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CMS Notes

ეძებე 900 ჩანაწერები:
ძებნის მინიშნებანი :: უბრალო ძებნა
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უკანასკნელი დამატებები:
2023-11-20
14:28
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-11-06
17:25
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-10-16
14:14
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-11
12:26
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-09-04
16:16
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-08-29
09:40
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;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-07-25
11:23
Production and validation of industrially produced large-sized GEM foils for the Phase-2 upgrade of the CMS muon spectrometer / Abbas, Syed Mohsin (IPM, Tehran) ; Abbrescia, Marcello (INFN, Bari ; Bari U.) ; Abdalla, Hassan Fathy (Cairo, Acad. Sci. Res. Tech.) ; Abdelalim, Ahmed Ali (Cairo, Acad. Sci. Res. Tech.) ; Abuzeid Hassan, Shimaa Abdelwahed (INFN, Pavia) ; Aebi, Devin Michael (Texas A-M) ; Agapitos, Antonis (Peking U.) ; Ahmad, Ashfaq (Quaid-i-Azam U.) ; Ahmed, Asar (Delhi U.) ; Ahmed, Waqar (Quaid-i-Azam U.) et al.
The upgrade of the CMS detector for the high luminosity LHC (HL-LHC) will include gas electron multiplier (GEM) detectors in the end-cap muon spectrometer. Due to the limited supply of large area GEM detectors, the Korean CMS (KCMS) collaboration had formed a consortium with Mecaro Co., Ltd. to serve as a supplier of GEM foils with area of approximately 0.6 m$^{2}$. The consortium has developed a double-mask etching technique for production of these large-sized GEM foils. This article describes the production, quality control, and quality assessment (QA/QC) procedures and the mass production status for the GEM foils. [...]
CMS-NOTE-2023-006; CERN-CMS-NOTE-2023-006.- Geneva : CERN, 2023 - 18 p. Fulltext: PDF;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-06-09
08:16
Improved Common $t\bar{t}$ Monte-Carlo Settings for ATLAS and CMS / The ATLAS ; CMS Collaborations /ATLAS and CMS Collaborations
The ATLAS and CMS Collaborations both use POWHEG+PYTHIA8 for their nominal $t\bar{t}$ Monte-Carlo simulations. Presented here is a second iteration of agreed-upon common settings for such a setup, in order to ease comparison and combination of ATLAS and CMS results. [...]
CMS-NOTE-2023-004; CERN-CMS-NOTE-2023-004.- Geneva : CERN, 2023 - 26 p. Fulltext: PDF;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-15
14:52
FlashSim prototype: an end-to-end fast simulation using Normalizing Flow / Vaselli, Francesco (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Rizzi, Andrea (INFN, Pisa ; Pisa U.) ; Cattafesta, Filippo (INFN, Pisa) ; Cicconofri, Gloria (INFN, Pisa) /CMS Collaboration
We present a prototype of Flash-sim, a fast simulation for CMS analysis level event content (NANOAOD) based on Machine Learning. The Normalizing Flow technique is used to directly simulate reconstructed physics object information from generator level objects, skipping the full simulation and reconstruction [...]
CMS-NOTE-2023-003; CERN-CMS-NOTE-2023-003.- Geneva : CERN, 2023 - 22 p. Fulltext: PDF;

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-02
11:39
Evaluation of HPK $n^+$-$p$ planar pixel sensors for the CMS Phase-2 upgrade / Tracker Group of the CMS Collaboration
To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10~years with an instantaneous peak luminosity of up to $7.5\times 10^{34}$~cm$^{-2}$s$^{-1}$ in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text{eq}} = 3.5\times 10^{16}$~cm$^{-2}$. [...]
arXiv:2212.04793; CMS-NOTE-2023-002.- Geneva : CERN, 2023-05-09 - 18 p. - Published in : Nucl. Instrum. Methods Phys. Res., A 1053 (2023) 168326 Fulltext: NOTE2023_002 - PDF; 2212.04793 - PDF; 826201a370cac8eb0cb4bd0a37aa14d9 - PDF; External link: Fermilab Library Server

დეტალური ჩანაწერი - მსგავსი ჩანაწერები