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Quantum Computing for High-Energy Physics: State of the Art and Challenges [PDF]

PRX Quantum, 2023
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup of numerical ...
A. D. Meglio, K. Jansen, I. Tavernelli, C. Alexandrou, Srinivasan Arunachalam, C. Bauer, K. Borras, S. Carrazza, Arianna Crippa, V. Croft, R. D. Putter, Andrea Delgado, V. Dunjko, D. Egger, E. Fernández-Combarro, Elina Fuchs, L. Funcke, D. González-Cuadra, M. Grossi, Jad C. Halimeh, Zoe Holmes, S. Kuhn, D. Lacroix, R. Lewis, D. Lucchesi, Miriam Lucio Martínez, F. Meloni, Antonio Mezzacapo, S. Montangero, Lento Nagano, V. Radescu, Enrique Rico Ortega, A. Roggero, Julian Schuhmacher, J. Seixas, P. Silvi, P. Spentzouris, F. Tacchino, K. Temme, K. Terashi, Jordi Tura i Brugués, Cenk Tüysüz, S. Vallecorsa, U. Wiese, Shinjae Yoo, Jinglei Zhang   +45 more
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Quantum Simulation for High-Energy Physics [PDF]

PRX Quantum, 2022
It is for the first time that Quantum Simulation for High Energy Physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community.
Christian W. Bauer. Zohreh Davoudi, A. Balantekin, Tanmoy Bhattacharya, M. Carena, W. A. Jong, P. Draper, A. El-Khadra, N. Gemelke, M. Hanada, D. Kharzeev, Henry Lamm, Yingying Li, Junyu Liu, M. Lukin, Y. Meurice, C. Monroe, B. Nachman, G. Pagano, J. Preskill, E. Rinaldi, A. Roggero, D. Santiago, M. Savage, I. Siddiqi, G. Siopsis, D. Zanten, N. Wiebe, Y. Yamauchi, Kubra Yeter-Aydeniz, S. Zorzetti   +29 more
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PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics [PDF]

SciPost Physics, 2023
In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with transformers which are well suited to the task of generating jets as particle
M. Leigh, Debasish Sengupta, Guillaume Qu'etant, J. Raine, K. Zoch, T. Golling   +5 more
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Fast point cloud generation with diffusion models in high energy physics [PDF]

Physical Review D, 2023
Many particle physics datasets like those generated at colliders are described by continuous coordinates (in contrast to grid points like in an image), respect a number of symmetries (like permutation invariance), and have a stochastic dimensionality ...
V. Mikuni, B. Nachman, Mariel Pettee
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High-energy nuclear physics meets machine learning [PDF]

Nuclear Science and Techniques, 2023
Although seemingly disparate, high-energy nuclear physics (HENP) and machine learning (ML) have begun to merge in the last few years, yielding interesting results. It is worthy to raise the profile of utilizing this novel mindset from ML in HENP, to help
Wanbing He, Yu-Gang Ma, L. Pang, Huichao Song, K. Zhou   +4 more
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Evaluating generative models in high energy physics [PDF]

Physical Review D, 2022
There has been a recent explosion in research into machine-learning-based generative modeling to tackle computational challenges for simulations in high energy physics (HEP).
R. Kansal, Anni Li, Javier Mauricio Duarte, N. Chernyavskaya, M. Pierini, B. Orzari, T. Tomei   +6 more
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Autoencoders for unsupervised anomaly detection in high energy physics [PDF]

Journal of High Energy Physics, 2021
Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for model-independent new physics searches.
Thorben Finke, M. Krämer, A. Morandini, A. Mück, Ivan Oleksiyuk   +4 more
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Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC [PDF]

Physical Review Research, 2021
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups.
S. Wu, Shaojun Sun, W. Guan, Chen Zhou, J. Chan, Chi Lung Cheng, T. Pham, Yan Qian, A. Wang, Rui Zhang, M. Livny, Jennifer R. Glick, P. Barkoutsos, Stefan Woerner, I. Tavernelli, F. Carminati, Alberto Di Meglio, A. Li, J. Lykken, P. Spentzouris, Samuel Yen-Chi Chen, Shinjae Yoo, T. Wei   +22 more
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Event generators for high-energy physics experiments [PDF]

SciPost Physics, 2022
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements.
J. Campbell, M. Diefenthaler, T. J. Hobbs, S. Höche, Joshua Isaacson, F. Kling, S. Mrenna, J. Reuter, S. Alioli, J. R. Andersen, C. Andreopoulos, A. Ankowski, E. Aschenauer, A. Ashkenazi, M. D. Baker, J. Barrow, Melissa van Beekveld, G. Bewick, S. Bhattacharya, Christian Bierlich, E. Bothmann, P. Bredt, A. Broggio, A. Buckley, A. Butter, Jon Butterworth, E. P. Byrne, Carlo Carloni-Calame, Smita Chakraborty, X. Chen, M. Chiesa, J. T. Childers, J. Cruz-Martinez, J. Currie, N. Darvishi, M. Dasgupta, A. Denner, F. Dreyer, S. Dytman, B. K. El-Menoufi, T. Engel, Silvia Ferrario Ravasio, Daniel Figueroa, L. Flower, J. R. Forshaw, R. Frederix, A. Friedland, S. Frixione, H. Gallagher, K. Gallmeister, S. Gardiner, R. Gauld, Jonathan Gaunt, A. Gavardi, T. Gehrmann, A. Gehrmann-De Ridder, L. Gellersen, W. Giele, S. Gieseke, F. Giuli, E. Glover, M. Grazzini, A. Grohsjean, Christian Gütschow, Keith Hamilton, T. Han, R. Hatcher, G. Heinrich, I. Helenius, O. Hen, Valentin Hirschi, M. Höfer, J. Holguin, A. Huss, P. Ilten, S. Jadach, A. Jentsch, S. Jones, W. Ju, S. Kallweit, Alexander Karlberg, T. Katori, M. Kerner, C. Kilian, M. M. Kirchgaesser, S. Klein, M. Knobbe, C. Krause, F. Krauss, J. Lang, J. Lang, G. Lee, S. Li, M. A. Lim, J. Lindert, D. Lombardi, L. Lönnblad, M. Löschner, N. Lurkin, Y. Ma, P. Machado, V. Magerya, A. Maier, I. Majer, F. Maltoni, M. Marcoli, G. Marinelli, M. Masouminia, P. Mastrolia, O. Mattelaer, J. Mazzitelli, J. Mcfayden, R. Medves, P. Meinzinger, J. Mo, P. Monni, G. Montagna, T. Morgan, U. Mosel, B. Nachman, P. Nadolsky, R. Nagar, Zoltán Nagy, D. Napoletano, P. Nason, Tobias Neumann, L. Nevay, O. Nicrosini, J. Niehues, K. Niewczas, Thorsten Ohl, G. Ossola, V. Pandey, A. Papadopoulou, A. Papaefstathiou, Gil Paz, M. Pellen, G. Pelliccioli, T. Peraro, F. Piccinini, L. Pickering, J. Pires, W. Płaczek, Simon Plätzer, Tilman Plehn, S. Pozzorini, S. Prestel, C. Preuss, A. Price, S. Quackenbush, E. Re, D. Reichelt, L. Reina, C. Reuschle, Peter Richardson, M. Rocco, N. Rocco, M. Roda, A. Rodriguez Garcia, S. Roiser, Juan Rojo, L. Rottoli, Gavin P. Salam, M. Schönherr, S. Schuchmann, Steffen Schumann, R. Schürmann, L. Scyboz, Michael H. Seymour, F. Siegert, A. Signer, G. Chahal, A. Siódmok, T. Sjöstrand, P. Skands, J. Smillie, J. Sobczyk, D. Soldin, D. Soper, A. Soto-Ontoso, Gregory Soyez, G. Stagnitto, J. Tena-Vidal, O. Tomalak, F. Tramontano, S. Trojanowski, Z. Tu, S. Uccirati, T. Ullrich, Y. Ulrich, M. Utheim, A. Valassi, A. Verbytskyi, R. Verheyen, M. Wagman, D. Walker, B. R. Webber, L. Weinstein, O. White, J. Whitehead, M. Wiesemann, C. Wilkinson, C. Williams, R. Winterhalder, C. Wret, K. Xie, T.-Z. Yang, E. Yazgan, G. Zanderighi, S. Zanoli, K. Zapp   +210 more
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Anomaly detection in high-energy physics using a quantum autoencoder [PDF]

Physical Review D, 2021
The lack of evidence for new interactions and particles at the Large Hadron Collider has motivated the high-energy physics community to explore model-agnostic data-analysis approaches to search for new physics.
Vishal S. Ngairangbam, M. Spannowsky, M. Takeuchi   +2 more
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