Publications

Order by: publication date number of citations

• The DAMIC-M experiment: Status and first results

  Isaac J. Arnquist, Nicolas Avalos, Philippe Bailly, David Baxter, Xavier Bertou, Mircea Bogdan, Christian Bourgeois, J. Brandt, Arnaud Cadiou, Nuria Castelló-Mor, Alvaro E. Chavarria, Marcel Conde, Nicholas J. Corso, J. C. Gutiérrez, Julian Cuevas-Zepeda, Ali Dastgheibi-Fard, Claudia De Dominicis, Olivier Deligny, R. Desani, Marc Dhellot, Jean-Jacques Dormard, Jordi Duarte-Campderros, E. Estrada, D. Florin, N. Gadola, R. Gaïor, J. González Sánchez, Todd W. Hossbach, Michael Huehn, Latifa Khalil, Ben Kilminster, Agustin Lantero-Barreda, Ian Lawson, Hervé Lebbolo, Steven Lee, Pascal Leray, Antoine Letessier-Selvon, Pia Loaiza, Amparo Lopez-Virto, David Martin, Ariel Matalon, Kellie McGuire, T. Milleto, Pitam Mitra, David M. Martin, S. Munagavalasa, Danielle Norcini, Cory T. Overman, Giorgos Papadopoulos, S. Paul, David Peterson, Alexander Piers, Olivier Pochon, Paolo Privitera, Karthik Ramanathan, Denis Reynet, Peter Robmann, Ryan Roehnelt, Mariangela Settimo, Radomir Smida, Ben Stillwell, Ryan Thomas, Michelangelo Traina, Philippe Vallerand, Tim Van Wechel, Ivan Vila, Rocio V. Cortabitarte, Achim Vollhardt, Guillaume Warot, D. Wolf, Rachana Yajur, J-P. Zopounidis

  SciPost Phys. Proc. 12, 014 (2023) · published 3 July 2023 | Toggle abstract · pdf

  The DAMIC-M (DArk Matter In CCDs at Modane) experiment employs thick, fully depleted silicon charged-coupled devices (CCDs) to search for dark matter particles with a target exposure of 1 kg-year. A novel skipper readout implemented in the CCDs provides single electron resolution through multiple non-destructive measurements of the individual pixel charge, pushing the detection threshold to the eV-scale. DAMIC-M will advance by several orders of magnitude the exploration of the dark matter particle hypothesis, in particular of candidates pertaining to the so-called "hidden sector." A prototype, the Low Background Chamber (LBC), with 20g of low background Skipper CCDs, has been recently installed at Laboratoire Souterrain de Modane and is currently taking data. We will report the status of the DAMIC-M experiment and first results obtained with LBC commissioning data.

  4 citations

• The WIMP paradigm: Theme and variations

  Jonathan L. Feng

  SciPost Phys. Lect. Notes 71 (2023) · published 13 June 2023 | Toggle abstract · pdf

  WIMPs, ↑ weakly-interacting massive particles, have been leading candidates for particle dark matter for decades, and they remain a viable and highly motivated possibility. In these lectures, I describe the basic motivations for WIMPs, beginning with the WIMP miracle and its under-appreciated cousin, the discrete WIMP miracle. I then give an overview of some of the basic features of WIMPs and how to find them. These lectures conclude with some variations on the WIMP theme that have by now become significant topics in their own right and illustrate the richness of the WIMP paradigm.

  10 citations

• Making digital objects FAIR in high energy physics: An implementation for Universal FeynRules Output (UFO) models

  Mark S. Neubauer, Avik Roy, Zijun Wang

  SciPost Phys. Codebases 13 (2023) · published 9 June 2023 | Toggle abstract · pdf

  Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

  1 citation

• Codebase release 2.0 for UFOManager

  Mark S. Neubauer, Avik Roy, Zijun Wang

  SciPost Phys. Codebases 13-r2.0 (2023) · published 9 June 2023 | Toggle abstract · src

  Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.

  1 citation

• STEP: A tool to perform tests of smoothness on differential distributions based on expansion of polynomials

  Patrick L. S. Connor, Radek Žlebčík

  SciPost Phys. Core 6, 040 (2023) · published 1 June 2023 | Toggle abstract · pdf

  We motivate and describe a method based on fits with polynomials to test the smoothness of differential distributions. As a demonstration, we apply the method to several measurements of inclusive jet double-differential cross section in the jet transverse momentum and rapidity at the Tevatron and LHC. This method opens new possibilities to test the quality of differential distributions used for the extraction of physics quantities such as the strong coupling.

  1 citation

• Strength in numbers: Optimal and scalable combination of LHC new-physics searches

  Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen

  SciPost Phys. 14, 077 (2023) · published 20 April 2023 | Toggle abstract · pdf

  To gain a comprehensive view of what the LHC tells us about physics beyond the Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in general search-analyses are not statistically orthogonal, so performing comprehensive combinations requires knowledge of the extent to which the same events co-populate multiple analyses' signal regions. We present a novel, stochastic method to determine this degree of overlap, and a graph algorithm to efficiently find the combination of signal regions with no mutual overlap that optimises expected upper limits on BSM-model cross-sections. The gain in exclusion power relative to single-analysis limits is demonstrated with models with varying degrees of complexity, ranging from simplified models to a 19-dimensional supersymmetric model.

  4 citations

• Cover your bases: asymptotic distributions of the profile likelihood ratio when constraining effective field theories in high-energy physics

  Florian Urs Bernlochner, Daniel C. Fry, Stephen Burns Menary, Eric Persson

  SciPost Phys. Core 6, 013 (2023) · published 16 March 2023 | Toggle abstract · pdf

  We investigate the asymptotic distribution of the profile likelihood ratio (PLR) when constraining effective field theories (EFTs) and show that Wilks' theorem is often violated, meaning that we should not assume the PLR to follow a $\chi^2$-distribution. We derive the correct asymptotic distributions when either one or two real EFT couplings modulate observable cross sections with a purely linear or quadratic dependence. We then discover that when both the linear and quadratic terms contribute, the PLR distribution does not have a simple form. In this case we provide a partly-numerical solution for the one-parameter case. Using a novel approach, we find that the constants which define our asymptotic distributions may be obtained experimentally using a profile of the Asimov likelihood contour. Our results may be immediately used to obtain the correct coverage when deriving real-world EFT constraints using the PLR as a test-statistic.

  2 citations

• Ephemeral Learning - Augmenting Triggers with Online-Trained Normalizing Flows

  Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, Benjamin Nachman, Tilman Plehn, David Shih, Ramon Winterhalder

  SciPost Phys. 13, 087 (2022) · published 7 October 2022 | Toggle abstract · pdf

  The large data rates at the LHC require an online trigger system to select relevant collisions. Rather than compressing individual events, we propose to compress an entire data set at once. We use a normalizing flow as a deep generative model to learn the probability density of the data online. The events are then represented by the generative neural network and can be inspected offline for anomalies or used for other analysis purposes. We demonstrate our new approach for a toy model and a correlation-enhanced bump hunt.

  12 citations

• Codebase release 1.0 for BlockGen

  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.

  3 citations

• Many-gluon tree amplitudes on modern GPUs: A case study for novel event generators

  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.

  10 citations