2025-09-01
11:27 |
詳細記錄
|
2025-09-01
11:27 |
Debiasing Ultrafast Anomaly Detection with Posterior Agreement
/CMS Collaboration
The Level-1 Trigger system of the CMS experiment at CERN makes the final decision on which LHC collision data are stored to disk for later analysis. One algorithm used with this scope is an anomaly detection model based on an autoencoder architecture. [...]
CMS-DP-2025-050; CERN-CMS-DP-2025-050.-
Geneva : CERN, 2025 - 40 p.
Fulltext: PDF;
|
詳細記錄
|
2025-09-01
11:27 |
詳細記錄
|
2025-09-01
11:27 |
詳細記錄
|
2025-09-01
11:27 |
Performance of boosted tau lepton identification with DeepTau Framework (Boosted DeepTau)
/CMS Collaboration
This note presents a dedicated identification algorithm targeting individual hadronic tau leptons ($\tau_\mathrm{h}$) within boosted ditau systems. Based on the DeepTau architecture used for resolved $\tau_\mathrm{h}$, the Boosted DeepTau algorithm achieves a factor of 2--4 improvement in the rejection of jets for individual $\tau_\mathrm{h}$ candidates with $p_\mathrm{T}$ $<$ 100 GeV, and an order of magnitude improvement at higher $p_\mathrm{T}$. [...]
CMS-DP-2025-047; CERN-CMS-DP-2025-047.-
Geneva : CERN, 2025 - 15 p.
Fulltext: PDF;
|
詳細記錄
|
2025-09-01
11:27 |
MEMFlow: Computing the Matrix Element Method with generative machine learning
/CMS Collaboration
The Matrix Element Method (MEM) is a well motivated multivariate technique to access the likelihood of an observed event given a hypothesis. It offers optimal statistical power for hypothesis testing in particle physics, but it is limited by the computation of the intensive multi-dimensional integrals required to model detector and theory effects.
We present a novel approach that addresses this challenge by employing Transformers and generative machine learning (ML) models. [...]
CMS-DP-2025-046; CERN-CMS-DP-2025-046.-
Geneva : CERN, 2025 - 29 p.
Fulltext: PDF;
|
詳細記錄
|
2025-07-28
13:21 |
An Energy Correlation Function Tagger for Gluon-Gluon Resonances
/CMS Collaboration
This note presents a tagging method for the discrimination of processes with two final state gluons from the dominant QCD background. The tagging model is a boosted decision tree that uses energy correlation functions as input features. [...]
CMS-DP-2025-045; CERN-CMS-DP-2025-045.-
Geneva : CERN, 2025 - 21 p.
Fulltext: PDF;
|
詳細記錄
|
2025-07-28
13:21 |
A First Look Into Jet Energy Scale With Early 2025 Data
/CMS Collaboration
We present the jet energy scale measurement with promptly reconstructed 13.6 TeV proton-proton collisions data collected by CMS in the first months of 2025..
CMS-DP-2025-044; CERN-CMS-DP-2025-044.-
Geneva : CERN, 2025 - 7 p.
Fulltext: PDF;
|
詳細記錄
|
2025-07-23
18:03 |
TROTA performance
/CMS Collaboration
Identifying boosted hadronic top quarks poses a significant challenge within the CMS physics program, particularly in Standard Model measurements and searches for new phenomena. There are many excellent tools available for identifying wide-angle jets with top quark flavor.
However, to enhance reconstruction and selection efficiencies for signal events including top quarks, an approach extending beyond large radius jets is necessary. [...]
CMS-DP-2025-043; CERN-CMS-DP-2025-043.-
Geneva : CERN, 2025 - 27 p.
Fulltext: PDF;
|
詳細記錄
|
2025-07-23
18:03 |
詳細記錄
|