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Paper Citation Record · LEDGER

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations

As of 18 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2501.16509.

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

pith.paper-citation-record.v1
2501.16509 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T12:51:37.793031Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c52d5d2a-64b0-4457-8f74-87407d21654f · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations , " * write output.state after.block = add.period write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T12:51:37.741264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T12:51:37.741264Z digest=sha256:999b54ea241f83a81b69632863df557d00d1db8a9253634e2136acd0069b7b71

Observation fb39f5dc-8a7e-4776-8d77-bd284eb02ead · outbound

This paper cites write newline.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T12:51:37.746989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T12:51:37.746989Z digest=sha256:340526a17b263c7b09ab2de6eb3574285ea6e9227b1fa3a158e0f99ce8428e2b

Observation 6149b581-be24-44b8-b7df-a86b56fe1a92 · outbound

This paper cites B.; Hirayama, T.; Yamanaka, K.; and Nishitani, Y.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations B.; Hirayama, T.; Yamanaka, K.; and Nishitani, Y

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T12:51:37.950711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.752789Z digest=sha256:5b6736a3fcf9ed337e97181f3cf88723e4efb1ac5a93623cea9781fe7f4cc5a3

Observation 85410972-5d4d-45d1-83f9-743c19fe1125 · outbound

This paper cites C.; Barends, R.; Biswas, R.; Boixo, S.; Brandao, F.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations C.; Barends, R.; Biswas, R.; Boixo, S.; Brandao, F

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T12:51:37.936619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.757890Z digest=sha256:c6d21a01b6c18f566dad7d81a6e098ea9ae6f126eefc94bd5bf3121c1dc38c38

Observation f073340e-6e35-40dc-9100-35b539cfeaf0 · outbound

This paper cites A.; Khanday, F.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations A.; Khanday, F

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T12:51:37.920754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.763380Z digest=sha256:9dac14b8ec9f6dc6097d96bfe677eb6bda1c59639db5a4f0ad24506df36c63e0

Observation 7bbe92da-3684-4c71-9fa3-cbbe880bfef5 · outbound

This paper cites Quantum Computing: A Taxonomy, Systematic Review and Future Directions.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations Quantum Computing: A Taxonomy, Systematic Review and Future Directions

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T12:51:37.768342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T12:51:37.768342Z digest=sha256:0b2ab62a9376f46876612cc6d7d3f1d830c9810a558cab5713ab01407bdaeab8

Observation 81d21769-ef3f-4423-82c7-8ea1cd7874e5 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-10T12:51:37.906095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.773728Z digest=sha256:5e9841b559d03c74444bee1229f233ea82dc8514acf964e092cb05a7bf4edbb2

Observation 0b3869f1-ff36-42b2-9d4e-e9325e00a5e2 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-10T12:51:37.889792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.778292Z digest=sha256:48f1e6e42bc5a0dff4edf00beb478e89cc6129961895ebec1c0d6df3ff0aea49

Observation b31e9d71-33f6-4da2-9e73-229f692ca5a5 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations Playing Atari with Deep Reinforcement Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T12:51:37.783674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T12:51:37.783674Z digest=sha256:a4a4662274322447e4422e916a75227d6d4e2ccc480118619f4d3dbd0ce2bc7e

Observation 9970a34e-7ec3-441c-8925-0d37b04913ef · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-10T12:51:37.874721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.788504Z digest=sha256:e7793f4a4497415f0480529959208723f6f02640a9122e86671139122343b6eb

Observation a9616281-1ba7-4067-8f6d-bdda0b6c802e · outbound

This paper cites J.; and Dayan, P.

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations J.; and Dayan, P

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T12:51:37.859871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T12:51:37.793031Z digest=sha256:c2d4648a0eaedf83806827d00d66c5ee9ad7d25f1ec05796a04534801d86629f

Pith citing papers

No inbound Pith citation observations are available.