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Deep learning techniques have the power to identify the degree of modification of high energy jets traversing deconfined QCD matter on a jet-by-jet basis. Such knowledge allows us to study jets based on their initial, rather than final…

High Energy Physics - Phenomenology · Physics 2022-04-04 Yi-Lun Du , Daniel Pablos , Konrad Tywoniuk

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…

High Energy Physics - Experiment · Physics 2025-09-10 Noah Clarke Hall , Nikolaos Konstantinidis

Results are presented from a search for supersymmetry in events with a single electron or muon and hadronic jets. The data correspond to a sample of proton-proton collisions at $\sqrt{s} = $ 13 TeV with an integrated luminosity of 35.9…

High Energy Physics - Experiment · Physics 2018-03-23 CMS Collaboration

The pseudorapidity ($\eta$) distributions of charged hadrons are measured using data collected at the highest ever nucleon-nucleon center-of-mass energy of $\sqrt{s_\mathrm{NN}}$ = 5.36 TeV for collisions of lead-lead ions. The data were…

High Energy Physics - Experiment · Physics 2025-02-11 CMS Collaboration

Hadron production at high-$p_T$ displays a strong suppression pattern in a wide rapidity region in heavy ion collisions at RHIC energies. This finding indicates the presence of strong final state effects for both transversally and…

High Energy Physics - Phenomenology · Physics 2011-09-13 G. G. Barnaföldi , P. Lévai , G. Papp , G. Fai

There seems to be a general consensus now that a first glimpse of a QGP-like effect has become visible in the beautiful NA50 data on J/\psi production and the `anomalous supression' phenomenon. On the other hand, it is still widely believed…

Nuclear Theory · Physics 2009-10-31 Klaus Geiger

Predictions are made for the jet substructure of one-jet events produced in electron-proton neutral current deep inelastic scattering at the future Electron-Ion Collider for exchanged four-momentum squared, $Q^2 > 125$ GeV$^2$. Data are…

High Energy Physics - Phenomenology · Physics 2023-06-14 Siddharth Jain , R. Aggarwal , M. Kaur

The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are $n$ heterogeneous sensors and a fusion center. The sensors are clustered into $K$ groups, and different groups follow different…

Signal Processing · Electrical Eng. & Systems 2022-03-23 Zhongchang Sun , Shaofeng Zou , Ruizhi Zhang , Qunwei Li

A data sample of events from proton-proton collisions with two isolated same-sign leptons, missing transverse momentum, and jets is studied in a search for signatures of new physics phenomena by the CMS Collaboration at the LHC. The data…

High Energy Physics - Experiment · Physics 2017-09-07 CMS Collaboration

Results are reported from a search for new physics processes in events containing a single isolated high-transverse-momentum lepton (electron or muon), energetic jets, and large missing transverse momentum. The analysis is based on a 4.98…

High Energy Physics - Experiment · Physics 2013-05-14 The CMS Collaboration

I discuss a number of novel phenomenological features of QCD in high transverse momentum reactions. The presence of direct higher-twist processes, where a proton is produced directly in the hard subprocess, can explain the "baryon anomaly"…

High Energy Physics - Phenomenology · Physics 2010-12-17 Stanley J. Brodsky

Complex devices are connected daily and eagerly generate vast streams of multidimensional state measurements. These devices often operate in distinct modes based on external conditions (day/night, occupied/vacant, etc.), and to prevent…

Signal Processing · Electrical Eng. & Systems 2020-07-21 John Sipple

Jet flavor tagging plays an important role in precise Standard Model measurement enabling the extraction of mass dependence in jet-quark interaction and quark-gluon plasma (QGP) interactions. They also enable inferring the nature of…

High Energy Physics - Phenomenology · Physics 2026-03-24 Diego F. Vasquez Plaza , Vidya Manian

Ultrarelativistic heavy ion collisions recreate in the laboratory the thermodynamical conditions prevailing in the early universe up to 10$^{-6}$ seconds, thereby allowing the study of the quark-gluon plasma (QGP), a state of quantum…

High Energy Physics - Experiment · Physics 2020-11-26 CMS Collaboration

We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical…

High Energy Physics - Phenomenology · Physics 2021-06-23 C. K. Khosa , V. Sanz , M. Soughton

So-called unsupervised anomaly detection is better described as semi-supervised, as it assumes all training data are nominal. This assumption simplifies training but requires manual data curation, introducing bias and limiting adaptability.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Muhammad Aqeel , Shakiba Sharifi , Marco Cristani , Francesco Setti

The rejection of forward jets originating from additional proton--proton interactions (pile-up) is crucial for a variety of physics analyses at the LHC, including Standard Model measurements and searches for physics beyond the Standard…

High Energy Physics - Experiment · Physics 2017-09-20 ATLAS Collaboration

This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on a signal simulations for developing the analysis selection. Weakly supervised learning is used to…

High Energy Physics - Experiment · Physics 2022-01-12 ATLAS Collaboration

Quirks are generic predictions of strongly-coupled dark sectors. For weak-scale masses and a broad range of confining scales in the dark sector, quirks can be discovered only at the energy frontier, but quirk--anti-quirk pairs are produced…

High Energy Physics - Phenomenology · Physics 2024-07-04 Jonathan L. Feng , Jinmian Li , Xufei Liao , Jian Ni , Junle Pei

Unsupervised learning-based anomaly detection in latent space has gained importance since discriminating anomalies from normal data becomes difficult in high-dimensional space. Both density estimation and distance-based methods to detect…

Machine Learning · Computer Science 2024-02-16 Padmaksha Roy