Publications

Order by: publication date number of citations

• Effective field theory descriptions of Higgs boson pair production

  Lina Alasfar, Luca Cadamuro, Christina Dimitriadi, Arnaud Ferrari, Ramona Gröber, Gudrun Heinrich, Tom Ingebretsen Carlson, Jannis Lang, Serhat Ördek, Laura Pereira Sánchez, Ludovic Scyboz, Jörgen Sjölin

  SciPost Phys. Comm. Rep. 2 (2024) · published 16 October 2024 | Toggle abstract · pdf

  Higgs boson pair production is traditionally considered to be of particular interest for a measurement of the trilinear Higgs self-coupling. Yet it can offer insights into other couplings as well, since -- in an effective field theory (EFT) parameterisation of potential new physics -- both the production cross section and kinematical properties of the Higgs boson pair depend on various other Wilson coefficients of EFT operators. This note summarises the ongoing efforts related to the development of EFT tools for Higgs boson pair production in gluon fusion, and provides recommendations for the use of distinct EFT parameterisations in the Higgs boson pair production process. This document also outlines where further efforts are needed and provides a detailed analysis of theoretical uncertainties. Additionally, benchmark scenarios are updated. We also re-derive a parameterisation of the next-to-leading order (NLO) QCD corrections in terms of the EFT Wilson coefficients both for the total cross section and the distribution in the invariant mass of the Higgs boson pair, providing for the first time also the covariance matrix. A reweighting procedure making use of the newly derived coefficients is validated, which can be used to significantly speed up experimental analyses.

  2 citations

• Higher-form symmetry and chiral transport in real-time Abelian lattice gauge theory

  Arpit Das, Adrien Florio, Nabil Iqbal, Napat Poovuttikul

  SciPost Phys. 17, 085 (2024) · published 19 September 2024 | Toggle abstract · pdf

  We study classical lattice simulations of theories of electrodynamics coupled to charged matter at finite temperature, interpreting them using the higher-form symmetry formulation of magnetohydrodynamics (MHD). We compute transport coefficients using classical Kubo formulas on the lattice and show that the properties of the simulated plasma are in complete agreement with the predictions from effective field theories. In particular, the higher-form formulation allows us to understand from hydrodynamic considerations the relaxation rate of axial charge in the chiral plasma observed in previous simulations. A key point is that the resistivity of the plasma – defined in terms of Kubo formulas for the electric field in the 1-form formulation of MHD – remains a well-defined and predictive quantity at strong electromagnetic coupling. However, the Kubo formulas used to define the conventional conductivity vanish at low frequencies due to electrodynamic fluctuations, and thus the concept of the conductivity of a gauged electric current must be interpreted with care.

  1 citation

• A portable parton-level event generator for the high-luminosity LHC

  Enrico Bothmann, Taylor Childers, Walter Giele, Stefan Höche, Joshua Isaacson, Max Knobbe

  SciPost Phys. 17, 081 (2024) · published 16 September 2024 | Toggle abstract · pdf

  The rapid deployment of computing hardware different from the traditional CPU+RAM model in data centers around the world mandates a change in the design of event generators for the Large Hadron Collider, in order to provide economically and ecologically sustainable simulations for the high-luminosity era of the LHC. Parton-level event generation is one of the most computationally demanding parts of the simulation and is therefore a prime target for improvements. We present a production-ready leading-order parton-level event generation framework capable of utilizing most modern hardware and discuss its performance in the standard candle processes of vector boson and top-quark pair production with up to five additional jets.

  3 citations

• Kicking it off(-shell) with direct diffusion

  Anja Butter, Tomáš Ježo, Michael Klasen, Mathias Kuschick, Sofia Palacios Schweitzer, Tilman Plehn

  SciPost Phys. Core 7, 064 (2024) · published 16 September 2024 | Toggle abstract · pdf

  Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We present a novel method to transform high-dimensional distributions based on a diffusion neural network and use it to generate a process with off-shell kinematics from the much simpler on-shell one. Applied to a toy example of top pair production at LO we show how our method generates off-shell configurations fast and precisely, while reproducing even challenging on-shell features.

  6 citations

• Anomalies, representations, and self-supervision

  Barry M. Dillon, Luigi Favaro, Friedrich Feiden, Tanmoy Modak, Tilman Plehn

  SciPost Phys. Core 7, 056 (2024) · published 16 August 2024 | Toggle abstract · pdf

  We develop a self-supervised method for density-based anomaly detection using contrastive learning, and test it using event-level anomaly data from CMS ADC2021. The AnomalyCLR technique is data-driven and uses augmentations of the background data to mimic non-Standard-Model events in a model-agnostic way. It uses a permutation-invariant Transformer Encoder architecture to map the objects measured in a collider event to the representation space, where the data augmentations define a representation space which is sensitive to potential anomalous features. An AutoEncoder trained on background representations then computes anomaly scores for a variety of signals in the representation space. With AnomalyCLR we find significant improvements on performance metrics for all signals when compared to the raw data baseline.

  5 citations

• Top-down and bottom-up: Studying the SMEFT beyond leading order in $1/\Lambda^2$

  Tyler Corbett

  SciPost Phys. Core 7, 053 (2024) · published 14 August 2024 | Toggle abstract · pdf

  In order to assess the relevance of higher order terms in the Standard Model effective field theory (SMEFT) expansion we consider four new physics models and their impact on the Drell Yan cross section. Of these four, one scalar model has no effect on Drell Yan, a model of fermions while appearing to generate a momentum expansion actually belongs to the vacuum expectation value expansion and so has a nominal effect on the process. The remaining two, a leptoquark and a $Z'$ model exhibit a momentum expansion. After matching these models to dimension-ten we study the how the inclusion of dimension-eight and dimension-ten operators in hypothetical effective field theory fits to the full ultraviolet models impacts fits. We do this both in the top-down approach, and in a very limited approximation to the bottom up approach of the SMEFT to infer the impact of a fully general fit to the SMEFT. We find that for the more weakly coupled models a strictly dimension-six fit is sufficient. In contrast when stronger interactions or lighter masses are considered the inclusion of dimension-eight operators becomes necessary. However, their Wilson coefficients perform the role of nuisance parameters with best fit values which can differ statistically from the theory prediction. In the most strongly coupled theories considered (which are already ruled out by data) the inclusion of dimension-ten operators allows for the measurement of dimension-eight operator coefficients consistent with theory predictions and the dimension-ten operator coefficients then behave as nuisance parameters. We also study the impact of the inclusion of partial next order results, such as dimension-six squared contributions, and find that in some cases they improve the convergence of the series while in others they hinder it.

• CURTAINs flows for flows: Constructing unobserved regions with maximum likelihood estimation

  Debajyoti Sengupta, Sam Klein, John Andrew Raine, Tobias Golling

  SciPost Phys. 17, 046 (2024) · published 12 August 2024 | Toggle abstract · pdf

  Model independent techniques for constructing background data templates using generative models have shown great promise for use in searches for new physics processes at the LHC. We introduce \FfF, a major improvement to the CURTAINs method by training the conditional normalizing flow between two side-band regions using maximum likelihood estimation instead of an optimal transport loss. The new training objective improves the robustness and fidelity of the transformed data and is much faster and easier to train. We compare the performance against the previous approach and the current state of the art using the LHC Olympics anomaly detection dataset, where we see a significant improvement in sensitivity over the original CURTAINs method. Furthermore, CURTAINsF4F requires substantially less computational resources to cover a large number of signal regions than other fully data driven approaches. When using an efficient configuration, an order of magnitude more models can be trained in the same time required for ten signal regions, without a significant drop in performance.

  8 citations

• Towards a data-driven model of hadronization using normalizing flows

  Christian Bierlich, Phil Ilten, Tony Menzo, Stephen Mrenna, Manuel Szewc, Michael K. Wilkinson, Ahmed Youssef, Jure Zupan

  SciPost Phys. 17, 045 (2024) · published 12 August 2024 | Toggle abstract · pdf

  We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

  6 citations

• An algorithm to parallelise parton showers on a GPU

  Michael H. Seymour, Siddharth Sule

  SciPost Phys. Codebases 33 (2024) · published 12 August 2024 | Toggle abstract · pdf

  The Single Instruction, Multiple Thread (SIMT) paradigm of GPU programming does not support the branching nature of a parton shower algorithm by definition. However, modern GPUs are designed to schedule threads with diverging processes independently, allowing them to handle such branches. With regular thread synchronisation and careful treatment of the individual steps, one can simulate a parton shower on a GPU. We present a Sudakov veto algorithm designed to simulate parton branching on multiple events in parallel. We also release a CUDA C++ program that generates matrix elements, showers partons and computes jet rates and event shapes for LEP at 91.2 GeV on a GPU. To benchmark its performance, we also provide a near-identical C++ program designed to simulate events serially on a CPU. While the consequences of branching are not absent, we demonstrate that a GPU can provide the throughput of a many-core CPU. As an example, we show that the time taken to shower $10^6$ events on one NVIDIA TESLA V100 GPU is equivalent to that of 295 Intel Xeon E5-2620 CPU cores.

  1 citation

• Codebase release 1.1 for GAPS

  Michael H. Seymour, Siddharth Sule

  SciPost Phys. Codebases 33-r1.1 (2024) · published 12 August 2024 | Toggle abstract · src

  The Single Instruction, Multiple Thread (SIMT) paradigm of GPU programming does not support the branching nature of a parton shower algorithm by definition. However, modern GPUs are designed to schedule threads with diverging processes independently, allowing them to handle such branches. With regular thread synchronisation and careful treatment of the individual steps, one can simulate a parton shower on a GPU. We present a Sudakov veto algorithm designed to simulate parton branching on multiple events in parallel. We also release a CUDA C++ program that generates matrix elements, showers partons and computes jet rates and event shapes for LEP at 91.2 GeV on a GPU. To benchmark its performance, we also provide a near-identical C++ program designed to simulate events serially on a CPU. While the consequences of branching are not absent, we demonstrate that a GPU can provide the throughput of a many-core CPU. As an example, we show that the time taken to shower $10^6$ events on one NVIDIA TESLA V100 GPU is equivalent to that of 295 Intel Xeon E5-2620 CPU cores.

  1 citation