◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Leonardo Giannini

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

fields
  • hep-ex3
same name
  • Leonardo Giannini — 1 paper
  • Leonardo Giannini — 1 paper
  • Leonardo Giannini — 1 paper
  • Leonardo Giannini — 1 paper
  • Leonardo Giannini — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSearch for long-lived particles decaying to final states with a pair of muons in proton-proton collisions at s​ = 13.6 TeV

8 citations · 11 across the 3 of their papers we have counts for

collaborators

3 papers

hep-ex2025★ 1 cited

Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC

CMS Collaboration

We propose a neural network training method capable of accounting for the effects of systematic variations of the data model in the training process and describe its extension towa…

hep-ex2024★ 2 cited

Observation of the J/ψ → μ+μ−μ+μ− decay in proton-proton collisions at s​ = 13 TeV

CMS Collaboration

The J/ψ → μ+μ−μ+μ− decay has been observed with a statistical significance in excess of five standard deviations. The analysis is based on an event sample of proton-pro…

hep-ex2024★ 8 cited

Search for long-lived particles decaying to final states with a pair of muons in proton-proton collisions at s​ = 13.6 TeV

CMS Collaboration

An inclusive search for long-lived exotic particles (LLPs) decaying to final states with a pair of muons is presented. The search uses data corresponding to an integrated luminosit…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.