Publications

Order by: publication date number of citations

• Accelerating Monte Carlo event generation -- rejection sampling using neural network event-weight estimates

  Katharina Danziger, Timo Janßen, Steffen Schumann, Frank Siegert

  SciPost Phys. 12, 164 (2022) · published 18 May 2022 | Toggle abstract · pdf

  The generation of unit-weight events for complex scattering processes presents a severe challenge to modern Monte Carlo event generators. Even when using sophisticated phase-space sampling techniques adapted to the underlying transition matrix elements, the efficiency for generating unit-weight events from weighted samples can become a limiting factor in practical applications. Here we present a novel two-staged unweighting procedure that makes use of a neural-network surrogate for the full event weight. The algorithm can significantly accelerate the unweighting process, while it still guarantees unbiased sampling from the correct target distribution. We apply, validate and benchmark the new approach in high-multiplicity LHC production processes, including $Z/W$+4 jets and $t\bar{t}$+3 jets, where we find speed-up factors up to ten.

  17 citations

• An introduction to axions and their detection

  Igor García Irastorza

  SciPost Phys. Lect. Notes 45 (2022) · published 29 March 2022 | Toggle abstract · pdf

  In these notes I try to introduce the reader to the topic of axions: their theoretical motivation and expected phenomenology, their role in astrophysics and as dark matter candidate, and the experimental techniques to detect them. Special emphasis is made in this last point, for which a relatively updated review of worldwide efforts and future prospects is made. The material is intended as an introduction to the topic, and it was prepared as lecture notes for Les Houches summer school 2021. Abundant references are included to direct the reader to deeper insight on the different aspects of axion physics.

  12 citations

• Uncertainties associated with GAN-generated datasets in high energy physics

  Konstantin T. Matchev, Alexander Roman, Prasanth Shyamsundar

  SciPost Phys. 12, 104 (2022) · published 24 March 2022 | Toggle abstract · pdf

  Recently, Generative Adversarial Networks (GANs) trained on samples of traditionally simulated collider events have been proposed as a way of generating larger simulated datasets at a reduced computational cost. In this paper we point out that data generated by a GAN cannot statistically be better than the data it was trained on, and critically examine the applicability of GANs in various situations, including a) for replacing the entire Monte Carlo pipeline or parts of it, and b) to produce datasets for usage in highly sensitive analyses or sub-optimal ones. We present our arguments using information theoretic demonstrations, a toy example, as well as in the form of a formal statement, and identify some potential valid uses of GANs in collider simulations.

  12 citations

• The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider

  T. Aarrestad, M. van Beekveld, M. Bona, A. Boveia, S. Caron, J. Davies, A. De Simone, C. Doglioni, J. M. Duarte, A. Farbin, H. Gupta, L. Hendriks, L. Heinrich, J. Howarth, P. Jawahar, A. Jueid, J. Lastow, A. Leinweber, J. Mamuzic, E. Merényi, A. Morandini, P. Moskvitina, C. Nellist, J. Ngadiuba, B. Ostdiek, M. Pierini, B. Ravina, R. Ruiz de Austri, S. Sekmen, M. Touranakou, M. Vaškevičiūte, R. Vilalta, J. R. Vlimant, R. Verheyen, M. White, E. Wulff, E. Wallin, K. A. Wozniak, Z. Zhang

  SciPost Phys. 12, 043 (2022) · published 28 January 2022 | Toggle abstract · pdf

  We describe the outcome of a data challenge conducted as part of the Dark Machines Initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims at detecting signals of new physics at the LHC using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of >1 Billion simulated LHC events corresponding to $10~\rm{fb}^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.

  47 citations

• Publishing statistical models: Getting the most out of particle physics experiments

  Kyle Cranmer, Sabine Kraml, Harrison B. Prosper, Philip Bechtle, Florian U. Bernlochner, Itay M. Bloch, Enzo Canonero, Marcin Chrzaszcz, Andrea Coccaro, Jan Conrad, Glen Cowan, Matthew Feickert, Nahuel Ferreiro Iachellini, Andrew Fowlie, Lukas Heinrich, Alexander Held, Thomas Kuhr, Anders Kvellestad, Maeve Madigan, Farvah Mahmoudi, Knut Dundas Morå, Mark S. Neubauer, Maurizio Pierini, Juan Rojo, Sezen Sekmen, Luca Silvestrini, Veronica Sanz, Giordon Stark, Riccardo Torre, Robert Thorne, Wolfgang Waltenberger, Nicholas Wardle, Jonas Wittbrodt

  SciPost Phys. 12, 037 (2022) · published 25 January 2022 | Toggle abstract · pdf

  The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases -- including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits -- we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

  19 citations

• BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

  Wenjing Wang, Mohan Krishnamoorthy, Juliane Muller, Stephen Mrenna, Holger Schulz, Xiangyang Ju, Sven Leyffer, Zachary Marshall

  SciPost Phys. Core 5, 001 (2022) · published 17 January 2022 | Toggle abstract · pdf

  The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the Sherpa generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators.

  3 citations

• Current status and prospects of muonium spectroscopy at PSI

  B. Ohayon, Z. Burkley, P. Crivelli

  SciPost Phys. Proc. 5, 029 (2021) · published 6 September 2021 | Toggle abstract · pdf

  Recent and ongoing developments of low energy muon beamlines are heralding a new era of precision Muonium spectroscopy. While past spectroscopic measurements of Muonium were performed at pulsed muon facilities and were statistically limited, the advent of continuous low energy muon beams, such as at the LEM beamline at PSI, paired with the development of efficient muon-muonium converters and laser advancements, will overcome these limitations. Current experiments presently underway at the LEM facility and in the near future at the muCool beamline, which is under development at PSI, aim to improve the precision of both the 1S-2S transition determination and Lamb shift by several orders of magnitude. In this Chapter we give an overview of the current status and future prospects of these activities at PSI, highlighting how their projected significance fits into a broader context of other ongoing efforts worldwide.

  5 citations

• The search for the neutron electric dipole moment at PSI

  Guillaume Pignol, Philipp Schmidt-Wellenburg

  SciPost Phys. Proc. 5, 027 (2021) · published 6 September 2021 | Toggle abstract · pdf

  The existence of a nonzero permanent electric dipole moment (EDM) of the neutron would reveal a new source of CP violation and shed light on the origin of the matter--antimatter asymmetry of the Universe. The sensitivity of current experiments using stored ultracold neutrons (UCN) probes new physics beyond the TeV scale. Using the UCN source at the Paul Scherrer Institut, the nEDM collaboration has performed the most sensitive measurement of the neutron EDM to date, still compatible with zero ($|d_n|<1.8\times 10^{-26} \, e {\rm cm}$, C.L.90%). A new experiment designed to improve the sensitivity by an order of magnitude, n2EDM, is currently in construction.

  3 citations

• Recent results of laser spectroscopy experiments of pionic helium atoms at PSI

  M. Hori, H. Aghai-Khozani, A. S\'ot\'er, A. Dax, D. Barna

  SciPost Phys. Proc. 5, 026 (2021) · published 6 September 2021 | Toggle abstract · pdf

  A review of a recent experiment carried out at PSI involving laser spectroscopy of metastable pionic helium ($\pi{\rm ^4He}^+\equiv\pi^{-}+{\rm ^4He}^{2+}+e^-$) atoms is presented. An infrared transition $(n,\ell)=(17,16)$$\rightarrow$$(17,15)$ at a resonance frequency of $\nu\approx 183760$ GHz was detected.

  2 citations

• MEG: Muon to Electron and Gamma

  A.M. Baldini, T. Mori

  SciPost Phys. Proc. 5, 019 (2021) · published 6 September 2021 | Toggle abstract · pdf

  The possible existence of the muon to electron and gamma decay predicted by many new physics scenarios is investigated by stopping positive muons in a very thin target and measuring emitted photons and positrons with the best possible resolutions. Photons are measured by a 2.7 ton ultra pure liquid xenon detector while positron trajectories are measured in a specially designed gradient magnetic field by low-mass drift chambers and precisely timed by scintillation counters. A first phase of the experiment (MEG) ended in 2016, and excluded the existence of the decay with branching ratios larger than 4.2x10**(-13) (90% C.L.). This provides approximately 30 times stronger constraints on a variety of new physics models than previous experiments. In the second phase (MEG II), most of the detectors have been upgraded by adopting up-to-date technologies to improve the search sensitivity by another order of magnitude down to O(10**(-19) ). MEG II will pursue new physics beyond the Standard Model complementary to high energy collider experiments with a compatible or even higher sensitivity.

  2 citations