Publications

Order by: publication date number of citations

• Casting a graph net to catch dark showers

  Elias Bernreuther, Thorben Finke, Felix Kahlhoefer, Michael Krämer, Alexander Mück

  SciPost Phys. 10, 046 (2021) · published 23 February 2021 | Toggle abstract · pdf

  Strongly interacting dark sectors predict novel LHC signatures such as semi-visible jets resulting from dark showers that contain both stable and unstable dark mesons. Distinguishing such semi-visible jets from large QCD backgrounds is difficult and constitutes an exciting challenge for jet classification. In this article we explore the potential of supervised deep neural networks to identify semi-visible jets. We show that dynamic graph convolutional neural networks operating on so-called particle clouds outperform convolutional neural networks analysing jet images as well as other neural networks based on Lorentz vectors. We investigate how the performance depends on the properties of the dark shower and discuss training on mixed samples as a strategy to reduce model dependence. By modifying an existing mono-jet analysis we show that LHC sensitivity to dark sectors can be enhanced by more than an order of magnitude by using the dynamic graph network as a dark shower tagger.

  35 citations

• Blast from the past: Constraints on the dark sector from the BEBC WA66 beam dump experiment

  Giacomo Marocco, Subir Sarkar

  SciPost Phys. 10, 043 (2021) · published 19 February 2021 | Toggle abstract · pdf

  We derive limits on millicharged dark states, as well as particles with electric or magnetic dipole moments, from the number of observed forward electron scattering events at the Big European Bubble Chamber in the 1982 CERN-WA-066 beam dump experiment. The dark states are produced by the 400~GeV proton beam primarily through the decays of mesons produced in the beam dump, and the lack of excess events places bounds extending up to GeV masses. These improve on bounds from all other experiments, in particular CHARM~II.

  24 citations

• A study of collider signatures for two Higgs doublet models with a Pseudoscalar mediator to Dark Matter

  Jonathan M. Butterworth, Martin Habedank, Priscilla Pani, Andrius Vaitkus

  SciPost Phys. Core 4, 003 (2021) · published 18 February 2021 | Toggle abstract · pdf

  Two Higgs doublet models with an additional pseudoscalar particle coupling to the Standard Model and to a new stable, neutral particle, provide an attractive and fairly minimal route to solving the problem of Dark Matter. They have been the subject of several searches at the LHC. We study the impact of existing LHC measurements on such models, first in the benchmark regions addressed by searches and then after relaxing some of their assumptions and broadening the parameter ranges considered. In each case we study how the new parameters change the potentially visible signatures at the LHC, and identify which of these signatures should already have had a significant impact on existing measurements. This allows us to set some first constraints on a number of so far unstudied scenarios.

  10 citations

• Dark Matter EFT, the Third -- Neutrino WIMPs

  Ingolf Bischer, Tilman Plehn, Werner Rodejohann

  SciPost Phys. 10, 039 (2021) · published 17 February 2021 | Toggle abstract · pdf

  Sterile neutrinos coupling only to third-generation fermions are attractive dark matter candidates. In an EFT approach we demonstrate that they can generate the observed relic density without violating constraints from direct and indirect detection. Such an EFT represents a gauged third-generation $B-L$ model, as well as third-generation scalar or vector leptoquarks. LHC measurements naturally distinguish the different underlying models.

  4 citations

• Phase space sampling and inference from weighted events with autoregressive flows

  Bob Stienen, Rob Verheyen

  SciPost Phys. 10, 038 (2021) · published 17 February 2021 | Toggle abstract · pdf

  We explore the use of autoregressive flows, a type of generative model with tractable likelihood, as a means of efficient generation of physical particle collider events. The usual maximum likelihood loss function is supplemented by an event weight, allowing for inference from event samples with variable, and even negative event weights. To illustrate the efficacy of the model, we perform experiments with leading-order top pair production events at an electron collider with importance sampling weights, and with next-to-leading-order top pair production events at the LHC that involve negative weights.

  36 citations

• OASIS: Optimal Analysis-Specific Importance Sampling for event generation

  Konstantin T. Matchev, Prasanth Shyamsundar

  SciPost Phys. 10, 034 (2021) · published 15 February 2021 | Toggle abstract · pdf

  We propose a technique called Optimal Analysis-Specific Importance Sampling (OASIS) to reduce the number of simulated events required for a high-energy experimental analysis to reach a target sensitivity. We provide recipes to obtain the optimal sampling distributions which preferentially focus the event generation on the regions of phase space with high utility to the experimental analyses. OASIS leads to a conservation of resources at all stages of the Monte Carlo pipeline, including full-detector simulation, and is complementary to approaches which seek to speed-up the simulation pipeline.

  6 citations

• Phase transitions in the early universe

  Mark Hindmarsh, Marvin Lüben, Johannes Lumma, Martin Pauly

  SciPost Phys. Lect. Notes 24 (2021) · published 15 February 2021 | Toggle abstract · pdf

  These lecture notes are based on a course given by Mark Hindmarsh at the 24th Saalburg Summer School 2018 and written up by Marvin L\"uben, Johannes Lumma and Martin Pauly. The aim is to provide the necessary basics to understand first-order phase transitions in the early universe, to outline how they leave imprints in gravitational waves, and advertise how those gravitational waves could be detected in the future. A first-order phase transition at the electroweak scale is a prediction of many theories beyond the Standard Model, and is also motivated as an ingredient of some theories attempting to provide an explanation for the matter-antimatter asymmetry in our Universe. Starting from bosonic and fermionic statistics, we derive Boltzmann's equation and generalise to a fluid of particles with field dependent mass. We introduce the thermal effective potential for the field in its lowest order approximation, discuss the transition to the Higgs phase in the Standard Model and beyond, and compute the probability for the field to cross a potential barrier. After these preliminaries, we provide a hydrodynamical description of first-order phase transitions as it is appropriate for describing the early Universe. We thereby discuss the key quantities characterising a phase transition, and how they are imprinted in the gravitational wave power spectrum that might be detectable by the space-based gravitational wave detector LISA in the 2030s.

  74 citations

• Light dark matter annihilation and scattering in LHC detectors

  Martin Bauer, Patrick Foldenauer, Peter Reimitz, Tilman Plehn

  SciPost Phys. 10, 030 (2021) · published 5 February 2021 | Toggle abstract · pdf

  We systematically study models with light scalar and pseudoscalar dark matter candidates and their potential signals at the LHC. First, we derive cosmological bounds on models with the Standard Model Higgs mediator and with a new weak-scale mediator. Next, we study two processes inspired by the indirect and direct detection process topologies, now happening inside the LHC detectors. We find that LHC can observe very light dark matter over a huge mass range if it is produced in mediator decays and then scatters with the detector material to generate jets in the nuclear recoil.

  8 citations

• Improved neural network Monte Carlo simulation

  I-Kai Chen, Matthew D. Klimek, Maxim Perelstein

  SciPost Phys. 10, 023 (2021) · published 29 January 2021 | Toggle abstract · pdf

  The algorithm for Monte Carlo simulation of parton-level events based on an Artificial Neural Network (ANN) proposed in arXiv:1810.11509 is used to perform a simulation of $H\to 4\ell$ decay. Improvements in the training algorithm have been implemented to avoid numerical instabilities. The integrated decay width evaluated by the ANN is within 0.7% of the true value and unweighting efficiency of 26% is reached. While the ANN is not automatically bijective between input and output spaces, which can lead to issues with simulation quality, we argue that the training procedure naturally prefers bijective maps, and demonstrate that the trained ANN is bijective to a very good approximation.

  25 citations

• Useful relations among the generators in the defining and adjoint representations of SU(N)

  Howard E. Haber

  SciPost Phys. Lect. Notes 21 (2021) · published 20 January 2021 | Toggle abstract · pdf

  There are numerous relations among the generators in the defining and adjoint representations of SU(N). These include Casimir operators, formulae for traces of products of generators, etc. Due to the existence of the completely symmetric tensor $d_{abc}$ that arises in the study of the SU(N) Lie algebra, one can also consider relations that involve the adjoint representation matrix, $(D^a)_{bc}=d_{abc}$. In this review, we summarize many useful relations satisfied by the defining and adjoint representation matrices of SU(N). A few relations special to the case of N=3 are highlighted.

  10 citations