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Paper Citation Record · LEDGER

Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.09474.

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

pith.paper-citation-record.v1
2106.09474 v2

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 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:11:56.554742Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T19:21:47.045113Z

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 061b2b63-69af-4d16-8ecf-54ad17ad3e0b · inbound

Explainable AI-assisted Optimization for Feynman Integral Reduction cites this paper.

Explainable AI-assisted Optimization for Feynman Integral Reduction Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T21:11:56.554742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation efe651b8-0c6c-4a73-a98f-ed82a92d6644 · inbound

Amplitude Uncertainties Everywhere All at Once cites this paper.

Amplitude Uncertainties Everywhere All at Once Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T19:21:47.048192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-18T19:21:24.292766Z digest=sha256:fa53dc3310525ecca833bafcc139658af938ba60c4be9490cd313e4a219a534d

Observation 6850a3f4-cf61-4ca5-adb9-99c4423287a5 · inbound

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD cites this paper.

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T22:58:02.149149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:58:02.149149Z digest=sha256:e5483423e65973e21c16e94d2afa5e3efed59a0e2ce16bb9a755fadd8178bdf2

Observation 983741ff-6e86-4405-9356-fa0c62188ffe · inbound

A Novel Implementation of the Matrix Element Method at Next-to-Leading Order for the Measurement of the Higgs Self-Coupling ${\lambda}_{3H}$ cites this paper.

A Novel Implementation of the Matrix Element Method at Next-to-Leading Order for the Measurement of the Higgs Self-Coupling ${\lambda}_{3H}$ Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-03T05:27:31.468152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:27:31.468152Z digest=sha256:6486ef131bcd6bc89a7896bcac45b31e7cf8cc8182c07df95f99de4cffffabc8

Observation a2e747f5-1823-490f-a7ea-9f4364f683d7 · inbound

MadSpace -- Event Generation for the Era of GPUs and ML cites this paper.

MadSpace -- Event Generation for the Era of GPUs and ML Optimising simulations for diphoton production at hadron colliders using amplitude neural networks

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-03T03:52:01.281359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:52:01.281359Z digest=sha256:6f16f0079198e1815306efe0e8f50acc56661f79864ecbb9b5d40004267e06e3