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CMS Notes

Darreres entrades:
Beam Test Performance Studies of CMS Phase-2 Outer Tracker Module Prototypes / The Tracker Group of the CMS Collaboration /CMS Collaboration
A new tracking detector will be installed as part of the Phase-2 upgrade of the CMS detector for the high-luminosity LHC era. This tracking detector includes the Inner Tracker, equipped with silicon pixel sensor modules, and the Outer Tracker, consisting of modules with two parallel stacked silicon sensors. [...]
CMS-NOTE-2024-002; CERN-CMS-NOTE-2024-002.- Geneva : CERN, 2021 - 41 p. Fulltext: PDF;

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Simultaneous determination of several differential observables with statistical correlations / The CMS Collaboration /CMS Collaboration
In the context of the determination of standard model parameters from CMS data, we explain and illustrate the simultaneous unfolding of several observables, such as jet cross sections, in a single fit based on the same data set, and the use of Monte Carlo integration to apply operations on unfolded observables, such as forming cross section ratios..
CMS-NOTE-2024-001; CERN-CMS-NOTE-2024-001.- Geneva : CERN, 2024 - 13 p.

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Simulation of on- and off-shell $\rm t\bar{t}$ production with the Monte Carlo generator b\_bbar\_4l at CMS / The CMS Collaboration /CMS Collaboration
This note presents performance studies of the b\_bbar\_4l package of the POWHEG BOX RES Monte Carlo generator used to model top quark production for the CMS experiment at the LHC. The b\_bbar\_4l package includes next-to-leading order treatment of the interference between top quark pair production, the associated production of a single top quark and a W boson, as well as non-resonant production of two charged leptons, two neutrinos, and two b quarks. [...]
CMS-NOTE-2023-015; CERN-CMS-NOTE-2023-015.- Geneva : CERN, 2023 - 12 p. Fulltext: PDF;

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Towards Real-Time Machine Learning Based Signal/Background Selection in the CMS Detector Using Quantized Neural Networks and Input Data Reduction / Burazin Misura, Arijana (Split Tech. U.) ; Music, Josip (Split Tech. U.) ; Prvan, Marina (Split Tech. U.) ; Lelas, Damir (Split Tech. U.)
To boost its discovery potential, the Large Hadron Collider (LHC) is being prepared for an extensive upgrade. The new phase, High Luminosity LHC (HL-LHC), will operate at luminosity (number proportional to the rate of collisions) increased by a factor of five. Such an increase in luminosity consequently will result in enormous amounts of generated data, the vast majority of which is uninteresting data or pile up (PU). [...]
CMS-NOTE-2023-014; CERN-CMS-NOTE-2023-014.- Geneva : CERN, 2023 - 25 p. Fulltext: PDF;

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Machine learning techniques for model-independent searches in dijet final states / Harris, Philip (MIT) ; Mccormack, William Patrick (MIT) ; Park, Sang Eon (MIT) ; Quadfasel, Tobias (Hamburg U.) ; Sommerhalder, Manuel (Hamburg U.) ; Moureaux, Louis Jean (Hamburg U.) ; Kasieczka, Gregor (Hamburg U.) ; Amram, Oz (Fermilab) ; Maksimovic, Petar (Johns Hopkins U.) ; Maier, Benedikt (KIT, Karlsruhe, EKP) et al.
We present the performance of Machine Learning--based anomaly detection techniques for extracting potential new physics phenomena in a model-agnostic way with the CMS Experiment at the Large Hadron Collider. We introduce five distinct outlier detection or density estimation techniques, namely CWoLa, Tag N' Train, CATHODE, QUAK, and QR-VAE, tailored for the identification of anomalous jets originating from the decay of unknown heavy particles. [...]
CMS-NOTE-2023-013; CERN-CMS-NOTE-2023-013.- Geneva : CERN, 2023 - 11 p. Fulltext: PDF;

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Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier / Groenroos, Sonja (Helsinki U.) ; Pierini, Maurizio (CERN) ; Chernyavskaya, Nadezda (CERN)
More than a thousand 8'' silicon sensors will be visually inspected to look for anomalies on their surface during the quality control preceding assembly into the High-Granularity Calorimeter for the CMS experiment at CERN. A deep learning- based algorithm that pre-selects potentially anomalous images of the sensor surface in real time has been developed to automate the visual inspection. [...]
CMS-NOTE-2023-012; CERN-CMS-NOTE-2023-012.- Geneva : CERN, 2023 - 17 p. Fulltext: PDF;

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Comparisons of VBF-enriched V+jets Monte Carlo predictions with ATLAS data via the ATLAS EW Zjj Rivet routine / CMS Collaboration /CMS Collaboration
The predicted distributions for various VBF observables from CMS Monte Carlo samples, for both strong- and electroweak-induced V+jets processes, are compared with ATLAS unfolded data in a VBF Z-enriched region. This study applies an EW Zjj Rivet routine created by ATLAS to CMS Monte Carlo samples. [...]
CMS-NOTE-2023-011; CERN-CMS-NOTE-2023-011.- Geneva : CERN, 2022 - 11 p. Fulltext: PDF;

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Autoencoder-based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter / The CMS ECAL Collaboration
The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online Data Quality Monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. [...]
CMS-NOTE-2023-009; CERN-CMS-NOTE-2023-009.- Geneva : CERN, 2023 - 30 p. Fulltext: PDF;

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Reconstructing the invariant mass of ultra-heavy resonances decaying to vector-like quark pairs in fully-hadronic final states / CMS Collaboration /CMS Collaboration
A new technique is introduced that uses event geometry, and multiple rounds of jet boosting and reclustering to reconstruct the daughter masses of fully-hadronic vector-like quark (VLQ) pair decays. Plots describing the performance of this technique on a diquark to VLQ pair model are shown..
CMS-NOTE-2023-008; CERN-CMS-NOTE-2023-008.- Geneva : CERN, 2023 - 8 p. Fulltext: PDF;

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CMS detector performance plots of heavy flavor decays using early Run 3 data / CMS Collaboration /CMS Collaboration
The document presents a series of performance plots for heavy flavor decays using an early Run 3 data sample collected by the CMS experiment in 2023. It highlights the impact of the new trigger strategy and detector upgrades on various observables. [...]
CMS-NOTE-2023-007; CERN-CMS-NOTE-2023-007.- Geneva : CERN, 2023 - 14 p. Fulltext: PDF;

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