Related papers: Testing a Neural Network for Anomaly Detection in …
The structure of the CMS inner tracking system has been studied using nuclear interactions of hadrons striking its material. Data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded in 2015 at the LHC are used to…
The first level trigger of the CMS experiment is comprised of custom electronics that process data from the electromagnetic and hadron calorimeters and three technologies of muon detectors in order to select the most interesting events from…
Anomaly detection through employing machine learning techniques has emerged as a novel powerful tool in the search for new physics beyond the Standard Model. Historically similar to the development of jet observables, theoretical…
Experimental particle physics demands a sophisticated trigger and acquisition system capable to efficiently retain the collisions of interest for further investigation. Heterogeneous computing with the employment of FPGA cards may emerge as…
At the Large Hadron Collider at CERN the proton bunches cross at a rate of 40MHz. At the Compact Muon Solenoid experiment the original collision rate is reduced by a factor of O (1000) using a Level-1 hardware trigger. A subsequent factor…
This study explores the potential of unsupervised anomaly detection for identifying physics beyond the Standard Model that may appear at proton collisions at the Large Hadron Collider. We introduce a novel quantum autoencoder circuit ansatz…
After nearly two decades of design, construction and commissioning, the CMS detector was operated with colliding LHC proton beams for the first time in November 2009. Collision data were recorded at centre-of-mass energies of 0.9 and 2.36…
The trigger systems of the LHC detectors play a crucial role in determining the physics capabilities of the experiments. A reduction of several orders of magnitude of the event rate is needed to reach values compatible with the detector…
The Pixel Detector is the innermost detector of the tracking system of the Compact Muon Solenoid (CMS) experiment at CERN Large Hadron Collider (LHC). It precisely determines the interaction point (primary vertex) of the events and the…
The implementation of convolutional neural networks in programmable logic, for applications in fast online event selection at hadron colliders is studied. In particular, an approach based on full event images for classification is studied,…
Real-time particle transverse momentum ($p_T$) estimation in high-energy physics demands algorithms that are both efficient and accurate under strict hardware constraints. Static machine learning models degrade under high pileup and lack…
The muon trigger system of the CMS experiment uses a combination of hardware and software to identify events containing a muon. During Run 2 (covering 2015-2018) the LHC achieved instantaneous luminosities as high as 2 $\times$…
The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show…
The CMS experiment, located at the Large Hadron Collider (LHC) in CERN, has a redundant muon system composed by three different gaseous detector technologies: Cathode Strip Chambers (in the forward regions), Drift Tubes (in the central…
At the ATLAS and CMS experiments at CERN's Large Hadron Collider, the rate of proton-proton collisions far exceeds the rate at which data can be recorded. A real-time event selection process, or "trigger", is needed to ensure that the data…
The Compact Muon Solenoid (CMS) calorimeter regional trigger system is designed to detect signatures of isolated and non-isolated electrons/photons, jets, ?-leptons, and missing and total transverse energy using a deadtimeless pipelined…
Selected results from searches for new physics with unconventional signatures using the ATLAS and CMS detectors are presented. Such signatures include emerging jets, heavy charged particles, displaced or delayed objects, and disappearing…
Unsupervised anomaly-based intrusion detection requires models that can generalize to attack patterns not observed during training. This work presents the first large-scale evaluation of hybrid quantum-classical (HQC) autoencoders for this…
The real-time identification and selection of b-jets play a crucial role in the CMS experiment, particularly in searches involving heavy-flavor jets. The High-Level Trigger (HLT) is designed to efficiently select events of interest while…
Due to the huge interaction rates and the tough experimental environment of pp collisions at a centre-of-mass energy sqrt(s)=14TeV and luminosities of up to 10^34 cm^-2 s^-1, one of the experimental challenges at the LHC is the triggering…