Contributor info: Mr Max Knobbe

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, Taylor Childers, Walter Giele, Florian Herren, Stefan Höche, Joshua Isaacson, Max Knobbe, Rui Wang

SciPost Phys. 15, 169 (2023) · published 18 October 2023 | Toggle abstract · pdf

We present a simple yet efficient algorithm for phase-space integration at hadron colliders. Individual mappings consist of a single t-channel combined with any number of s-channel decays, and are constructed using diagrammatic information. The factorial growth in the number of channels is tamed by providing an option to limit the number of s-channel topologies. We provide a publicly available, parallelized code in C++ and test its performance in typical LHC scenarios.

Enrico Bothmann, Walter Giele, Stefan Hoeche, Joshua Isaacson, Max Knobbe

SciPost Phys. Codebases 3 (2022) · published 23 August 2022 | Toggle abstract · pdf

The compute efficiency of Monte-Carlo event generators for the Large Hadron Collider is expected to become a major bottleneck for simulations in the high-luminosity phase. Aiming at the development of a full-fledged generator for modern GPUs, we study the performance of various recursive strategies to compute multi-gluon tree-level amplitudes. We investigate the scaling of the algorithms on both CPU and GPU hardware. Finally, we provide practical recommendations as well as baseline implementations for the development of future simulation programs. The GPU implementations can be found at: https://www.gitlab.com/ebothmann/blockgen-archive.

Enrico Bothmann, Walter Giele, Stefan Hoeche, Joshua Isaacson, Max Knobbe

SciPost Phys. Codebases 3-r1.0 (2022) · published 23 August 2022 | Toggle abstract · src

The compute efficiency of Monte-Carlo event generators for the Large Hadron Collider is expected to become a major bottleneck for simulations in the high-luminosity phase. Aiming at the development of a full-fledged generator for modern GPUs, we study the performance of various recursive strategies to compute multi-gluon tree-level amplitudes. We investigate the scaling of the algorithms on both CPU and GPU hardware. Finally, we provide practical recommendations as well as baseline implementations for the development of future simulation programs. The GPU implementations can be found at: https://www.gitlab.com/ebothmann/blockgen-archive.

Enrico Bothmann, Timo Janßen, Max Knobbe, Tobias Schmale, Steffen Schumann

SciPost Phys. 8, 069 (2020) · published 29 April 2020 | Toggle abstract · pdf

We present a novel approach for the integration of scattering cross sections and the generation of partonic event samples in high-energy physics. We propose an importance sampling technique capable of overcoming typical deficiencies of existing approaches by incorporating neural networks. The method guarantees full phase space coverage and the exact reproduction of the desired target distribution, in our case given by the squared transition matrix element. We study the performance of the algorithm for a few representative examples, including top-quark pair production and gluon scattering into three- and four-gluon final states.