Pith. sign in

Paper Citation Record · LEDGER

Quantum circuit optimization with deep reinforcement learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2103.07585.

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

pith.paper-citation-record.v1
2103.07585 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:51:36.887098Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:30:08.178618Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 48e16d45-e35c-4d4f-bf57-fa005c74d5f0 · inbound

Leveraging Diffusion Models for Parameterized Quantum Circuit Generation cites this paper.

Leveraging Diffusion Models for Parameterized Quantum Circuit Generation Quantum circuit optimization with deep reinforcement learning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T13:51:36.887098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:51:36.887098Z digest=sha256:b3bbb5d568db1831b8e2dd30859d53ddd1f2af79a9c956370a9723d32220a1ae

Observation bad6a20c-f799-4f27-b82f-05453a3a2b64 · inbound

Quantum computing and artificial intelligence: status and perspectives cites this paper.

Quantum computing and artificial intelligence: status and perspectives Quantum circuit optimization with deep reinforcement learning

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T12:54:10.171153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:54:10.171153Z digest=sha256:c5cf6caaa5a5afb90ad5c6482d42aac383e9a0f2514a66da12f0d24f7e11949a

Observation a4ea25b8-7cef-42aa-bf5e-bc59ae271241 · inbound

Learning Circuits with Infinite Tensor Networks cites this paper.

Learning Circuits with Infinite Tensor Networks Quantum circuit optimization with deep reinforcement learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:36:38.830906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:36:38.830906Z digest=sha256:82d3ac6ae763f6fe33e95ff482dd4967e6a7005d8f0acb7af7a5e8cbab9b7d73

Observation fb0c0fe5-f6eb-497e-a449-d47089e201f7 · inbound

Quantum circuits as a game: A reinforcement learning agent for quantum compilation and its application to reconfigurable neutral atom arrays cites this paper.

Quantum circuits as a game: A reinforcement learning agent for quantum compilation and its application to reconfigurable neutral atom arrays Quantum circuit optimization with deep reinforcement learning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T10:26:04.826357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:26:04.826357Z digest=sha256:c03bebd2d003e3362e7af913aeecd01dba54134839eb9516329461e7d20feb35

Observation 06a7627d-b244-43d7-88f8-d9d8468c055e · inbound

Learning-Optimized Qubit Mapping and Reuse to Minimize Inter-Core Communication in Modular Quantum Architectures cites this paper.

Learning-Optimized Qubit Mapping and Reuse to Minimize Inter-Core Communication in Modular Quantum Architectures Quantum circuit optimization with deep reinforcement learning

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T10:37:14.868832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T10:36:59.885795Z digest=sha256:f900037d6e537a7ac691a21d094d419442fa893867dafeabe2fa101ea62d1551

Observation 3f101dd5-558f-4b99-b992-f9c2de042846 · inbound

Leveraging Phase Polynomials for Quantum Circuit Optimization cites this paper.

Leveraging Phase Polynomials for Quantum Circuit Optimization Quantum circuit optimization with deep reinforcement learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:34.046879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:34.046879Z digest=sha256:4efdca5852afeff7934ddd0c3548aa3e2c6d2af2e94b0545a74bf45c7963a06b

Observation 52ff00d4-ec67-4f17-a036-53f90b203339 · inbound

Quantum algorithms for equational reasoning cites this paper.

Quantum algorithms for equational reasoning Quantum circuit optimization with deep reinforcement learning

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:04:25.727663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T23:01:32.436890Z digest=sha256:49384fae40c3310045b33284e0213660421140f5f0161d4ea3cc2c9093ff9a37

Observation e452fce4-8fdc-4a5d-95e5-c9fca34807f0 · inbound

Artificial intelligence for representing and characterizing quantum systems cites this paper.

Artificial intelligence for representing and characterizing quantum systems Quantum circuit optimization with deep reinforcement learning

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:39.073548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:39.073548Z digest=sha256:035dad3093a29f152abfefdd5995bb47c07f51d57b143b76df5dc432b839afaa

Observation 6f73e97a-3155-45bb-85a2-568acd5f10d0 · inbound

Practical Fidelity Limits of Toffoli Gates in Superconducting Quantum Processors cites this paper.

Practical Fidelity Limits of Toffoli Gates in Superconducting Quantum Processors Quantum circuit optimization with deep reinforcement learning

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-05T05:41:44.266757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:41:44.266757Z digest=sha256:313850666c77c79b7dd309b25fe7e4eca6969b1af13e3d7bdbafaf244c801e50

Observation f36b7a9c-b0eb-4359-8b8a-26d2fcecadfb · inbound

Quantum feature-map learning with reduced resource overhead cites this paper.

Quantum feature-map learning with reduced resource overhead Quantum circuit optimization with deep reinforcement learning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T12:39:06.570386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:39:06.570386Z digest=sha256:9b7366f4bc471b56d9e4bd4ddc8d9bbade15ee0b370591563c6b1b87f4a19ad8

Observation 346dc48a-04b0-44a7-9ba8-d83559bccad7 · inbound

Reinforcement Learning Control of Quantum Error Correction cites this paper.

Reinforcement Learning Control of Quantum Error Correction Quantum circuit optimization with deep reinforcement learning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-03T22:54:51.351148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:54:51.351148Z digest=sha256:4274bed97522e0cb7e9ffbe98cb820175510c33b827b93fb800db3e3ed2bc482

Observation c87a9c53-fdb9-4354-8621-4c85aac70d87 · inbound

DeepQuantum: A PyTorch-based Software Platform for Quantum Machine Learning and Photonic Quantum Computing cites this paper.

DeepQuantum: A PyTorch-based Software Platform for Quantum Machine Learning and Photonic Quantum Computing Quantum circuit optimization with deep reinforcement learning

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:08:32.999197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T21:04:13.847669Z digest=sha256:240b66a665528873e4c6850424318a2d51800c9f1a55864bf3408ebedde0d86a

Observation 3f992d0f-3037-460c-bad5-0d62851831bc · inbound

Noise tolerance via reinforcement in the quantum search problem cites this paper.

Noise tolerance via reinforcement in the quantum search problem Quantum circuit optimization with deep reinforcement learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:00.959106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T17:05:42.367715Z digest=sha256:90e1e6bace5b63c45d5fd19a7fc5a1b0ec2b53ce40e5e6ce13beabe5518261cd

Observation a8e75765-ff4d-496f-8a9d-5ce0175cb743 · inbound

Investigation of Automated Design of Quantum Circuits for Imaginary Time Evolution Methods Using Deep Reinforcement Learning cites this paper.

Investigation of Automated Design of Quantum Circuits for Imaginary Time Evolution Methods Using Deep Reinforcement Learning Quantum circuit optimization with deep reinforcement learning

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:51:02.841444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T17:55:44.044291Z digest=sha256:2ac5c1d9357368f9c74a1869eee27a7e3c9d8eaeab55a65a3e1e863e1971172e

Observation 8ad1fb88-ec4f-4cc8-acb5-007c71c418bf · inbound

Replay-buffer engineering for noise-robust quantum circuit optimization cites this paper.

Replay-buffer engineering for noise-robust quantum circuit optimization Quantum circuit optimization with deep reinforcement learning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:16:11.399340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T22:11:29.151910Z digest=sha256:1fd199e2ce155b887500fba6e9e633ba0381c0713ade424cf3c9a820d99e8d7c

Observation d8f8a420-e15f-40a2-beef-8a4f7408f6d6 · inbound

Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with System-Size Generalization in 1D Heisenberg Hamiltonians cites this paper.

Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with System-Size Generalization in 1D Heisenberg Hamiltonians Quantum circuit optimization with deep reinforcement learning

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:46:26.066736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T09:33:16.864456Z digest=sha256:6dd88e5fb39f240fd2762d2b3916facb6341159eeaf0ce0eec3162fb107a7af5

Observation 63239b1e-dbed-4354-9680-a2488907836b · inbound

Learning quantum disentanglement scheduling from reduced states via modular hybrid policies cites this paper.

Learning quantum disentanglement scheduling from reduced states via modular hybrid policies Quantum circuit optimization with deep reinforcement learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:21:28.873230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T06:34:13.380471Z digest=sha256:13cc9b0c8fade63bb6fd493f3fc029b5f26871ada61515f7f6fbe8d8451c6012

Observation 165ed650-9739-40c4-b936-c5584c7fa06d · inbound

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver cites this paper.

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver Quantum circuit optimization with deep reinforcement learning

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:40:43.412749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T18:11:29.380162Z digest=sha256:898e12b3ca26453b5d63503a558453103b181b4aae25a97c30bd262f22cfdfb2

Observation e43b18ad-c8dc-465f-a739-547fced511e1 · inbound

Physics Guided Generative Optimization for Trotter Suzuki Decomposition cites this paper.

Physics Guided Generative Optimization for Trotter Suzuki Decomposition Quantum circuit optimization with deep reinforcement learning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-14T18:42:37.037798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-14T18:41:10.806780Z digest=sha256:b41241f219cd5084a95e485c9dc3048f5e6d858bc7c21120bc062a7f2294d866

Observation 4aa9421a-84a8-433c-a0b6-8c2df3d6541b · inbound

Physics Guided Generative Optimization for Trotter Suzuki Decomposition cites this paper.

Physics Guided Generative Optimization for Trotter Suzuki Decomposition Quantum circuit optimization with deep reinforcement learning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:55:05.889966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T21:52:20.008770Z digest=sha256:fc79f0301e0c2d0c73aae16d7a94c2978b7ad6d7375d8905297f060f1b7f9c1e

Observation 6f068959-701e-4c89-b04e-862986dd47a2 · inbound

Automatic De-Quantization of Quantum Programs Using Constant Propagation cites this paper.

Automatic De-Quantization of Quantum Programs Using Constant Propagation Quantum circuit optimization with deep reinforcement learning

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:36:40.032900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T05:32:50.992299Z digest=sha256:e8ad424de63b1d529ac7324e1fe3fc3bf07b942f376087d8fd31170d8d63b592

Observation 6289fa46-2c6f-4195-8437-c3e8b04af6b4 · inbound

Generative Quantum Data Embeddings for Supervised Learning cites this paper.

Generative Quantum Data Embeddings for Supervised Learning Quantum circuit optimization with deep reinforcement learning

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:36:09.461696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T22:10:38.902738Z digest=sha256:6a9f566d031b7fb8ceb2c67ced03add18cbbd08ae7bfa3f05fa37827e4b3c9fa

Observation 63dba04f-3765-4da0-a81f-8c03cb1416d4 · inbound

FactorLibrary: From Polynomials to Circuits via Recursive Subgoals cites this paper.

FactorLibrary: From Polynomials to Circuits via Recursive Subgoals Quantum circuit optimization with deep reinforcement learning

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:30:08.179999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-25T21:12:22.718409Z digest=sha256:0bdd7b477d838dff99630dd139991746c627518c12ebee056c9a41f5a32642cd

Observation 23e30609-28c3-47fd-99a5-e08e9e7095b9 · inbound

Shielded RL for Route-Charged Parity-Term Ordering in QEDA Phase Components cites this paper.

Shielded RL for Route-Charged Parity-Term Ordering in QEDA Phase Components Quantum circuit optimization with deep reinforcement learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-02T05:31:40.743070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:31:40.743070Z digest=sha256:bf6b8686857a1939fae5521d6d15e5b08ab0bb98e31c343f09c8b03256f1cafa