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Paper Citation Record · LEDGER

Deep learning assisted jet tomography for the study of Mach cones in QGP

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2206.02393.

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

pith.paper-citation-record.v1
2206.02393 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:51:39.694805Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T22:27:49.412641Z

Reference resolution

0 of 0 outbound references displayed

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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 d7f8a404-e836-4417-ae03-37d8759980ad · inbound

Machine Learning Insights into Quark-Antiquark Interactions: Probing Field Distributions and String Tension in QCD cites this paper.

Machine Learning Insights into Quark-Antiquark Interactions: Probing Field Distributions and String Tension in QCD Deep learning assisted jet tomography for the study of Mach cones in QGP

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T14:51:39.694805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:51:39.694805Z digest=sha256:3b3c88d237eb57a93a0dde537c078eb051bf7133004b39b3f7a120fa29c7fa84

Observation 5607133e-0f3c-40eb-9096-32cef764991c · inbound

Rapidity asymmetry of jet-hadron correlation as a robust signal of diffusion wake induced by di-jets in high-energy heavy-ion collisions cites this paper.

Rapidity asymmetry of jet-hadron correlation as a robust signal of diffusion wake induced by di-jets in high-energy heavy-ion collisions Deep learning assisted jet tomography for the study of Mach cones in QGP

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T21:57:27.355957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:57:27.355957Z digest=sha256:59a125641c20b2a0b10aecacab7917871703d869f9a298c535d07c89b611ca65

Observation 2030aaec-a5be-4985-b9df-704e6372c0e4 · inbound

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD cites this paper.

Probing Proton Structure via Physics-Guided Neural Networks in Holographic QCD Deep learning assisted jet tomography for the study of Mach cones in QGP

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-13T18:48:08.085719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T18:44:28.360549Z digest=sha256:7e4a8fe209314901b21f2f0d2eaeb7bb81ffae80bbde39beb65e7e22814fc3d7

Observation 30a8df94-24ad-45bf-811a-fe9d522aba09 · inbound

Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning cites this paper.

Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning Deep learning assisted jet tomography for the study of Mach cones in QGP

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:56:00.662662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T17:23:12.933048Z digest=sha256:6a52adf7dc57d3d348bf75be04fcd54477a4383cc0bb5a1a816b9792a97bdcd8

Observation 2bd2f62f-5d9f-43d4-928b-a45533b40ed2 · inbound

Study of jet-induced hydro response in high-energy heavy-ion collisions with a flow-matching generative model cites this paper.

Study of jet-induced hydro response in high-energy heavy-ion collisions with a flow-matching generative model Deep learning assisted jet tomography for the study of Mach cones in QGP

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-19T22:27:49.414490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T22:24:51.990184Z digest=sha256:6870ebd3edb0b8b7976bf0eca26ae277fd41ccd947f3dc7ef648534dfb2971ce