Contributor info: Dr Andrzej Siodmok

Riccardo Aliberti, Paolo Beltrame, Ettore Budassi, Carlo M. Carloni Calame, Gilberto Colangelo, Lorenzo Cotrozzi, Achim Denig, Anna Driutti, Tim Engel, Lois Flower, Andrea Gurgone, Martin Hoferichter, Fedor Ignatov, Sophie Kollatzsch, Bastian Kubis, Andrzej Kupść, Fabian Lange, Alberto Lusiani, Stefan E. Müller, Jérémy Paltrinieri, Pau Petit Rosàs, Fulvio Piccinini, Alan Price, Lorenzo Punzi, Marco Rocco, Olga Shekhovtsova, Andrzej Siódmok, Adrian Signer, Giovanni Stagnitto, Peter Stoffer, Thomas Teubner, William J. Torres Bobadilla, Francesco P. Ucci, Yannick Ulrich, Graziano Venanzoni

SciPost Phys. Comm. Rep. 9 (2025) · published 25 June 2025 | Toggle abstract · pdf

We present the results of Phase I of an ongoing review of Monte Carlo tools relevant for low-energy hadronic cross sections. This includes a detailed comparison of Monte Carlo codes for electron–positron scattering into a muon pair, pion pair, and electron pair, for scan and radiative-return experiments. After discussing the various approaches that are used and effects that are included, we show differential cross sections obtained with AfkQed, BabaYaga@NLO, KKMC, MCGPJ, McMule, Phokhara, and Sherpa, for scenarios that are inspired by experiments providing input for the dispersive evaluation of the hadronic vacuum polarisation.

J. M. Campbell, M. Diefenthaler, T. J. Hobbs, S. Höche, J. Isaacson, F. Kling, S. Mrenna, J. Reuter, S. Alioli, J. R. Andersen, C. Andreopoulos, A. M. Ankowski, E. C. Aschenauer, A. Ashkenazi, M. D. Baker, J. L. Barrow, M. van Beekveld, G. Bewick, S. Bhattacharya, C. Bierlich, E. Bothmann, P. Bredt, A. Broggio, A. Buckley, A. Butter, J. M. Butterworth, E. P. Byrne, C. M. Carloni-Calame, S. Chakraborty, X. Chen, M. Chiesa, J. T. Childers, J. Cruz-Martinez, J. Currie, N. Darvishi, M. Dasgupta, A. Denner, F. A. Dreyer, S. Dytman, B. K. El-Menoufi, T. Engel, S. Ferrario Ravasio, D. Figueroa, L. Flower, J. R. Forshaw, R. Frederix, A. Friedland, S. Frixione, H. Gallagher, K. Gallmeister, S. Gardiner, R. Gauld, J. Gaunt, A. Gavardi, T. Gehrmann, A. Gehrmann-De Ridder, L. Gellersen, W. Giele, S. Gieseke, F. Giuli, E. W. N. Glover, M. Grazzini, A. Grohsjean, C. Gütschow, K. Hamilton, T. Han, R. Hatcher, G. Heinrich, I. Helenius, O. Hen, V. Hirschi, M. Höfer, J. Holguin, A. Huss, P. Ilten, S. Jadach, A. Jentsch, S. P. Jones, W. Ju, S. Kallweit, A. Karlberg, T. Katori, M. Kerner, W. Kilian, M. M. Kirchgaeßer, S. Klein, M. Knobbe, C. Krause, F. Krauss, J. Lang, J. -N. Lang, G. Lee, S. W. Li, M. A. Lim, J. M. 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. R. Masouminia, P. Mastrolia, O. Mattelaer, J. Mazzitelli, J. McFayden, R. Medves, P. Meinzinger, J. Mo, P. F. Monni, G. Montagna, T. Morgan, U. Mosel, B. Nachman, P. Nadolsky, R. Nagar, Z. Nagy, D. Napoletano, P. Nason, T. Neumann, L. J. Nevay, O. Nicrosini, J. Niehues, K. Niewczas, T. Ohl, G. Ossola, V. Pandey, A. Papadopoulou, A. Papaefstathiou, G. Paz, M. Pellen, G. Pelliccioli, T. Peraro, F. Piccinini, L. Pickering, J. Pires, W. Placzek, S. Plätzer, T. Plehn, S. Pozzorini, S. Prestel, C. T. Preuss, A. C. Price, S. Quackenbush, E. Re, D. Reichelt, L. Reina, C. Reuschle, P. Richardson, M. Rocco, N. Rocco, M. Roda, A. Rodriguez Garcia, S. Roiser, J. Rojo, L. Rottoli, G. P. Salam, M. Schönherr, S. Schuchmann, S. Schumann, R. Schürmann, L. Scyboz, M. H. Seymour, F. Siegert, A. Signer, G. Singh Chahal, A. Siódmok, T. Sjöstrand, P. Skands, J. M. Smillie, J. T. Sobczyk, D. Soldin, D. E. Soper, A. Soto-Ontoso, G. 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

SciPost Phys. 16, 130 (2024) · published 24 May 2024 | Toggle abstract · pdf

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. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

Enrico Bothmann, Andy Buckley, Christian Gütschow, Stefan Prestel, Marek Schönherr, Peter Skands, Jeppe R. Andersen, Saptaparna Bhattacharya, Jonathan Butterworth, Gurpreet Singh Chahal, Louie Corpe, Leif Gellersen, Matthew Gignac, Stefan Höche, Deepak Kar, Frank Krauss, Jan Kretzschmar, Leif Lönnblad, Josh McFayden, Andreas Papaefstathiou, Simon Plätzer, Steffen Schumann, Michael H. Seymour, Frank Siegert, Andrzej Siódmok

SciPost Phys. Core 6, 007 (2023) · published 8 February 2023 | Toggle abstract · pdf

Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.