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To maximise the potential for new measurements and discoveries at the LHC, the machine delivers as high as possible collision rates. As a consequence, multiple proton-proton collisions occur whenever two bunches cross. Interesting…

High Energy Physics - Phenomenology · Physics 2019-08-07 Gregory Soyez

At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets overlap. Deducing whether the substructure of an observed jet…

High Energy Physics - Experiment · Physics 2016-06-01 Pierre Baldi , Kevin Bauer , Clara Eng , Peter Sadowski , Daniel Whiteson

We present a novel approach for inspecting variable data prints (VDP) with an ultra-low false alarm rate (0.005%) and potential applicability to other real-world problems. The system is based on a comparison between two images: a reference…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Oren Haik , Oded Perry , Eli Chen , Peter Klammer

In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many…

High Energy Physics - Phenomenology · Physics 2025-02-13 Callum Birch-Sykes , Brian Le , Yvonne Peters , Ethan Simpson , Zihan Zhang

High energy (CERN SPS and LHC) $pp$ ($p\bar p$) scattering is treated in the framework of Additive Quark Model together with Pomeron exchange theory. The reasonable agreement with experimental data is achieved both for the elastic…

High Energy Physics - Phenomenology · Physics 2015-10-28 Yu. M. Shabelski , A. G. Shuvaev

The Large Hadron Collider, LHC, collides bunches of protons resulting in multiple interactions that occur practically simultaneously. This creates a pileup effect that distorts physics measurements due to the products of pileup collisions.…

High Energy Physics - Experiment · Physics 2025-03-05 Luke Vaughan , Mohammed Rakib , Shivang Patel , Flera Rizatdinova , Alexander Khanov , Arunkumar Bagavathi

Machine learning has become a powerful tool in high-energy collider experiments, which enables the studies based on data-driven approaches to complex reconstruction and regression tasks. The study of identified hadron spectra in…

High Energy Physics - Phenomenology · Physics 2026-05-12 Rishabh Gupta , Kangkan Goswami , Suraj Prasad , Raghunath Sahoo

We present a transformer architecture-based foundation model for tasks at high-energy particle colliders such as the Large Hadron Collider. We train the model to classify jets using a self-supervised strategy inspired by the Joint Embedding…

Machine Learning · Computer Science 2025-02-07 Jai Bardhan , Radhikesh Agrawal , Abhiram Tilak , Cyrin Neeraj , Subhadip Mitra

The mechanisms underlying hadronization are not well understood, both in vacuum and in hot QCD matter. Precise characterization of jet fragmentation to hadrons in p-p collisions will help elucidate the fundamental process of hadronization,…

Nuclear Experiment · Physics 2009-11-18 Helen Caines

Low-energy strong interactions are a major source of background at hadron colliders, and methods of subtracting the associated energy flow are well established in the field. Traditional approaches treat the contamination as diffuse, and…

Data Analysis, Statistics and Probability · Physics 2014-12-22 Federico Colecchia

We present a new framework for the modelling of hard diffraction in pp and ppbar collisions. It starts from the the approach pioneered by Ingelman and Schlein, wherein the single diffractive cross section is factorized into a Pomeron flux…

High Energy Physics - Phenomenology · Physics 2018-01-03 Christine O. Rasmussen , Torbjörn Sjöstrand

In this paper, we show predictions from a new QGP-free, no-equilibration, improved baseline model for heavy-ion collisions. It is comprised of the PYTHIA Angantyr event generator coupled to UrQMD, as a hadronic cascade simulator, and…

High Energy Physics - Phenomenology · Physics 2020-12-01 André Vieira da Silva , Willian Matioli Serenone , David Dobrigkeit Chinellato , Jun Takahashi , Christian Bierlich

We describe a method to measure and subtract the incoherent component of energy flow arising from multiple interactions from jet shape/substructure observables of ultra-massive jets. The amount subtracted is a function of the jet shape…

High Energy Physics - Phenomenology · Physics 2013-05-29 Raz Alon , Ehud Duchovni , Gilad Perez , Aliaksandr P. Pranko , Pekka K. Sinervo

We present an extension to the jet area-based pileup subtraction for both jet kinematics and jet shapes. A particle-level approach is explored whereby the jet constituents are corrected or removed using an extension of the methods currently…

High Energy Physics - Experiment · Physics 2014-07-04 Peter Berta , Martin Spousta , David W. Miller , Rupert Leitner

Jet substructure variables aim to reveal details of the parton fragmentation and hadronization processes that create a jet. By removing collinear radiation while maintaining the soft radiation components, one can construct CollinearDrop jet…

Nuclear Experiment · Physics 2023-07-19 Youqi Song

Identified-hadron (PID) $p_t$ spectra from 13 TeV $p$-$p$ collisions are compared with a two-component (soft+hard) model (TCM) that accurately distinguishes jet-related hadron production (hard component) from nonjet projectile-nucleon…

High Energy Physics - Phenomenology · Physics 2022-10-13 Thomas A. Trainor

In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require…

High Energy Physics - Experiment · Physics 2024-11-08 Samuel Van Stroud , Nikita Pond , Max Hart , Jackson Barr , Sébastien Rettie , Gabriel Facini , Tim Scanlon

A model for the production of large rapidity gaps being implemented in the Monte Carlo event generator PHOJET is discussed. In this model, high-mass diffraction dissociation exhibits properties similar to hadron production in…

High Energy Physics - Phenomenology · Physics 2007-05-23 F. W. Bopp , R. Engel , J. Ranft

Multivariate machine learning techniques provide an alternative to the rapidity gap method for event-by-event identification and classification of diffraction in hadron-hadron collisions. Traditionally, such methods assign each event…

High Energy Physics - Experiment · Physics 2015-05-20 Mikael Kuusela , Eric Malmi , Risto Orava , Tommi Vatanen