Paper Citation Record · LEDGER

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2411.17853.

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

pith.paper-citation-record.v1
2411.17853 v1

Coverage vector

measured 39 of 39 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-12T11:51:07.397360Z

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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 2026-08-11T22:21:35.105251Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

39 of 39 outbound references displayed

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pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation aefaf842-76b1-4b4f-9d59-f5f79ca5c52c · outbound

This paper cites 2015, TensorFlow: Large-Scale Ma- chine Learning on Heterogeneous Systems, software available from tensor- flow.org.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2015, TensorFlow: Large-Scale Ma- chine Learning on Heterogeneous Systems, software available from tensor- flow.org

Reference 1

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Observation a355864e-f764-4a34-b163-6534ac21a077 · outbound

This paper cites 2019, Optuna: A Next- generation Hyperparameter Optimization Framework.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2019, Optuna: A Next- generation Hyperparameter Optimization Framework

Reference 2

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Observation 537943e6-bda3-42e6-a051-d93d715dc684 · outbound

This paper cites S., Bell, J.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning S., Bell, J

Reference 3

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Observation 02087d6c-c239-45ec-941d-e53e162a61cd · outbound

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

Reference 4

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Observation 78bd7076-c066-4c85-af6e-db0a9949f89c · outbound

This paper cites D., Bolton, J.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning D., Bolton, J

Reference 5

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Observation 5d78080e-5971-430d-b461-705066cff2f4 · outbound

This paper cites S., Puchwein, E., Sijacki, D., et al.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning S., Puchwein, E., Sijacki, D., et al

Reference 6

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

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Observation f5369b02-381b-434f-b9b5-0e0d63eaede0 · outbound

This paper cites S., & Kaplinghat, M.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning S., & Kaplinghat, M

Reference 10

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This paper cites & Kochanek, C.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning & Kochanek, C

Reference 11

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Observation adecb089-f6ff-4528-936c-5b9cf56e0ca3 · outbound

This paper cites 2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Se- ries, V ol.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Se- ries, V ol

Reference 12

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Observation b153758e-5065-4077-b662-a5dc8756d26f · outbound

This paper cites J., Zehavi, I., Hogg, D.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning J., Zehavi, I., Hogg, D

Reference 13

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This paper cites K., Strauss, M.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning K., Strauss, M

Reference 14

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Observation 0d178fd3-bae4-445d-bb61-b9b43f538571 · outbound

This paper cites 2021, Proceedings of the IEEE, 109, 683–703.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2021, Proceedings of the IEEE, 109, 683–703

Reference 15

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Observation 74adf7ea-153a-4fa9-be14-b95a451cf072 · outbound

This paper cites G., et al.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning G., et al

Reference 16

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Observation 2fc3a667-4804-4ad1-a204-3d6b09f15e0c · outbound

This paper cites G., & Choudhury, T.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning G., & Choudhury, T

Reference 17

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

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Observation dbc20997-868c-411c-8f40-02872408732e · outbound

This paper cites & Ra ffelt, G.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning & Ra ffelt, G

Reference 19

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Observation 3274adb2-98b9-42df-b00c-a7b91dac0150 · outbound

This paper cites V ., Laga, H., Boussaid, F., Buntine, W., & Bennamoun, M.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning V ., Laga, H., Boussaid, F., Buntine, W., & Bennamoun, M

Reference 20

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Observation 0ea7d557-68c6-47a6-9271-ec41701e4ecf · outbound

This paper cites M., Diaz, R.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning M., Diaz, R

Reference 21

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Observation ad08e085-4d01-4119-8383-b4766617b810 · outbound

This paper cites 2024, Parameter esti- mation from Ly-alpha forest in Fourier space using Information Maximising Neural Network.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2024, Parameter esti- mation from Ly-alpha forest in Fourier space using Information Maximising Neural Network

Reference 22

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Observation fadadb51-f300-4b6c-bebd-60fce1efa98e · outbound

This paper cites W., Hayes, C.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning W., Hayes, C

Reference 23

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Observation ea75c9d9-afc3-493c-8806-0ead0123bf3c · outbound

This paper cites 1994, Nature, 370, 629.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 1994, Nature, 370, 629

Reference 24

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Observation 41478251-b03a-4ea7-94ec-afdd2f7ec2d1 · outbound

This paper cites T., Kacprzak, G.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning T., Kacprzak, G

Reference 25

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Observation 4961cee5-d200-413d-8f35-0ace7b94c3c5 · outbound

This paper cites B., et al.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning B., et al

Reference 26

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Observation 177c917d-d381-4b42-bc45-ca678ab5d4ef · outbound

This paper cites 2024, Astronomy and Astro- physics Planck Collaboration, Ade, P.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2024, Astronomy and Astro- physics Planck Collaboration, Ade, P

Reference 27

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Observation 4f6a3dd5-6ebd-43a2-a725-75a9d3419f7e · outbound

This paper cites S., Keating, L.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning S., Keating, L

Reference 28

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Observation 6c005bd4-cc5b-46af-ba23-bd9e92cd2245 · outbound

This paper cites G., & Madau, P.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning G., & Madau, P

Reference 29

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Observation b33059b9-01fa-4a16-98c6-23703a870cae · outbound

This paper cites 1999, MNRAS, 310, 57.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 1999, MNRAS, 310, 57

Reference 30

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Observation 283155a5-f163-4032-bbb7-e1633218b8de · outbound

This paper cites 2005, Monthly Notices of the Royal Astronomical Society, 364, 1105–1134 Van Waerbeke, L., Mellier, Y ., & Hoekstra, H.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2005, Monthly Notices of the Royal Astronomical Society, 364, 1105–1134 Van Waerbeke, L., Mellier, Y ., & Hoekstra, H

Reference 31

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Observation dec1956c-86aa-4634-a88e-fbfc72a9ad36 · outbound

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

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning G., Matarrese, S., & Riotto, A

Reference 32

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Observation ca04ccfd-488a-451f-89ff-c4109a33d082 · outbound

This paper cites 2021, Frontiers in As- tronomy and Space Sciences, 8.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2021, Frontiers in As- tronomy and Space Sciences, 8

Reference 33

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Observation 25f32594-6aca-4584-acd7-437188288b25 · outbound

This paper cites 2023, Physical Review D, 108 V ogelsberger, M., Genel, S., Springel, V ., et al.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2023, Physical Review D, 108 V ogelsberger, M., Genel, S., Springel, V ., et al

Reference 34

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Observation 4dca33f4-125a-43bc-af49-9cc2ea91792f · outbound

This paper cites 2015, The Astrophysical Journal, 807, L9.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2015, The Astrophysical Journal, 807, L9

Reference 35

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This paper cites 2023, Tree-Structured Parzen Estimator: Understanding Its Algo- rithm Components and Their Roles for Better Empirical Performance.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning 2023, Tree-Structured Parzen Estimator: Understanding Its Algo- rithm Components and Their Roles for Better Empirical Performance

Reference 36

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Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning Unresolved cited work

Reference 37

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Observation 39364b2b-81c3-464d-a600-4acba02c814f · outbound

This paper cites H., Bullock, J.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning H., Bullock, J

Reference 38

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Observation ff974fd3-5c5d-407d-af68-36373ee81406 · outbound

This paper cites F., Davies, F.

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning F., Davies, F

Reference 39

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Pith citing papers

Observation 1756abe9-2210-401f-b93a-a9aacb640e36 · inbound

Learning from galactic rotation curves: a neural network approach cites this paper.

Learning from galactic rotation curves: a neural network approach Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning

Reference 22

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Ringing of the Reionization: A first direct measurement of the intergalactic pressure smoothing scale at redshift z>4.2 as imprinted onto small-scale peculiar velocities in the Lyman-alpha forest cites this paper.

Ringing of the Reionization: A first direct measurement of the intergalactic pressure smoothing scale at redshift z>4.2 as imprinted onto small-scale peculiar velocities in the Lyman-alpha forest Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning

Reference 175

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