Paper Citation Record · LEDGER

Provably Efficient Learning of Phases of Matter via Dissipative Evolutions

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.07506.

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

pith.paper-citation-record.v1
2311.07506 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:50:39.494303Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T05:24:31.911414Z

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 7496e155-951e-46c5-9634-72bc405b3c46 · inbound

Quantum circuit complexity and unsupervised machine learning of topological order cites this paper.

Quantum circuit complexity and unsupervised machine learning of topological order Provably Efficient Learning of Phases of Matter via Dissipative Evolutions

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:31:55.785560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dc2e3a8e-cc13-4929-b821-9e916f3458ed · inbound

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

Artificial intelligence for representing and characterizing quantum systems Provably Efficient Learning of Phases of Matter via Dissipative Evolutions

Reference 193

Resolution: unresolved; no resolver link, observed 2026-08-05T05:50:39.494303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acf84d9e-9aba-49fe-be3f-419290bc1394 · inbound

Analogue quantum simulation with polylogarithmic interaction strengths by extrapolating within phases of matter cites this paper.

Analogue quantum simulation with polylogarithmic interaction strengths by extrapolating within phases of matter Provably Efficient Learning of Phases of Matter via Dissipative Evolutions

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:47:04.161214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2e6ad22e-a53b-4620-92be-ba25dadfc997 · inbound

Provable learning separation for predicting time-evolution of quantum many-body systems cites this paper.

Provable learning separation for predicting time-evolution of quantum many-body systems Provably Efficient Learning of Phases of Matter via Dissipative Evolutions

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-07-08T05:24:31.912960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.