Paper Citation Record · LEDGER

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach

As of 14 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2501.16243.

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

pith.paper-citation-record.v1
2501.16243 v3

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:46:18.478733Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

40 of 40 outbound references displayed

verified exact1
verified fuzzy25
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d5c47d6e-8313-453a-b8bb-eeec269c7b5b · outbound

This paper cites write newline.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.215759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3bac0a4-8e15-4bbc-afcb-0e318e538da9 · outbound

This paper cites M., Lee, J.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach M., Lee, J

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.210346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d5644cc9-c969-4dfc-b088-f3ea306a04b7 · outbound

This paper cites M., Lee, J.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach M., Lee, J

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.229752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 404c4286-9241-4961-9680-cb5a3068ef76 · outbound

This paper cites O., Ghosh, A., and Aggarwal, V.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach O., Ghosh, A., and Aggarwal, V

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.181149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5e3f83a2-33c7-4a4b-a3f6-d465de853708 · outbound

This paper cites S., and Aggarwal, V.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach S., and Aggarwal, V

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.164653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eae5daed-6d60-45a3-a5b5-47cce0fe7420 · outbound

This paper cites and Bartlett, P.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach and Bartlett, P

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.144290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 295ac583-0f95-4ba7-a756-9157879c044b · outbound

This paper cites Quantum amplitude amplification and estimation.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum amplitude amplification and estimation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.128801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8ff98503-963e-451f-a515-6cddcc0f908b · outbound

This paper cites Quantum bandits.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum bandits

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.112194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1c6a3bc6-aa7c-421c-b385-1d94ec1b3ea6 · outbound

This paper cites Near-optimal quantum algorithms for multivariate mean estimation.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Near-optimal quantum algorithms for multivariate mean estimation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.098582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 42d025c6-641b-4aab-88d8-8ce07d15268f · outbound

This paper cites Quantum reinforcement learning.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum reinforcement learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.081128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 29ae8188-d93b-4a9d-9aa9-99d01a78ee95 · outbound

This paper cites M., and Briegel, H.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach M., and Briegel, H

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.065463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2804b376-a235-49a1-8611-766ad7ef6cfd · outbound

This paper cites U., and Aggarwal, V.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach U., and Aggarwal, V

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.051579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7908f74e-771a-434b-b495-62b6e1fea24f · outbound

This paper cites Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-10T13:46:18.612116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fbfe318f-bf57-4fa4-83c3-f38695fd0e7e · outbound

This paper cites Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T13:46:18.585626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e809ed3c-b9df-43c0-8d24-7115510e088e · outbound

This paper cites W., McKee, J., Hager, G., Aggarwal, V., Xue, Y., et al.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach W., McKee, J., Hager, G., Aggarwal, V., Xue, Y., et al

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.038666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0ca16b0f-4ca2-4bca-80c6-b72b11b7450a · outbound

This paper cites Creating superpositions that correspond to efficiently integrable probability distributions.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Creating superpositions that correspond to efficiently integrable probability distributions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.316908Z

Source-reported events for the cited work

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Observation 3f0248a9-9bd2-4ccd-a55e-be0dd5d58721 · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:19.024795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bb14b24d-8db1-4452-b270-4cda4d1ff195 · outbound

This paper cites Quantum sub-gaussian mean estimator.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum sub-gaussian mean estimator

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:19.011973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f4d6e5a6-e21d-4b91-bc81-50bef315d43e · outbound

This paper cites M., Nautrup, H.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach M., Nautrup, H

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.995776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5bd51ae5-de70-4a37-ae1e-7f14e0c2afcf · outbound

This paper cites Quantum policy gradient algorithms.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum policy gradient algorithms

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.977086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c638e435-f701-432f-82f8-c55855952424 · outbound

This paper cites An improved analysis of (variance-reduced) policy gradient and natural policy gradient methods.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach An improved analysis of (variance-reduced) policy gradient and natural policy gradient methods

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.958390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 616994db-99d3-4fee-937c-7bb69aa6d41c · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.943746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5aa06c5d-564d-43e8-98a4-9d9e0293dbd1 · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.928785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 464cca96-2515-465b-a734-b42accbcff75 · outbound

This paper cites Quantum speedup of monte carlo methods.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum speedup of monte carlo methods

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.912762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dc005ce3-fa30-45ea-9713-160264ed25b5 · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.895794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fd4dcedf-32e2-4882-9d3b-2bc03a2e6e66 · outbound

This paper cites D., Dunjko, V., Makmal, A., Martin-Delgado, M.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach D., Dunjko, V., Makmal, A., Martin-Delgado, M

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.875527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 37b96099-8973-4966-bb60-033671711ab3 · outbound

This paper cites and Schaal, S.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach and Schaal, S

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.854424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 03cdfe46-0ac6-442a-a251-6626bbf78ce6 · outbound

This paper cites and Zhang, C.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach and Zhang, C

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.836909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dc57a5e3-fb26-4deb-a1d8-291de3636411 · outbound

This paper cites S., McAllester, D., Singh, S., and Mansour, Y.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach S., McAllester, D., Singh, S., and Mansour, Y

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.402908Z

Source-reported events for the cited work

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Observation 57bb01d1-fb2a-4db3-955a-19f79b5b57eb · outbound

This paper cites P., Yu, D., and Aggarwal, V.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach P., Yu, D., and Aggarwal, V

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.806835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b4f3d51a-cdd0-4a4a-bfff-d2d85d6c700e · outbound

This paper cites Quantum multi-armed bandits and stochastic linear bandits enjoy logarithmic regrets.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum multi-armed bandits and stochastic linear bandits enjoy logarithmic regrets

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.782423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 43d65252-0114-4900-8a7c-40cfe863b8df · outbound

This paper cites Quantum algorithms for reinforcement learning with a generative model.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum algorithms for reinforcement learning with a generative model

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.762175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 10245b49-5810-47be-bc17-fb94c94ce411 · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.742582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d52d2c68-c7ed-466a-a406-97e7aab9e1c3 · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.728065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7ebd41d6-923e-4a01-80a2-be19c57d5aeb · outbound

This paper cites Neural policy gradient methods: Global optimality and rates of convergence.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Neural policy gradient methods: Global optimality and rates of convergence

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.712904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 482320dd-70dc-4598-a2ab-a5a0f36a0a8b · outbound

This paper cites an unresolved cited work.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:46:18.696134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 91445b63-2d3b-43f9-9f36-fff9470504b6 · outbound

This paper cites Quantum Heavy-tailed Bandits.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Quantum Heavy-tailed Bandits

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.462321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d48dea98-520a-49a5-863c-f933ca4cd7a1 · outbound

This paper cites Sample efficient policy gradient methods with recursive variance reduction.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Sample efficient policy gradient methods with recursive variance reduction

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.674584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4f87009a-74de-4ab1-904f-e5df910b84e8 · outbound

This paper cites Global convergence of policy gradient methods to (almost) locally optimal policies.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Global convergence of policy gradient methods to (almost) locally optimal policies

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T13:46:18.473418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28716c83-1b52-46a4-ad54-ee3718a94147 · outbound

This paper cites Provably efficient exploration in quantum reinforcement learning with logarithmic worst-case regret.

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach Provably efficient exploration in quantum reinforcement learning with logarithmic worst-case regret

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:46:18.635523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.