Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2203.07460

Machine Learning and LHC Event Generation

Anja Butter·Tilman Plehn·Steffen Schumann·Simon Badger·Sascha Caron·Kyle Cranmer·Francesco Armando Di Bello·Etienne Dreyer·Stefano Forte·Sanmay Ganguly·Dorival Gonçalves·Eilam Gross·Theo Heimel·Gudrun Heinrich·Lukas Heinrich·Alexander Held·Stefan Höche·Jessica N. Howard·Philip Ilten·Joshua Isaacson·Timo Janßen·Stephen Jones·Marumi Kado·Michael Kagan·Gregor Kasieczka·Felix Kling·Sabine Kraml·Claudius Krause·Frank Krauss·Kevin Kröninger·Rahool Kumar Barman·Michel Luchmann·Vitaly Magerya·Daniel Maitre·Bogdan Malaescu·Fabio Maltoni·Till Martini·Olivier Mattelaer·Benjamin Nachman·Sebastian Pitz·Juan Rojo·Matthew Schwartz·David Shih·Frank Siegert·Roy Stegeman·Bob Stienen·Jesse Thaler·Rob Verheyen·Daniel Whiteson·Ramon Winterhalder·Jure Zupan
View original source ↗Read source document ↗Export metadata ↓

Abstract

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem.

Explore related subjects

hep-phhep-ex

Keep this discovery

BibTeXRIS

Anja Butter, Tilman Plehn, Steffen Schumann, Simon Badger, Sascha Caron, Kyle Cranmer, Francesco Armando Di Bello, Etienne Dreyer, Stefano Forte, Sanmay Ganguly, Dorival Gonçalves, Eilam Gross, Theo Heimel, Gudrun Heinrich, Lukas Heinrich, Alexander Held, Stefan Höche, Jessica N. Howard, Philip Ilten, Joshua Isaacson, Timo Janßen, Stephen Jones, Marumi Kado, Michael Kagan, Gregor Kasieczka, Felix Kling, Sabine Kraml, Claudius Krause, Frank Krauss, Kevin Kröninger, Rahool Kumar Barman, Michel Luchmann, Vitaly Magerya, Daniel Maitre, Bogdan Malaescu, Fabio Maltoni, Till Martini, Olivier Mattelaer, Benjamin Nachman, Sebastian Pitz, Juan Rojo, Matthew Schwartz, David Shih, Frank Siegert, Roy Stegeman, Bob Stienen, Jesse Thaler, Rob Verheyen, Daniel Whiteson, Ramon Winterhalder, Jure Zupan. 2022-03-14. Machine Learning and LHC Event Generation. https://doi.org/10.21468/scipostphys.14.4.079

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Axionic Wormholes in Metric-Affine Gravity

The axion is a promising candidate for solving the strong CP problem. To solve this problem, the global U(1) symmetry must be preserved to a high degree of accuracy. However, it is well known that global symmetries are explicitly violated by quantum gravity effects, giving rise to what is referred to as the axion quality problem. In this paper, we investigate axionic wormholes as a source of explicit U(1) violation in Metric-Affine Gravity. This framework allows for spacetime torsion and non-metricity, which accommodate additional curvature-like and topological terms, such as the Holst and Nieh--Yan terms, that are absent from the metric and Palatini formalisms. We show that non-minimal couplings to these terms modify the wormhole dynamics and enhance the Euclidean wormhole action, thereby alleviating the axion quality problem. We also find that the viable parameter space is enlarged when two of these couplings are simultaneously present. We further identify representative parameter regions where the alleviation of the axion quality problem is compatible with inflationary constraints.

hep-ph↗
arXiv2026

Qubit-Qutrit Quantum Tomography of hadronic $\Lambda\phi$ and $\Lambda K^{\ast 0}$ systems

Quantum-information observables have emerged in recent years as new tools in nuclear and particle physics, from entanglement in top-quark pairs to spin correlations in $\Lambda\bar{\Lambda}$ production. Extending these studies to unequal-spin hadronic final states poses a fundamental challenge: the $6\times6$ density matrix of a qubit-qutrit system contains 35 independent spin parameters, but the decays of $\Lambda V$ pairs, with $V=\phi$ or $K^{*0}$, provide access to only 23 due to the hidden vector polarization from the strong decay. In this Letter, we formulate a qubit-qutrit quantum tomography (QQQT) technique for these spin-$\tfrac{1}{2}\otimes1$ systems and establish exact criteria for entanglement certification from the \textit{incomplete} density matrix. Compared with the $\Lambda\bar{\Lambda}$ system, QQQT of $\Lambda\phi$ and $\Lambda K^{*0}$ provides a new probe of nonperturbative QCD hadronization, enabling a direct comparison of the spin evolution of entangled quark pairs produced from the vacuum as they hadronize into a baryon or a vector meson.

hep-ph↗
arXiv2026

Twist decomposition of exclusive heavy meson production cross sections

We study the twist decomposition of the total cross sections for exclusive heavy vector meson electroproduction and photoproduction in the $\gamma^\ast p$ processes, within the leading logarithmic $1/x$ BFKL formalism. The Mellin transforms of the impact factors of the vector meson are calculated. We show that the higher twist contributions are strongly suppressed in the low-$x$ kinematical regime. Possible enhancement of the higher twists effects for nuclei targets is discussed.

hep-ph↗