Paper Citation Record · LEDGER

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.20832.

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

pith.paper-citation-record.v1
2606.20832 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T15:17:55.188215Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact2
verified fuzzy0
unresolved28
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c5aec30-bac4-436b-9f39-5547a35efa6c · outbound

This paper cites A., 2003.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems A., 2003

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c19c48ca-ba99-43f8-8a05-7ccc3e883200 · outbound

This paper cites an unresolved cited work.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edae10c8-fb79-426a-a492-30d65dafb1c6 · outbound

This paper cites & Hut, P., 1986.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Hut, P., 1986

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52dac318-2120-43b9-bfb3-f1714b9d845c · outbound

This paper cites & Portegies Zwart , S., 2015.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Portegies Zwart , S., 2015

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42617341-ce54-4520-8087-93942625f381 · outbound

This paper cites G., Foley , C.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems G., Foley , C

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c87116-c37b-47eb-be6d-c2c481eaa1ac · outbound

This paper cites E., 2021.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems E., 2021

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62bfcfde-5d84-4bbe-8812-83ec4219b31d · outbound

This paper cites an unresolved cited work.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58f144de-caef-41df-9f73-81218312b77e · outbound

This paper cites an unresolved cited work.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcf38bc2-302b-4f21-91e8-b8f6f452ce7a · outbound

This paper cites Hamiltonian neural networks, Advances in neural information processing systems\/ , 32.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Hamiltonian neural networks, Advances in neural information processing systems\/ , 32

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 631f69be-bbcb-42b8-8a4f-ffa630c6ebc2 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Soft Actor-Critic Algorithms and Applications

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-04T05:49:38.233933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f477f337-50ba-49f9-a282-46e80482b15d · outbound

This paper cites & Hut , P., 2003.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Hut , P., 2003

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52467a34-3ee1-4686-b262-98b4a363d05d · outbound

This paper cites A connected component-based method for efficiently integrating multi-scale n-body systems, Astronomy & Astrophysics\/ , 570 , A20.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems A connected component-based method for efficiently integrating multi-scale n-body systems, Astronomy & Astrophysics\/ , 570 , A20

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91028bc1-f0dd-4af2-bbc5-d4fddb1bba7e · outbound

This paper cites & Ida, S., 2002.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Ida, S., 2002

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79ba6a9b-a579-4dbd-9907-86dac38d788e · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Playing Atari with Deep Reinforcement Learning

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-04T05:49:38.229810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a4e11778-c414-4704-b09d-f6a2888ad647 · outbound

This paper cites A., Veness, J., Bellemare, M.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems A., Veness, J., Bellemare, M

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 323cf6ae-2376-44f5-a60a-cff9f43e9e88 · outbound

This paper cites & Towers, M., 2025.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Towers, M., 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae8547b5-e133-4d9a-a1fb-45cca8fd1e0f · outbound

This paper cites I., J \"a nes , J., & Portegies Zwart , S., 2012.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems I., J \"a nes , J., & Portegies Zwart , S., 2012

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbb20e7a-70c0-49f6-8d07-bc21a18d2a86 · outbound

This paper cites & McMillan , S., 2018.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & McMillan , S., 2018

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce2bdcfe-685d-4bdb-8b56-72735433c1e3 · outbound

This paper cites an unresolved cited work.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 534a332f-bde2-442e-837f-5b002a685be8 · outbound

This paper cites Non-intrusive hierarchical coupling strategies for multi-scale simulations in gravitational dynamics, Communications in Nonlinear Science and Numerical Simulation\/ , 85 , 105240.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Non-intrusive hierarchical coupling strategies for multi-scale simulations in gravitational dynamics, Communications in Nonlinear Science and Numerical Simulation\/ , 85 , 105240

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f1ecaaf-38ee-4241-9a6c-eecde97105c3 · outbound

This paper cites Astrophysical Recipes; The art of AMUSE \/ , 2514-3433, IOP Publishing.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Astrophysical Recipes; The art of AMUSE \/ , 2514-3433, IOP Publishing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d319d6b-ddd0-4b74-9a85-0f5888f3025d · outbound

This paper cites F., McMillan, S.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems F., McMillan, S

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84c2ec2c-c3ad-49c5-afe7-852a3b4a1f10 · outbound

This paper cites F., Boekholt , T.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems F., Boekholt , T

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 153bf92c-2b43-431a-ba9a-9742beab2931 · outbound

This paper cites E., 1955.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems E., 1955

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f08912a-0705-4fd7-aa69-db0d149798dc · outbound

This paper cites & Portegies Zwart, S., 2025.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems & Portegies Zwart, S., 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88f79942-8c51-4a28-9434-8fc11a62f7c9 · outbound

This paper cites X., 2024.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems X., 2024

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0898d5d-e77b-4d6c-96e8-53b9e2ccf0fa · outbound

This paper cites an unresolved cited work.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d434d9-599c-4a6e-8ee7-7da4a737e9b0 · outbound

This paper cites The statistical mechanics of planet orbits, The Astrophysical Journal\/ , 807 (2), 157.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems The statistical mechanics of planet orbits, The Astrophysical Journal\/ , 807 (2), 157

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d39971-9448-4e8a-8e8d-e2d45cfe73e9 · outbound

This paper cites A review on deep reinforcement learning for fluid mechanics: An update, Physics of Fluids\/ , 34 (11), 111301.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems A review on deep reinforcement learning for fluid mechanics: An update, Physics of Fluids\/ , 34 (11), 111301

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a10ff0a-258b-4bb0-8c48-ce358b5039fa · outbound

This paper cites Historical best q-networks for deep reinforcement learning, in 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\/ , pp.

ReLaTS: a Reinforcement Learning-based method for dynamically determining the coupling Time Step in multi-scale simulations of self-gravitating systems Historical best q-networks for deep reinforcement learning, in 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\/ , pp

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-26T15:17:55.188215Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.