Paper Citation Record · LEDGER

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method

As of 13 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2411.15914.

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

pith.paper-citation-record.v1
2411.15914 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:51:26.195184Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

14 of 14 outbound references displayed

verified exact1
verified fuzzy7
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e75b1294-8655-4376-b3e0-c753a4548b80 · outbound

This paper cites an unresolved cited work.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:51:26.422707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e78c8ac8-f09b-44ee-8da4-dded22841d28 · outbound

This paper cites The Journal of Physical Chemistry Letters 2022, 13, 6037–6041, PMID: 35749307.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method The Journal of Physical Chemistry Letters 2022, 13, 6037–6041, PMID: 35749307

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.299107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 620840c4-3d07-4af9-ae2e-43c4639a0271 · outbound

This paper cites an unresolved cited work.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:51:26.395887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7682842b-0e61-4c0c-904b-8f06eb5bee42 · outbound

This paper cites an unresolved cited work.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:51:26.341603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9be9141a-e296-40ee-b952-2415c52ef76e · outbound

This paper cites Predicting quantum evolutions of excitation energy transfer in a light-harvesting complex using multi-optimized recurrent neural networks.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Predicting quantum evolutions of excitation energy transfer in a light-harvesting complex using multi-optimized recurrent neural networks

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-12T13:51:26.254348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b03fbbb-0909-4940-8478-a4cccd7c3466 · outbound

This paper cites P.; Lesanovsky, I.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method P.; Lesanovsky, I

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.382157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d3162dcb-dd8d-461d-b9d2-a25df7ffe7f8 · outbound

This paper cites Discrete Time-Crystalline Order in Cavity and Circuit QED Systems.Physical review letters 2017, 120 4, 040404.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Discrete Time-Crystalline Order in Cavity and Circuit QED Systems.Physical review letters 2017, 120 4, 040404

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.369918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e4725380-42ac-4c30-83a7-c9884b6f1895 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Deep Residual Learning for Image Recognition

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-12T13:51:26.195184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3396999-f0be-43b2-aba5-646f18dabefb · outbound

This paper cites Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning.Ge- netic Programming and Evolvable Machines 2018, 19, 305–307.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning.Ge- netic Programming and Evolvable Machines 2018, 19, 305–307

Reference 125

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.356682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3edbf814-3306-4231-b85f-d358a20b4ec0 · outbound

This paper cites Variational Neural-Network Ansatz for Steady States in Open Quantum Systems.Phys.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Variational Neural-Network Ansatz for Steady States in Open Quantum Systems.Phys

Reference 155

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.313421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e70ac37a-8fc3-46f7-80ec-4814733b7648 · outbound

This paper cites an unresolved cited work.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Unresolved cited work

Reference 1993

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:51:26.409493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 675c7a53-55d6-4d98-8e19-e6bb9254fbf4 · outbound

This paper cites J.; Zhao, T.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method J.; Zhao, T

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.284953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8da8140b-0d46-4ac0-8377-30156432371c · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-12T13:51:26.163438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31154481-47dc-42de-ba08-86df7068175c · outbound

This paper cites Forecasting Nonadiabatic Dynamics using Hybrid Convolutional Neural Network/Long Short-Term Memory Network.

Enhancing Open Quantum Dynamics Simulations Using Neural Network-Based Non-Markovian Stochastic Schr\"odinger Equation Method Forecasting Nonadiabatic Dynamics using Hybrid Convolutional Neural Network/Long Short-Term Memory Network

Reference 2483

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:26.327804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.