Pith. sign in

REVIEW 3 cited by

Jets and Jet Substructure at Future Colliders

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2203.07462 v1 pith:B3CXAMRS submitted 2022-03-14 hep-ph hep-ex

classification hep-phhep-ex
keywords substructurefuturecollidersphysicsprogramdesignenergyfrontier
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Even though jet substructure was not an original design consideration for the Large Hadron Collider (LHC) experiments, it has emerged as an essential tool for the current physics program. We examine the role of jet substructure on the motivation for and design of future energy frontier colliders. In particular, we discuss the need for a vibrant theory and experimental research and development program to extend jet substructure physics into the new regimes probed by future colliders. Jet substructure has organically evolved with a close connection between theorists and experimentalists and has catalyzed exciting innovations in both communities. We expect such developments will play an important role in the future energy frontier physics program.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders

    hep-ph 2026-07 conditional novelty 7.0 of 10

    Simplex demixing recovers T mutually irreducible jet-flavor topics from M mixed samples via the (T−1)-simplex geometry of a multi-category classifier, demonstrated on Pythia dijets.

  2. The Scaffold Effect: How Prompt Framing Drives Apparent Multimodal Gains in Clinical VLM Evaluation

    cs.AI 2026-03 unverdicted novelty 6.0 of 10

    Merely mentioning MRI availability in the prompt drives 70-80% of apparent multimodal F1 gains in clinical VLMs, even when no imaging is present.

  3. A Step Toward Interpretability: Smearing the Likelihood

    hep-ph 2025-01 conditional novelty 6.0 of 10

    Smearing the likelihood over an energy metric reveals the physical scales used by a jet classifier, and the needed smearing radius follows a power-law scaling with dataset size.

Pith tools