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Paper Citation Record · LEDGER

Detecting Quantum and Classical Phase Transitions via Unsupervised Machine Learning of the Fisher Information Metric

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.03418.

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

pith.paper-citation-record.v1
2408.03418 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:03:54.409528Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

0
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1f7f9a9c-7e52-4b19-865f-45ec90310691 · inbound

Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise cites this paper.

Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise Detecting Quantum and Classical Phase Transitions via Unsupervised Machine Learning of the Fisher Information Metric

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-11T15:03:54.409528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:03:54.409528Z digest=sha256:38da1db3c36c924d25b5ed7c0a43d58e1a54a4f993b5561b61647b9c9ca9215a

Observation 7c4cac3e-73e2-404d-8bdb-74e952fb1120 · inbound

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors cites this paper.

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors Detecting Quantum and Classical Phase Transitions via Unsupervised Machine Learning of the Fisher Information Metric

Reference 136

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:59:20.429393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T14:59:15.785416Z digest=sha256:d80491df50415171ba212e0027c213f5d92d8c7503116d0f888702effd4f21e9