Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:11:39.276983Z
Paper Citation Record · LEDGER
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems
As of 15 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 2 inbound Pith citation observations for arXiv:2411.17442.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T05:02:01.210295Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T21:57:10.469827Z
Reference resolution
23 of 23 outbound references displayed
- verified exact0
- verified fuzzy14
- unresolved8
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b4b57da9-84a6-453c-a091-ac8f87dee708 · outbound
This paper cites This amounts to computing the single-clause polynomial, i.e.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems This amounts to computing the single-clause polynomial, i.e
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.459947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 588ad58f-d41d-4178-ae79-3f32779b2062 · outbound
This paper cites This results from pairing together original configuration basis numbers adding up to a reeduced configuration basis numbers, i.e.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems This results from pairing together original configuration basis numbers adding up to a reeduced configuration basis numbers, i.e
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.505153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 21b34d39-32de-419e-8803-a1cb25d5f222 · outbound
This paper cites Let q ≥ 1 an integer andq ∈ P(q) a weight-q configuration basis number.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Let q ≥ 1 an integer andq ∈ P(q) a weight-q configuration basis number
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.496887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e058d44c-cbed-43b5-970b-ee42fd3fc20f · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.488450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 03175645-e596-4f89-9924-4503de80ccd8 · outbound
This paper cites Hamming weight.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Hamming weight
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.478948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 650251af-359c-422c-957e-512632e84159 · outbound
This paper cites Near-term quantum computing for solving hard industrial optimisation problems.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Near-term quantum computing for solving hard industrial optimisation problems
Reference 6
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-12T12:11:39.470000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 92acf513-04e3-4fb5-b94f-bd09774c5d34 · outbound
This paper cites Boulebnane and A.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Boulebnane and A
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.377473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 68ca7e37-d642-40a6-a580-eef881a25886 · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.449529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1196c1f2-9dbb-49ed-a118-3d3adb78ac15 · outbound
This paper cites This problem corresponds to the functionT : {0, 1}k → {0, 1} where T (x) = 1 ⇔ 0 < |x| < k, and |x| denotes the Hamming weight.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems This problem corresponds to the functionT : {0, 1}k → {0, 1} where T (x) = 1 ⇔ 0 < |x| < k, and |x| denotes the Hamming weight
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.440738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 34dd25c0-4a82-4569-af72-f52f4a47ca76 · outbound
This paper cites Farhi, J.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Farhi, J
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.430959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 855fb040-ed60-4f6d-9a83-ef7ca25cd39e · outbound
This paper cites (49) Similar to notationP(q) introduced in definition 5 for configuration basis numbers, we denote by P ′(q) (50) the set of reduced configuration basis numbers of weightq.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems (49) Similar to notationP(q) introduced in definition 5 for configuration basis numbers, we denote by P ′(q) (50) the set of reduced configuration basis numbers of weightq
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.514459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation aa2d1f6d-9d95-409f-be2e-3f7a7cd14cae · outbound
This paper cites Marwaha and S.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Marwaha and S
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.421909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f0cb036c-4a97-4465-a69d-3d609af37410 · outbound
This paper cites Farhi, J.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Farhi, J
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.412952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation eba663a4-a7d8-4678-b44c-5a03db2db37e · outbound
This paper cites Basso, D.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Basso, D
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.404177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0cd9b8fc-d8d2-49f1-8665-56b9df789e10 · outbound
This paper cites Basso, E.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Basso, E
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.395383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bfe2f1e4-62aa-4b1a-b536-5cc9cf02920e · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.386743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 70e44097-52f2-4ec2-8cd1-1f7dcf90d0c6 · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.368177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dde2a3e9-7aca-41ee-ab6a-ff4de4015860 · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.359223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 218537bd-95c2-46c7-a6ad-c47bc22fe374 · outbound
This paper cites Boulebnane and A.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Boulebnane and A
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.349405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1d0375b8-4fdb-4aad-9e09-49d1dcba0755 · outbound
This paper cites Claes and W.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Claes and W
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:11:39.339196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 699ccfd4-6db3-4856-ae36-a37182600478 · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.328270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9d381746-db42-4bb8-bece-e6cfae8a50b4 · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 22
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.317119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 72259489-0659-42f0-a34d-956eefeae54a · outbound
This paper cites an unresolved cited work.
Applying the quantum approximate optimization algorithm to general constraint satisfaction problems Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T12:11:39.306331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
Observation 29faec16-421a-418c-b39e-4e8a477df5d1 · inbound
Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm cites this paper.
Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm Applying the quantum approximate optimization algorithm to general constraint satisfaction problems
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T21:57:10.473276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b6f16748-68bc-4d9f-8d47-145822e4e301 · inbound
Quantum-informed surrogate sampling for combinatorial optimization cites this paper.
Quantum-informed surrogate sampling for combinatorial optimization Applying the quantum approximate optimization algorithm to general constraint satisfaction problems
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T05:02:01.210295Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.