11:15:53.175178Z digest=sha256:56bc1c39b14c53d69590b372bb7f3d7de1e62bef37ff95398aa01169f6f02374

Observation 0afec027-0ea2-4e73-a793-a79b9ba5fa1c · outbound

This paper cites A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems

Reference 9

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source=arxiv_source observed=2026-08-07T11:15:53.250426Z digest=sha256:a5fd29651d4810a8384b448bc09ac8c8aadb00993154f1dddc6762d21e3193d9

Observation 456eaf70-3fc7-4599-8978-cad09a84f625 · outbound

This paper cites S., & Boylan-Kolchin , M.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks S., & Boylan-Kolchin , M

Reference 10

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source=arxiv_source observed=2026-08-07T11:15:53.320024Z digest=sha256:3c6e8bbae8d11930123f39a645f5a87246a90bd308ab1f06db57005f877f7de3

Observation a84d00c4-9a50-47bc-8b88-dabdb633ce92 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 11

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source=arxiv_source observed=2026-08-07T11:15:53.397870Z digest=sha256:e024df32a75d81e86890a1d808c602e1754e1175171e1aedb958b7c2b388ce3d

Observation d95b61cf-565d-4412-a03e-3089248bbe29 · outbound

This paper cites 2024, Physical Review Research, 6, 013282, 10.1103/PhysRevResearch.6.013282.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2024, Physical Review Research, 6, 013282, 10.1103/PhysRevResearch.6.013282

Reference 12

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doi, observed 2026-08-07T11:16:01.430833Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T11:15:53.464356Z digest=sha256:2e570e2674f97c6c50d37fa283d771dfe7e622edb2dc9b2a44ce17bda39f70e3

Observation 60ccdcb8-debf-4dac-b1d1-de90a8b70942 · outbound

This paper cites 2019, MNRAS, 490, 1055, 10.1093/mnras/stz2605.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2019, MNRAS, 490, 1055, 10.1093/mnras/stz2605

Reference 13

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source=arxiv_source observed=2026-08-07T11:15:53.546201Z digest=sha256:f69c2456f1f48968a3dd1add655c09cc073afa69e63330c393542ea72dd4b598

Observation ac66c31c-540d-484f-a002-d056e4e05f3f · outbound

This paper cites H., et al.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks H., et al

Reference 14

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source=arxiv_source observed=2026-08-07T11:15:53.611457Z digest=sha256:dc52eecd4c4b75b7162b8cc41c70aff5f90d2ca61a3c7311598aa0161eb7d59d

Observation e6ca4f89-61d0-4913-9fdb-6989456bda19 · outbound

This paper cites 2021, Proceedings of the National Academy of Sciences, 118, e2020324118, 10.1073/pnas.2020324118.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, Proceedings of the National Academy of Sciences, 118, e2020324118, 10.1073/pnas.2020324118

Reference 15

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source=arxiv_source observed=2026-08-07T11:15:53.679588Z digest=sha256:ee2019cb308bc78e8911c0e6da27cc77ecd056e6d91d0a3b3206c121ce1de0fb

Observation bcc656fd-6224-41b5-8d5e-826cbf3d6696 · outbound

This paper cites 2020, Physics of the Dark Universe, 28, 100503, https://doi.org/10.1016/j.dark.2020.100503.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2020, Physics of the Dark Universe, 28, 100503, https://doi.org/10.1016/j.dark.2020.100503

Reference 16

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source=arxiv_source observed=2026-08-07T11:15:53.769892Z digest=sha256:959e48163cb99cd438948282586a25518f66bb2cf1cf45588b99bf87531e99cb

Observation 8265a642-fe63-4f99-b8c4-cf597c23df39 · outbound

This paper cites 2024, Computer Methods in Applied Mechanics and Engineering, 429, 117116, 10.1016/j.cma.2024.117116.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2024, Computer Methods in Applied Mechanics and Engineering, 429, 117116, 10.1016/j.cma.2024.117116

Reference 17

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Observation cc6a373d-1784-495e-afc4-33ceb9161279 · outbound

This paper cites C., & B \"u rger , D.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks C., & B \"u rger , D

Reference 18

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source=arxiv_source observed=2026-08-07T11:15:53.933554Z digest=sha256:81162094d567f1a710da84135e5fa877a24eafc41832c6b02fac899730edca34

Observation f040dd89-9f1f-4f98-a205-457b5e908308 · outbound

This paper cites S., & White , S.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks S., & White , S

Reference 19

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source=arxiv_source observed=2026-08-07T11:15:54.028807Z digest=sha256:3b7fa48a92b9603df7be0f1afce6e209971210d99ecd75820d63c7e17b8d22ef

Observation 7f2a134e-2c4b-435a-81ee-b43dc9259062 · outbound

This paper cites 2010, in Proceedings of Machine Learning Research, Vol.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2010, in Proceedings of Machine Learning Research, Vol

Reference 20

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source=arxiv_source observed=2026-08-07T11:15:54.121277Z digest=sha256:fdf582f4b3fcdd2877db5c5da8b92cbb8de0fd652e66b57e6e367638fa5273c0

Observation fc8c86ee-759c-457b-b9f3-5cf9e2b7bfaf · outbound

This paper cites 2019, Proceedings of the National Academy of Sciences, 116, 13825, 10.1073/pnas.1821458116.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2019, Proceedings of the National Academy of Sciences, 116, 13825, 10.1073/pnas.1821458116

Reference 21

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source=arxiv_source observed=2026-08-07T11:15:54.201631Z digest=sha256:a7cf36379ea64640291aa89d2159b3f4286c8ef96e04b92e20eccb1d78bea13c

Observation 5f4182da-b3d7-45a7-9ecc-fad07644c454 · outbound

This paper cites G., Geiger, B.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks G., Geiger, B

Reference 22

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source=arxiv_source observed=2026-08-07T11:15:54.298353Z digest=sha256:8923cab210f493cd00f254d14affe0f72e3adf69ed930b2d72f630db2e9c8384

Observation ea817143-3681-4eff-b6e1-450d2d0b2a5c · outbound

This paper cites 2000, Phys.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2000, Phys

Reference 23

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source=arxiv_source observed=2026-08-07T11:15:54.384756Z digest=sha256:2ea8fa800001530431a062a5319479f355dfa2d91dc80e45b1f1ea90744936b5

Observation 7a6563b6-5d42-40c1-b158-0ce476946993 · outbound

This paper cites 2021, , 59, 247, 10.1146/annurev-astro-120920-010024.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, , 59, 247, 10.1146/annurev-astro-120920-010024

Reference 24

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Observation 4180a032-6980-44a5-8c7a-c1ce57575621 · outbound

This paper cites P., Tremaine , S., & Witten , E.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks P., Tremaine , S., & Witten , E

Reference 25

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source=arxiv_source observed=2026-08-07T11:15:54.570840Z digest=sha256:fa91fd71f36b248c8b2c0597f31833f925e27c77355fe3dff2af2c37487b5584

Observation 3861470f-cf32-4884-84c1-865e5cf68d8e · outbound

This paper cites D., Mao , Z., Adams , N., & Karniadakis , G.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks D., Mao , Z., Adams , N., & Karniadakis , G

Reference 26

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Observation b428e5f9-a184-42af-9207-0d5e8e58c5e8 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-08-07T11:15:54.775953Z digest=sha256:b13353913e99b20e9f3e577b8f650a16d20a68031a688d5ce5989dc3b2a71cb3

Observation 60ba9c69-9f02-4337-8276-8296aa148aa0 · outbound

This paper cites dm2gal: Mapping Dark Matter to Galaxies with Neural Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks dm2gal: Mapping Dark Matter to Galaxies with Neural Networks

Reference 28

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source=arxiv_source observed=2026-08-07T11:15:54.866457Z digest=sha256:f83e6ce760418fa2a1d74dc597f7e6637fe8d6249156f461ee7f3d9a616bab2f

Observation 13a31789-6756-4b91-8839-c25954102493 · outbound

This paper cites 2022, The Astrophysical Journal, 930, 115, 10.3847/1538-4357/ac5c4a.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2022, The Astrophysical Journal, 930, 115, 10.3847/1538-4357/ac5c4a

Reference 29

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Observation 6dc97890-ea9e-4a4c-904c-7343e0fa4900 · outbound

This paper cites DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation

Reference 30

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source=arxiv_source observed=2026-08-07T11:15:55.077224Z digest=sha256:7c09f9d8e6502beab759735bf170e28134c8d80ca5230b1652be6fc0d7074f61

Observation 8390e407-fe01-48a6-bb92-cd735404734a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Adam: A Method for Stochastic Optimization

Reference 31

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source=arxiv_source observed=2026-08-07T11:15:55.169024Z digest=sha256:9218ff7c5cb5afc6e3ecee4795bf2548b9b3ff4f4afdac0d911a9c31e9b59060

Observation 0ee36f54-3814-424a-b10c-62a0132cef81 · outbound

This paper cites PINION: Physics-informed neural network for accelerating radiative transfer simulations for cosmic reionization.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks PINION: Physics-informed neural network for accelerating radiative transfer simulations for cosmic reionization

Reference 32

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local_arxiv, observed 2026-08-07T11:16:02.643084Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T11:15:55.262089Z digest=sha256:f06206b069c2ab0b0aa8a19d135ccba4ec01aae82762824ff16298a816d54a43

Observation c1d89cb2-f681-441e-a6e9-5507b6c19ffa · outbound

This paper cites Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas

Reference 33

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source=arxiv_source observed=2026-08-07T11:15:55.408967Z digest=sha256:34b97176a6f914f1e29161a18706fa1d113d6d569ffd5abb6125a2d882f1adcf

Observation 29eca031-c69e-4c93-9608-2598f835aacd · outbound

This paper cites A Hybrid Scheme for Fuzzy Dark Matter Simulations Combining the Schr\"odinger and Hamilton-Jacobi-Madelung Equations.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks A Hybrid Scheme for Fuzzy Dark Matter Simulations Combining the Schr\"odinger and Hamilton-Jacobi-Madelung Equations

Reference 34

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source=arxiv_source observed=2026-08-07T11:15:55.504185Z digest=sha256:7c5595242b61df2974056cf6b6abacb7b4b4ec1fb40b09f75ae212056c1fbe39

Observation f4635a57-05b4-4da9-ad08-3908cd76d15b · outbound

This paper cites 2015, Nature, 521, 436, 10.1038/nature14539.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2015, Nature, 521, 436, 10.1038/nature14539

Reference 35

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source=arxiv_source observed=2026-08-07T11:15:55.657094Z digest=sha256:1ef5d69953db58c6120cd5e5f23c81d64278cdc9e920b7b0436bc2ece4237483

Observation 542ed473-e655-4be2-9326-a634ba616c1d · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 36

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source=arxiv_source observed=2026-08-07T11:15:55.785487Z digest=sha256:2339d83f1f65194ca780b3915ef3a6149efe34a5e8b3ba61110e83e411ac989e

Observation 13ba3832-0d36-4ef0-a793-a86ddbcfdc82 · outbound

This paper cites 2025, , 111, 023535, 10.1103/PhysRevD.111.023535.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2025, , 111, 023535, 10.1103/PhysRevD.111.023535

Reference 37

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source=arxiv_source observed=2026-08-07T11:15:55.882226Z digest=sha256:f151cf5c0f4805fcf8f15da3584ea58277ff8106dcdd6ac58c9e34480b3a2f3d

Observation 43b8598e-11a4-466c-bc06-7c7976cb4cdc · outbound

This paper cites 1927, Zeitschrift fur Physik, 40, 322, 10.1007/BF01400372.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 1927, Zeitschrift fur Physik, 40, 322, 10.1007/BF01400372

Reference 38

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source=arxiv_source observed=2026-08-07T11:15:55.976777Z digest=sha256:372e1f29680b43e6fc41950ee5f7c4d95987b5eb60d02cf8ce79cb8b049e3e4e

Observation db169911-c3ad-45d7-9af7-f9393b7bb20c · outbound

This paper cites D., & Karniadakis , G.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks D., & Karniadakis , G

Reference 39

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source=arxiv_source observed=2026-08-07T11:15:56.045950Z digest=sha256:ddd823672793312f0bc0abe15ae597e7449fd8b56b82de00c7781b88d508785c

Observation 24deb38c-6067-4706-bc0f-905cea419bfc · outbound

This paper cites Axion Cosmology.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Axion Cosmology

Reference 40

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source=arxiv_source observed=2026-08-07T11:15:56.165068Z digest=sha256:53f543390ebc9146d51de4a092023353322a67f24f75a5ab517d57c4c6f4482a

Observation 9de7811f-8530-4a61-b776-6bee576adc88 · outbound

This paper cites PinnDE: Physics-Informed Neural Networks for Solving Differential Equations.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks PinnDE: Physics-Informed Neural Networks for Solving Differential Equations

Reference 41

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source=arxiv_source observed=2026-08-07T11:15:56.220918Z digest=sha256:ef4ef4dbd9271e10bd0379ae31cc29c408058a97c8ec1d958f363cf6ee3ba541

Observation fa1f2bbd-9c3e-448f-a7dd-4eed68f9d8bf · outbound

This paper cites 2021, , 506, 2603, 10.1093/mnras/stab1764.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, , 506, 2603, 10.1093/mnras/stab1764

Reference 42

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source=arxiv_source observed=2026-08-07T11:15:56.278977Z digest=sha256:58d6086f58be8754282a18b6870eee263de1d0fce9bb990515fdd469fff5eab1

Observation 3ad3a192-ab36-434f-8301-92acf6f05079 · outbound

This paper cites Solitons in the dark: non-linear structure formation with fuzzy dark matter.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Solitons in the dark: non-linear structure formation with fuzzy dark matter

Reference 43

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source=arxiv_source observed=2026-08-07T11:15:56.378652Z digest=sha256:aca42ed565902ce5451e3606c16a6191401bc9f94266ff62d851eb7f38b3489e

Observation 63b4a602-d080-4413-b945-fb57fbf9c1bd · outbound

This paper cites 2021, Journal of Quantitative Spectroscopy and Radiative Transfer, 270, 107705, https://doi.org/10.1016/j.jqsrt.2021.107705.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, Journal of Quantitative Spectroscopy and Radiative Transfer, 270, 107705, https://doi.org/10.1016/j.jqsrt.2021.107705

Reference 44

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source=arxiv_source observed=2026-08-07T11:15:56.464886Z digest=sha256:17dc256fde5a62213d7f15343dfd808afc57e05265e41bca018afa9cbc58472b

Observation 3dc96702-eaea-456d-a78f-376fa60e8dd2 · outbound

This paper cites 2024, Symmetry, 16, 201, 10.3390/sym16020201.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2024, Symmetry, 16, 201, 10.3390/sym16020201

Reference 45

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source=arxiv_source observed=2026-08-07T11:15:56.526418Z digest=sha256:8449a9e6f15d09e7c002d0b552bd5b60871303215b322b56cfc6326f848b9e05

Observation e8b38690-985e-4a39-bdbb-807e100940c8 · outbound

This paper cites 2018, , 97, 083519, 10.1103/PhysRevD.97.083519.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2018, , 97, 083519, 10.1103/PhysRevD.97.083519

Reference 46

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source=arxiv_source observed=2026-08-07T11:15:56.577909Z digest=sha256:be40932fa209f713ffd4979d50ac4d77b5adfd8b99011b421cbb72688e8b6e63

Observation bb349069-4686-43d5-9810-879186bc3b40 · outbound

This paper cites 2021, , 910, 29, 10.3847/1538-4357/abe6ac.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, , 910, 29, 10.3847/1538-4357/abe6ac

Reference 47

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doi, observed 2026-08-07T11:16:00.819674Z

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source=arxiv_source observed=2026-08-07T11:15:56.673521Z digest=sha256:1da1e1932cc1cc098709c22d10e22ab18d67ab9b2c4da7bb2ec4f990e5a00fa0

Observation 082fea78-ca79-46ef-9547-26ea9b0eaeab · outbound

This paper cites H., et al.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks H., et al

Reference 48

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source=arxiv_source observed=2026-08-07T11:15:56.739633Z digest=sha256:ffbcfe45071a5ce5e074da116c89b962664ae0b3a731c48e8e05367270eaa4ca

Observation 2ee48486-3b62-4ee1-901a-5e8017dee0af · outbound

This paper cites DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks

Reference 49

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source=arxiv_source observed=2026-08-07T11:15:56.816786Z digest=sha256:81f3c1528a8006a19502fef5039cdf3cabc5f38bd153f632e1cc5e9a8f6a9c09

Observation 1487f532-cb7c-4e65-877b-61a8b368ce81 · outbound

This paper cites 2015, Neural Networks and Deep Learning (Determination Press).

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2015, Neural Networks and Deep Learning (Determination Press)

Reference 50

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no resolver link, observed 2026-08-07T11:15:56.901516Z

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source=arxiv_source observed=2026-08-07T11:15:56.901516Z digest=sha256:e9d74b97a77319284aeeb542489fed136b845a508c6695471d858565012b6e05

Observation cd460928-f413-49ef-ad03-e251a6027a4f · outbound

This paper cites 1980, Mathematics of Computation, 35, 773.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 1980, Mathematics of Computation, 35, 773

Reference 51

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source=arxiv_source observed=2026-08-07T11:15:56.994026Z digest=sha256:450bb18062003a61402069422f7f7cddfc9c5065dc4d8ec5003493d3ac8e9899

Observation 2f343fc7-6483-4c6f-a394-6bff578df996 · outbound

This paper cites 2018, , 478, 3935, 10.1093/mnras/sty1224.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2018, , 478, 3935, 10.1093/mnras/sty1224

Reference 52

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source=arxiv_source observed=2026-08-07T11:15:57.064789Z digest=sha256:82ed2de435c2053d922ad23c4e0418bf151272f8c46ea080179aa27d5252b998

Observation 2e3255bb-d68b-4d3e-bea7-9cc009d5a318 · outbound

This paper cites A., Navarro , J.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks A., Navarro , J

Reference 53

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source=arxiv_source observed=2026-08-07T11:15:57.145627Z digest=sha256:d4415b1924733b3766c74c041cc0cc690a8716f8b7cd7c53f237dddd0a81c3bc

Observation 5787401b-2a06-4c90-8d98-f75997b2cd49 · outbound

This paper cites 2022, Universe, 8, 76, 10.3390/universe8020076.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2022, Universe, 8, 76, 10.3390/universe8020076

Reference 54

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source=arxiv_source observed=2026-08-07T11:15:57.230062Z digest=sha256:b1097144f88d746a372c7ad36727182212d736c16851e7ec56b2bd309e9f8229

Observation 3f20eede-d4f9-4e7f-9178-6f469419c538 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 55

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source=arxiv_source observed=2026-08-07T11:15:57.303812Z digest=sha256:0513ce746ae848057e93d15a294f4fcf0f57b5a389955ee8621182dd45fe33ec

Observation 31272196-dac5-41ee-bf27-0efb9e06463d · outbound

This paper cites D., & Quinn, H.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks D., & Quinn, H

Reference 56

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source=arxiv_source observed=2026-08-07T11:15:57.415197Z digest=sha256:558836395a9461031753b3a8e05346fcee7c0fda7e464b1af1428bb00cd4a3b6

Observation 5cb6b8c9-0f12-455d-b3d4-509151f7c4db · outbound

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

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2020, , 641, A6, 10.1051/0004-6361/201833910

Reference 57

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source=arxiv_source observed=2026-08-07T11:15:57.596084Z digest=sha256:95a404f2a3e5bb3a05dfea1f11cd51cd4ade63f64e9058b2b209131eff5e99d2

Observation a491a401-f7d5-4053-a143-a09aff632bf9 · outbound

This paper cites On the Spectral Bias of Neural Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks On the Spectral Bias of Neural Networks

Reference 58

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source=arxiv_source observed=2026-08-07T11:15:57.724446Z digest=sha256:35a0aa33e5f7579a7bf921634b1421bd9f72f1c3d8a0f85172850e1422b5e2ff

Observation 3cee0267-6dd7-49af-a592-f1236d9a8b09 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 59

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source=arxiv_source observed=2026-08-07T11:15:57.869982Z digest=sha256:b94624f523399855a6aa7a48458064acf593b7ff0c7018ea18538284322914ab

Observation 08b29e2a-df96-494a-983c-dd7a6d5e5af8 · outbound

This paper cites Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data

Reference 60

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source=arxiv_source observed=2026-08-07T11:15:57.960014Z digest=sha256:df9aae3c83065d37c790d9cbf8a1ba4bf331f0c5360ed5dfc560cd600849cd30

Observation eb40ac2d-761d-47bf-92eb-577ee1ccb36c · outbound

This paper cites Challenges in Training PINNs: A Loss Landscape Perspective.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Challenges in Training PINNs: A Loss Landscape Perspective

Reference 61

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source=arxiv_source observed=2026-08-07T11:15:58.021686Z digest=sha256:9d7542e0186e65785676bf74a30b8ebfc7f8f38922323b6bb8970a21319337e6

Observation 522c4b38-5c2b-4189-9c57-e9903342149d · outbound

This paper cites 2024, Physics of Fluids, 36, 036129, 10.1063/5.0200384.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2024, Physics of Fluids, 36, 036129, 10.1063/5.0200384

Reference 62

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source=arxiv_source observed=2026-08-07T11:15:58.097312Z digest=sha256:b06e92645897db9b119dc2e8247f7752f86831e9eb4fb8a749d453dfd7ddb974

Observation 55c4cf4d-5bb6-43fd-9eb4-4a3e2fc9568a · outbound

This paper cites T., Singh, S., & Guestrin, C.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks T., Singh, S., & Guestrin, C

Reference 63

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source=arxiv_source observed=2026-08-07T11:15:58.197075Z digest=sha256:8c093febca2c9fb1f98bf4d7ed1f9b778662f47257a9868e11a15ef98d94262f

Observation 06569a6b-eac4-4c77-9dcd-42258286a980 · outbound

This paper cites G., Filippenko , A.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks G., Filippenko , A

Reference 64

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source=arxiv_source observed=2026-08-07T11:15:58.283030Z digest=sha256:fa0be9ca275dfeb4d64450128069c182f37526181d68774507ad1cc6387070d2

Observation ae915ed2-012a-4a77-a160-65084985e685 · outbound

This paper cites C., Ford , Jr., W.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks C., Ford , Jr., W

Reference 65

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source=arxiv_source observed=2026-08-07T11:15:58.353045Z digest=sha256:0468de78a13e9eb9c7ca4a7351efff3f740a5033989872fd756c08f01fbc918a

Observation dddbbd33-98dc-4c89-9e72-0386a7567fda · outbound

This paper cites V., Wetzel , A., & Fattahi , A.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks V., Wetzel , A., & Fattahi , A

Reference 66

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source=arxiv_source observed=2026-08-07T11:15:58.435315Z digest=sha256:4f648588fb82a23e24e999967f387df817896fbbf9d75dea1759b8929d22df54

Observation 44c8270b-4add-4ea5-924f-9933d8f8d852 · outbound

This paper cites G., Sc \'o ccola , C.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks G., Sc \'o ccola , C

Reference 67

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source=arxiv_source observed=2026-08-07T11:15:58.505038Z digest=sha256:273932e3962d03bf78e6b7cb3dc0f7293585eb361db494acc14024f63ab98dd6

Observation 9f819db7-5cfe-4703-b8b1-918f45c27ff8 · outbound

This paper cites 2014, Nature Physics, 10, 496, 10.1038/nphys2996.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2014, Nature Physics, 10, 496, 10.1038/nphys2996

Reference 68

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source=arxiv_source observed=2026-08-07T11:15:58.581387Z digest=sha256:5f3f7268b54a156307a14fd2acd614ca2c5b00783b7499049e1f9d9a9ba50154

Observation 39fcdb3c-ed83-4193-a128-17e38ac47190 · outbound

This paper cites 2016, , 818, 89, 10.3847/0004-637X/818/1/89.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2016, , 818, 89, 10.3847/0004-637X/818/1/89

Reference 69

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source=arxiv_source observed=2026-08-07T11:15:58.670669Z digest=sha256:0d5cddf034ef5eb5122c5d375260c5e2f57bee164117267545cc7cfacf6c5741

Observation 0927470b-5bba-4ff6-90b1-6a64ddf4a209 · outbound

This paper cites Physics-Informed Kolmogorov-Arnold Networks for Power System Dynamics.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Physics-Informed Kolmogorov-Arnold Networks for Power System Dynamics

Reference 70

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source=arxiv_source observed=2026-08-07T11:15:58.751943Z digest=sha256:13510f86896bb9536bd0a9bcead01d7d4cb682635c9a8d9fe654cae6940a2345

Observation 4cbf96f6-c52f-4cd8-8adc-9b3ee3bd4eb9 · outbound

This paper cites 2021, Reviews of Modern Physics, 93, 015004, 10.1103/RevModPhys.93.015004.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, Reviews of Modern Physics, 93, 015004, 10.1103/RevModPhys.93.015004

Reference 71

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source=arxiv_source observed=2026-08-07T11:15:58.834836Z digest=sha256:e1aa7361156eee48d838fe015c174099e4ca8056a0f3c10ffdf1fbc65366c6b8

Observation b7ba01de-9a4f-4793-9846-0da4f94764ad · outbound

This paper cites 2022, Phys.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2022, Phys

Reference 72

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source=arxiv_source observed=2026-08-07T11:15:58.905255Z digest=sha256:937bd8b7aae84354cafcb38633c145c772e31f95b3d9d790de1b2db8a0375a70

Observation 305eef36-88dc-47d0-8120-cd0ca5439f1c · outbound

This paper cites Implicit Neural Representations with Periodic Activation Functions.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Implicit Neural Representations with Periodic Activation Functions

Reference 73

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Observation 9d25c6a9-6e18-4554-bc11-b4b9d93a941e · outbound

This paper cites 2020, Computer Methods in Applied Mechanics and Engineering, 361, 112732, 10.1016/j.cma.2019.112732.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2020, Computer Methods in Applied Mechanics and Engineering, 361, 112732, 10.1016/j.cma.2019.112732

Reference 74

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Observation 492c8ec2-fb6d-4b53-bd00-d621cc37557a · outbound

This paper cites Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 75

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Observation a4b1a95c-2f3d-4f90-b336-384ba98c6fc2 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 76

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Observation c9fd57b4-3097-4de3-b457-5eec249490b8 · outbound

This paper cites 2021, SIAM Journal on Scientific Computing, 43, A3055, 10.1137/20M1318043.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2021, SIAM Journal on Scientific Computing, 43, A3055, 10.1137/20M1318043

Reference 77

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Observation 902dbdd1-c241-4ff5-ba40-5c7cd1cddb1c · outbound

This paper cites When and why PINNs fail to train: A neural tangent kernel perspective.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks When and why PINNs fail to train: A neural tangent kernel perspective

Reference 78

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Observation 0b8b08fe-67cc-48ce-9e86-809726703259 · outbound

This paper cites H., Bullock , J.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks H., Bullock , J

Reference 79

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source=arxiv_source observed=2026-08-07T11:15:59.532105Z digest=sha256:f8907e9524cf8d17b8aefe4d1f6bd3a2222cf192e42824a320049b7042f17018

Observation 6b6158ae-f20a-4fb3-be98-4c666d4ab212 · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 80

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source=arxiv_source observed=2026-08-07T11:15:59.614235Z digest=sha256:16c7a63329eebd1cee883e06f20a2c12686a0cee17ac6316a49dc0ca2bfcd727

Observation c90c5969-3c71-4755-9fdc-b8e6bc503e0f · outbound

This paper cites 1969, SIAM Review, 11, 226, 10.1137/1011036.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 1969, SIAM Review, 11, 226, 10.1137/1011036

Reference 81

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source=arxiv_source observed=2026-08-07T11:15:59.708966Z digest=sha256:9c051997dd9a3eb772036fcd4d465e1bda135121cab64a5fccc8cf4959609a8c

Observation 9dd2c8cb-3c54-4102-84c0-5074a1202ab3 · outbound

This paper cites 1971, SIAM Review, 13, 185, 10.1137/1013035.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 1971, SIAM Review, 13, 185, 10.1137/1013035

Reference 82

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Observation 23b6bf8f-b267-4b6c-8d56-f6d903480261 · outbound

This paper cites Learning in Sinusoidal Spaces with Physics-Informed Neural Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Learning in Sinusoidal Spaces with Physics-Informed Neural Networks

Reference 83

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Observation 5903e98b-b358-4b94-84c2-77c62df59d86 · outbound

This paper cites ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks

Reference 84

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Observation b13efeb8-4952-4e41-94b4-5944266f9907 · outbound

This paper cites Sub-Sequential Physics-Informed Learning with State Space Model.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Sub-Sequential Physics-Informed Learning with State Space Model

Reference 85

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source=arxiv_source observed=2026-08-07T11:16:00.005795Z digest=sha256:c361e5e8c27d7d375bfd56fbd6fe2fbaeda9d27874fa51964ca7d6d4a87e663f

Observation bdf7a163-4dcf-4230-b81a-98f9b010ad1d · outbound

This paper cites an unresolved cited work.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Unresolved cited work

Reference 86

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source=arxiv_source observed=2026-08-07T11:16:00.075063Z digest=sha256:debd5405698455e68971cf7347caf3e9652dec54370bc5d62ab4683f689e670f

Observation b8018ee2-96ae-4506-aa1c-a936e625ae4a · outbound

This paper cites 2024, Journal of Computational Physics, 515, 113284, https://doi.org/10.1016/j.jcp.2024.113284.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2024, Journal of Computational Physics, 515, 113284, https://doi.org/10.1016/j.jcp.2024.113284

Reference 87

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source=arxiv_source observed=2026-08-07T11:16:00.132206Z digest=sha256:6912ee25554b5b3b3110a6d63979c3ef970a0c92274e162594085cb153271853

Observation d0ac9153-f18e-4766-bc0c-3aaa8a645ebb · outbound

This paper cites 2018, Frontiers in Astronomy and Space Sciences, 5, 48, 10.3389/fspas.2018.00048.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2018, Frontiers in Astronomy and Space Sciences, 5, 48, 10.3389/fspas.2018.00048

Reference 88

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source=arxiv_source observed=2026-08-07T11:16:00.240788Z digest=sha256:f90fc4000c6e5e65f1891a9497858fd7b1bdf2bd6ff4270f86e25b400764cc71

Observation d865d790-05fc-4a4e-b382-4c3fe35b03c0 · outbound

This paper cites H., Mo, H.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks H., Mo, H

Reference 89

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Observation 0f90cf8b-b2cf-44bf-8c28-70f1962c67a3 · outbound

This paper cites PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Reference 90

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source=arxiv_source observed=2026-08-07T11:16:00.431695Z digest=sha256:41869f578f2d699785f9f1bf5dfeea1e22e8439d1e293b73e10e5861b424cfb5

Observation 6ecbc6f0-ff3d-4ed7-97dc-89a7bdc2e991 · outbound

This paper cites 2019, Journal of Computational Physics, 394, 56, 10.1016/j.jcp.2019.05.024.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks 2019, Journal of Computational Physics, 394, 56, 10.1016/j.jcp.2019.05.024

Reference 91

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source=arxiv_source observed=2026-08-07T11:16:00.434563Z digest=sha256:a89e897655b9233a0f79b10325f7b84276650106134d5826c8d23a3c10947b55

Pith citing papers

Observation 14af15f5-5c78-4e66-ae33-c8a363cf5255 · inbound

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks cites this paper.

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks

Reference 27

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