Particle production from secondary proton-proton collisions, commonly referred to as pile-up, impair the sensitivity of both new physics searches and precision measurements at large hadron collider (LHC) experiments. We propose a novel algorithm,
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Abstract Puma , for modeling pile-up with the help of deep neural networks based on sparse transformers. These attention mechanisms were developed for natural language processing but have become popular in other applications. In a realistic detector simulation, our method outperforms classical benchmark algorithms for pile-up mitigation in key observables. It provides a perspective for mitigating the effects of pile-up in the high luminosity era of the LHC, where up to 200 proton-proton collisions are expected to occur simultaneously. -
Free, publicly-accessible full text available December 1, 2024
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Free, publicly-accessible full text available November 1, 2024
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Free, publicly-accessible full text available November 1, 2024
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Abstract A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.
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Free, publicly-accessible full text available November 1, 2024
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Free, publicly-accessible full text available November 1, 2024
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Abstract A search for decays to invisible particles of Higgs bosons produced in association with a top-antitop quark pair or a vector boson, which both decay to a fully hadronic final state, has been performed using proton-proton collision data collected at
by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138$${\sqrt{s}=13\,\text {Te}\hspace{-.08em}\text {V}}$$ . The 95% confidence level upper limit set on the branching fraction of the 125$$\,\text {fb}^{-1}$$ Higgs boson to invisible particles,$$\,\text {Ge}\hspace{-.08em}\text {V}$$ , is 0.54 (0.39 expected), assuming standard model production cross sections. The results of this analysis are combined with previous$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$ searches carried out at$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$ , 8, and 13$${\sqrt{s}=7}$$ in complementary production modes. The combined upper limit at 95% confidence level on$$\,\text {Te}\hspace{-.08em}\text {V}$$ is 0.15 (0.08 expected).$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$ Free, publicly-accessible full text available October 1, 2024 -
Free, publicly-accessible full text available October 1, 2024
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Free, publicly-accessible full text available October 1, 2024