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Paper Citation Record · LEDGER

Efficient learning of Sparse Pauli Lindblad models for fully connected qubit topology

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.11639.

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

pith.paper-citation-record.v1
2311.11639 v1

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:51:46.832286Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T21:37:08.120217Z

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 de196550-74b1-4e8a-9dbc-84a5e4bfcafc · inbound

Sparse Non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations cites this paper.

Sparse Non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations Efficient learning of Sparse Pauli Lindblad models for fully connected qubit topology

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-11T10:51:46.832286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:51:46.832286Z digest=sha256:c99f77e366d1166f9dd5c061c66e9f3552ec6920097eb1d39274af494006a2e6

Observation bf98fe3a-108f-4182-ad00-d0af04418fc3 · inbound

Physics-inspired Machine Learning for Quantum Error Mitigation cites this paper.

Physics-inspired Machine Learning for Quantum Error Mitigation Efficient learning of Sparse Pauli Lindblad models for fully connected qubit topology

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:37:08.126514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T21:37:08.043405Z digest=sha256:92eef889a5ebbac8df9d407e41e23b401e6350cd5e3d0bb49d86f7e8851f0b9f