Paper Citation Record · LEDGER

Potential and limitations of random Fourier features for dequantizing quantum machine learning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2309.11647.

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

pith.paper-citation-record.v1
2309.11647 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:28:01.908946Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T05:37:36.889174Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 20e76aa7-5260-4cc1-9c89-60bc3b437ec3 · inbound

Opportunities and limitations of explaining quantum machine learning cites this paper.

Opportunities and limitations of explaining quantum machine learning Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T12:02:09.020874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb12f06a-f2ae-4462-8f8e-7f80d1eb49ef · inbound

IQPopt: Fast optimization of instantaneous quantum polynomial circuits in JAX cites this paper.

IQPopt: Fast optimization of instantaneous quantum polynomial circuits in JAX Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:37:36.892414Z

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.

Observation 37f36a40-3ac3-4174-8049-73364023fa2b · inbound

Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models cites this paper.

Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 109

Resolution: unresolved; no resolver link, observed 2026-08-07T19:24:33.005166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7729aa6-1a68-4502-9fb0-7604dde0be87 · inbound

Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models cites this paper.

Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 44

Resolution: malformed identifier; no resolver link, observed 2026-08-07T04:53:38.907962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e90cfba7-1b0c-4ae8-b8c8-05455f9544fb · inbound

Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction cites this paper.

Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T19:28:01.908946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5a591f6-11e1-416c-b026-83320e3d7973 · inbound

The Fourier Wall: Why Public Tabular Datasets Refuse Quantum Advantage, and a Certified Recipe for Where It Lives cites this paper.

The Fourier Wall: Why Public Tabular Datasets Refuse Quantum Advantage, and a Certified Recipe for Where It Lives Potential and limitations of random Fourier features for dequantizing quantum machine learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T22:20:46.653485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.