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Paper Citation Record · LEDGER

Adding machine learning within Hamiltonians: Renormalization group transformations, symmetry breaking and restoration

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.00054.

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

pith.paper-citation-record.v1
2010.00054 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:58:33.317149Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:10:58.379962Z

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 741c05bc-359e-46d9-a546-be10b0c355d9 · inbound

Symmetry-preserving neural networks in lattice field theories cites this paper.

Symmetry-preserving neural networks in lattice field theories Adding machine learning within Hamiltonians: Renormalization group transformations, symmetry breaking and restoration

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T00:58:33.317149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:33.317149Z digest=sha256:edfdb5bcd3932be31a8c4e846a44eae1c06e4995b528278d202e0b0a78fd3304

Observation a0a92c22-ad30-43c4-a14f-6e19c7c6030b · inbound

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition cites this paper.

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition Adding machine learning within Hamiltonians: Renormalization group transformations, symmetry breaking and restoration

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:10:58.386150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T01:54:10.924145Z digest=sha256:f9ef18363c5acab39b0467cfd91b801e360c9f662db90e5bf5567499348e924f