Paper Citation Record · LEDGER

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1709.03489.

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

pith.paper-citation-record.v1
1709.03489 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:36:57.180221Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1a287a72-5a15-4166-8aa7-b10c79395027 · inbound

Learning to learn with quantum neural networks via classical neural networks cites this paper.

Learning to learn with quantum neural networks via classical neural networks From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:00:03.171637Z

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 e16612bb-bfaa-4681-82af-e3ad9b72addf · inbound

Towards quantum simulation of lower-dimensional supersymmetric lattice models cites this paper.

Towards quantum simulation of lower-dimensional supersymmetric lattice models From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T14:36:57.180221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c671ce-3720-440c-bb88-dc21a1de2afb · inbound

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms cites this paper.

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-18T15:36:34.716535Z

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 0e0261d5-e288-42f1-a924-b909e2cc0d2e · inbound

Constrained Counterdiabatic Quantum Approximate Optimization Algorithm for Portfolio Optimization cites this paper.

Constrained Counterdiabatic Quantum Approximate Optimization Algorithm for Portfolio Optimization From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T01:45:51.020740Z

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 5fc76f6a-e9d5-4cbc-9e18-ada3505a56c4 · inbound

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework cites this paper.

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 130

Resolution: metadata mismatch; local_arxiv, observed 2026-06-28T16:52:23.756290Z

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 5a54d537-19a4-4d3b-8cb2-dccd1c7fff5c · inbound

Simulating quantum circuits with a neural statebank cites this paper.

Simulating quantum circuits with a neural statebank From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-07-02T23:07:27.399485Z

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 500bee40-1655-4cef-b6e6-23c6d2fc3048 · inbound

Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm cites this paper.

Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

Reference 53

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T03:53:04.362569Z

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.