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CERN Document Server Pronađeno je 2,372 zapisa  1 - 10slijedećikraj  idi na zapis: Pretraživanje je potrajalo 0.82 sekundi 
1.
25th IEEE Real Time Conference - RT2026   25 - 29 May 2026  - La Biodola, Elba Island, It  .-
2026
Detaljnije
2.
Anomaly detection with AXOL1TL at the CMS Level-1 Trigger in 2024 and 2025 /CMS Collaboration
AXOL1TL (Anomaly eXtraction Online Level-1 Trigger aLgorithm) is a machine learning-based anomaly detection algorithm deployed at the CMS Level-1 Global Trigger. It is an event-level trigger that selects anomalous events in real time using an unsupervised, signal-agnostic approach, providing sensitivity to a wide variety of signals. [...]
CMS-DP-2025-061; CERN-CMS-DP-2025-061.- Geneva : CERN, 2025 - 20 p. Fulltext: PDF;
Detaljnije
3.
Low-latency electron $p_T$ regression with the CMS Phase-2 Level 1 trigger /CMS Collaboration
The CMS Level-1 Trigger (L1T) for the HL-LHC will use powerful FPGA processors connected by a high-bandwidth network of optical fibers. The new system will have access to online tracking, which enables the identification of calorimeter deposits originating from electrons. [...]
CMS-DP-2025-059; CERN-CMS-DP-2025-059.- Geneva : CERN, 2025 - 24 p. Fulltext: PDF;
Detaljnije
4.
Extending the Features of the CMS Phase-2 Level-1 Trigger Scouting /CMS Collaboration
Traditional data streams rely on a decision of the Level-1 trigger to accept only a fraction of the events for further processing and selection by the High Level Trigger, followed by an offline analysis of the selected events. Level-1 scouting introduces an alternative path, by analyzing events only based on the Level-1 trigger reconstruction without a preselection. [...]
CMS-DP-2025-058; CERN-CMS-DP-2025-058.- Geneva : CERN, 2025 - 36 p. Fulltext: PDF;
Detaljnije
5.
The ATLAS RPC Phase II upgrade for High Luminosity LHC era / Falsetti, G (U. Calabria, Arcavacata di Rende (main) ; INFN, Cosenza) /ATLAS Muon Collaboration
Resistive Plate Chamber detectors, play a crucial role in triggering events with muons in the ATLAS central region. In view of the High Luminosity LHC program, this system is facing a significant upgrade. [...]
2025 - 3 p. - Published in : Nucl. Instrum. Methods Phys. Res., A 1082 (2026) 170955
In : 17th Vienna Conference on Instrumentation (VCI2025), Vienna, Austria, 17 - 21 Feb 2025, pp.170955
Detaljnije
6.
Online Track Reconstruction with Graph Neural Networks on FPGAs for ATLAS / Neubauer, Mark (Univ. Illinois at Urbana Champaign (US)) /ATLAS Collaboration
The High-Luminosity Large Hadron Collider (HL-LHC) at CERN marks a new era for high-energy particle physics, demanding significant upgrades to the ATLAS Trigger and Data Acquisition (TDAQ) system. Central to these upgrades is the enhancement of online software tracking capabilities to meet the unprecedented data rates and complexity of HL-LHC operations. [...]
ATL-DAQ-SLIDE-2025-469.- Geneva : CERN, 2025 Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : The 32nd International Symposium on Lepton Photon Interactions at High Energies (Lepton Photon 2025), Madison, Wisconsin, Us, 25 - 29 Aug 2025
Detaljnije
7.
High Throughput FPGA Deployment of Distilled Deep Sets Networks for Jet Preselection in the High Level Trigger / Antel, Claire (CERN) ; Bezio, Lucas (Universite de Geneve (CH)) ; Berthet, Quentin (HEPIA - Haute école du paysage, d'ingénierie et d'architecture (CH)) ; Franchellucci, Stefano (Universite de Geneve (CH)) ; Sfyrla, Anna (Universite de Geneve (CH)) /ATLAS Collaboration
Deep Sets-based neural networks are well-suited to learning from unordered, variable-length inputs such as particle tracks associated with jets. Their permutation-invariant structure makes them attractive for high-energy physics (HEP) applications where input ordering is ambiguous and throughput is a critical constraint. [...]
ATL-DAQ-SLIDE-2025-467.- Geneva : CERN, 2025 - 1 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
Detaljnije
8.
GELATO: A Generic Event-Level Anomaly Detection Trigger for ATLAS / Jia, Kenny (SLAC National Accelerator Laboratory (US)) ; ATLAS Collaboration /ATLAS Collaboration
The absence of BSM physics discoveries at the LHC suggests new physics could lie outside current trigger schemes. By applying unsupervised ML–based anomaly detection, we gain a model-agnostic way of spotting anomalous signatures that deviate from the current trigger’s expectations. [...]
ATL-DAQ-SLIDE-2025-466.- Geneva : CERN, 2025 - 17 p. Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : Fast Machine Learning for Science Conference 2025, Zurich, Switzerland, Ch, 1 - 5 Sep 2025
Detaljnije
9.
Results on CUDA and HIP execution graphs and unified memory in CLUE /CMS Collaboration
This note outlines the impact of execution graphs and unified memory with CUDA and ROCm on CLUE..
CMS-DP-2025-055; CERN-CMS-DP-2025-055.- Geneva : CERN, 2025 - 100 p. Fulltext: PDF;
Detaljnije
10.
Validation of online GPU vs. CPU reconstruction in Pixel, ECAL, HCAL, and PF /CMS Collaboration
Since the beginning of Run 3, the CMS experiment has implemented a heterogeneous scheme for the High-Level Trigger (HLT) farm that integrates NVIDIA GPU accelerators for online event reconstruction. This note reports on the validation of GPU-based reconstruction against CPU for pixel, ECAL, and HCAL local reconstruction, as well as for pixel track and vertex reconstruction and the clustering stage of Particle Flow (PF) reconstruction. [...]
CMS-DP-2025-054; CERN-CMS-DP-2025-054.- Geneva : CERN, 2025 - 11 p. Fulltext: PDF;
Detaljnije

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