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Author Desai, N.; Domingo, F.; Kim, J.S.; Ruiz de Austri, R.; Rolbiecki, K.; Sonawane, M.; Wang, Z.S.
Title Constraining electroweak and strongly charged long-lived particles with CheckMATE Type Journal Article
Year 2021 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 81 Issue 11 Pages 968 - 19pp
Keywords
Abstract Long-lived particles have become a new frontier in the exploration of physics beyond the Standard Model. In this paper, we present the implementation of four types of long-lived particle searches, viz. displaced leptons, disappearing track, displaced vertex with either muons or with missing transverse energy, and heavy charged tracks. These four categories cover the signatures of a large range of physics models. We illustrate their potential for exclusion and discuss their mutual overlaps in mass-lifetime space for two simple phenomenological models involving either a U(1)-charged or a coloured scalar.
Address [Desai, Nishita] Tata Inst Fundamental Res, Dept Theoret Phys, Mumbai 400005, Maharashtra, India, Email: nishita.desai@tifr.res.in;
Corporate Author Thesis
Publisher (down) Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:000714374500002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5015
Permanent link to this record
 
 
Author Balazs, C. et al; Mamuzic, J.; Ruiz de Austri, R.
Title A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications Type Journal Article
Year 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 05 Issue 5 Pages 108 - 46pp
Keywords Phenomenology of Field Theories in Higher Dimensions; Supersymmetry Phenomenology
Abstract Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.
Address [Balazs, Csaba] Monash Univ, Sch Phys & Astron, Melbourne, Vic 3800, Australia, Email: bstienen@science.ru.nl;
Corporate Author Thesis
Publisher (down) Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1029-8479 ISBN Medium
Area Expedition Conference
Notes WOS:000762408900002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5149
Permanent link to this record
 
 
Author MoEDAL Collaboration (Acharya, B. et al); Musumeci,E.; Mitsou, V.A.; Papavassiliou, J.; Ruiz de Austri, R.; Santra, A.; Vento, V.; Vives, O.
Title Search for highly-ionizing particles in pp collisions at the LHC's Run-1 using the prototype MoEDAL detector Type Journal Article
Year 2022 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C
Volume 82 Issue 8 Pages 694 - 16pp
Keywords
Abstract A search for highly electrically charged objects (HECOs) and magnetic monopoles is presented using 2.2 fb(-1) of p – p collision data taken at a centre of mass energy (E-CM) of 8 TeV by the MoEDAL detector during LHC's Run-1. The data were collected using MoEDAL's prototype Nuclear Track Detectord array and the Trapping Detector array. The results are interpreted in terms of Drell-Yan pair production of stable HECO and monopole pairs with three spin hypotheses (0, 1/2 and 1). The search provides constraints on the direct production of magnetic monopoles carrying one to four Dirac magnetic charges and with mass limits ranging from 590 GeV/c(2) to 1 TeV/c(2). Additionally, mass limits are placed on HECOs with charge in the range 10e to 180e, where e is the charge of an electron, for masses between 30 GeV/c(2) and 1 TeV/c(2).
Address [Acharya, B.; Alexandre, J.; Ellis, J. R.; Fairbairn, M.; Mavromatos, N. E.; Sakellariadou, M.; Sarkar, S.] Kings Coll London, Phys Dept, Theoret Particle Phys & Cosmol Grp, London, England, Email: Laura.Patrizii@bo.infn.il;
Corporate Author Thesis
Publisher (down) Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1434-6044 ISBN Medium
Area Expedition Conference
Notes WOS:000838674800001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5326
Permanent link to this record
 
 
Author Caron, S.; Ruiz de Austri, R.; Zhang, Z.Y.
Title Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? Type Journal Article
Year 2023 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 03 Issue 3 Pages 004 - 37pp
Keywords Specific BSM Phenomenology; Supersymmetry
Abstract Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has been no clear signal for new physics and on the other hand there is a lack of a highly probable and parameter-free extension of the standard model. For these reasons, there is no simple search target so far. In this work, we try to take a new direction and ask the question: bearing in mind that we have a large number of new physics theories that go beyond the Standard Model and may contain a grain of truth, can we improve our search strategy for unknown signals by using them “in combination”? In particular, we show that a signal hypothesis based on a large, intermingled set of many different theoretical signal models can be a superior approach to find an unknown BSM signal. Applied to a recent data challenge, we show that “mixture-of-theories training” outperforms strategies that optimize signal regions with a single BSM model as well as most unsupervised strategies. Applications of this work include anomaly detection and the definition of signal regions in the search for signals of new physics.
Address [Caron, Sascha; Zhang, Zhongyi] Radboud Univ Nijmegen, High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: scaron@nikhef.nl;
Corporate Author Thesis
Publisher (down) Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1029-8479 ISBN Medium
Area Expedition Conference
Notes WOS:000943095100001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5494
Permanent link to this record
 
 
Author Jueid, A.; Kip, J.; Ruiz de Austri, R.; Skands, P.
Title The Strong Force meets the Dark Sector: a robust estimate of QCD uncertainties for anti-matter dark matter searches Type Journal Article
Year 2024 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 02 Issue 2 Pages 119 - 48pp
Keywords Cosmic Rays; Particle Nature of Dark Matter; Specific QCD Phenomenology
Abstract In dark-matter annihilation channels to hadronic final states, stable particles – such as positrons, photons, antiprotons, and antineutrinos – are produced via complex sequences of phenomena including QED/QCD radiation, hadronisation, and hadron decays. These processes are normally modelled by Monte Carlo (MC) event generators whose limited accuracy imply intrinsic QCD uncertainties on the predictions for indirect-detection experiments like Fermi-LAT, Pamela, IceCube or Ams-02. In this article, we perform a comprehensive analysis of QCD uncertainties, meaning both perturbative and nonperturbative sources of uncertainty are included – estimated via variations of MC renormalization-scale and fragmentation-function parameters, respectively – in antimatter spectra from dark-matter annihilation, based on parametric variations of the Pythia 8 event generator. After performing several retunings of light-quark fragmentation functions, we define a set of variations that span a conservative estimate of the QCD uncertainties. We estimate the effects on antimatter spectra for various annihilation channels and final-state particle species, and discuss their impact on fitted values for the dark-matter mass and thermally-averaged annihilation cross section. We find dramatic impacts which can go up to O(10%) for the annihilation cross section. We provide the spectra in tabulated form including QCD uncertainties and code snippets to perform fast dark-matter fits, in this github repository.
Address [Jueid, Adil] Inst Basic Sci IBS, Ctr Theoret Phys Universe, Particle Theory & Cosmol Grp, Daejeon 34126, South Korea, Email: adiljueid@ibs.re.kr;
Corporate Author Thesis
Publisher (down) Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1029-8479 ISBN Medium
Area Expedition Conference
Notes WOS:001165531600003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5956
Permanent link to this record
 
 
Author Aarrestad, T. et al; Mamuzic, J.; Ruiz de Austri, R.
Title Benchmark data and model independent event classification for the large hadron collider Type Journal Article
Year 2022 Publication Scipost Physics Abbreviated Journal SciPost Phys.
Volume 12 Issue 1 Pages 043 - 57pp
Keywords
Abstract We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (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 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.
Address [Aarrestad, Thea; Heinrich, Lukas A.; Jawahar, Pratik; Pierini, Maurizio; Touranakou, Mary; Wozniak, Kinga A.] European Org Nucl Res CERN, CH-1211 Geneva 23, Switzerland
Corporate Author Thesis
Publisher (down) Scipost Foundation Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2542-4653 ISBN Medium
Area Expedition Conference
Notes WOS:000807448000038 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5256
Permanent link to this record
 
 
Author van Beekveld, M.; Beenakker, W.; Caron, S.; Kip, J.; Ruiz de Austri, R.; Zhang, Z.Y.
Title Non-standard neutrino spectra from annihilating neutralino dark matter Type Journal Article
Year 2023 Publication Scipost Physics Core Abbreviated Journal SciPost Phys. Core
Volume 6 Issue 1 Pages 006 - 23pp
Keywords
Abstract Neutrino telescope experiments are rapidly becoming more competitive in indirect de-tection searches for dark matter. Neutrino signals arising from dark matter annihilations are typically assumed to originate from the hadronisation and decay of Standard Model particles. Here we showcase a supersymmetric model, the BLSSMIS, that can simulta-neously obey current experimental limits while still providing a potentially observable non-standard neutrino spectrum from dark matter annihilation.
Address [van Beekveld, Melissa] Univ Oxford, Rudolf Peierls Ctr Theoret Phys, Clarendon Lab, Parks Rd, Oxford OX1 3PU, England, Email: melissa.vanbeekveld@physics.ox.ac.uk;
Corporate Author Thesis
Publisher (down) Scipost Foundation Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes WOS:000928492200001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5480
Permanent link to this record
 
 
Author Otten, S.; Caron, S.; de Swart, W.; van Beekveld, M.; Hendriks, L.; van Leeuwen, C.; Podareanu, D.; Ruiz de Austri, R.; Verheyen, R.
Title Event generation and statistical sampling for physics with deep generative models and a density information buffer Type Journal Article
Year 2021 Publication Nature Communications Abbreviated Journal Nat. Commun.
Volume 12 Issue 1 Pages 2985 - 16pp
Keywords
Abstract Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes e(+)e(-)-> Z -> l(+)l(-) and pp -> tt<mml:mo><overbar></mml:mover> including the decay of the top quarks and a simulation of the detector response. By buffering density information of encoded Monte Carlo events given the encoder of a Variational Autoencoder we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g., for the phase space integration of matrix elements in quantum field theories. Here, the authors report buffered-density variational autoencoders for the generation of physical events. This method is computationally less expensive over other traditional methods and beyond accelerating the data generation process, it can help to steer the generation and to detect anomalies.
Address [Otten, Sydney; Caron, Sascha; de Swart, Wieske; van Beekveld, Melissa; Hendriks, Luc; Verheyen, Rob] Radboud Univ Nijmegen, Inst Math Astro & Particle Phys IMAPP, Nijmegen, Netherlands, Email: Sydney.Otten@ru.nl
Corporate Author Thesis
Publisher (down) Nature Research Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2041-1723 ISBN Medium
Area Expedition Conference
Notes WOS:000658761600003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4862
Permanent link to this record
 
 
Author MoEDAL Collaboration (Acharya, B. et al); Mitsou, V.A.; Papavassiliou, J.; Ruiz de Austri, R.; Santra, A.; Vento, V.; Vives, O.
Title Search for magnetic monopoles produced via the Schwinger mechanism Type Journal Article
Year 2022 Publication Nature Abbreviated Journal Nature
Volume 602 Issue 7895 Pages 63-67
Keywords
Abstract Electrically charged particles can be created by the decay of strong enough electric fields, a phenomenon known as the Schwinger mechanism(1). By electromagnetic duality, a sufficiently strong magnetic field would similarly produce magnetic monopoles, if they exist(2). Magnetic monopoles are hypothetical fundamental particles that are predicted by several theories beyond the standard model(3-7) but have never been experimentally detected. Searching for the existence of magnetic monopoles via the Schwinger mechanism has not yet been attempted, but it is advantageous, owing to the possibility of calculating its rate through semi-classical techniques without perturbation theory, as well as that the production of the magnetic monopoles should be enhanced by their finite size(8,9) and strong coupling to photons(2,10). Here we present a search for magnetic monopole production by the Schwinger mechanism in Pb-Pb heavy ion collisions at the Large Hadron Collider, producing the strongest known magnetic fields in the current Universe(11). It was conducted by the MoEDAL experiment, whose trapping detectors were exposed to 0.235 per nanobarn, or approximately 1.8 x 10(9), of Pb-Pb collisions with 5.02-teraelectronvolt center-of-mass energy per collision in November 2018. A superconducting quantum interference device (SQUID) magnetometer scanned the trapping detectors of MoEDAL for the presence of magnetic charge, which would induce a persistent current in the SQUID. Magnetic monopoles with integer Dirac charges of 1, 2 and 3 and masses up to 75 gigaelectronvolts per speed of light squared were excluded by the analysis at the 95% confidence level. This provides a lower mass limit for finite-size magnetic monopoles from a collider search and greatly extends previous mass bounds.
Address [Acharya, B.; Alexandre, J.; Ellis, J. R.; Fairbairn, M.; Mavromatos, N. E.; Sakellariadou, M.; Sarkar, S.] Kings Coll London, Phys Dept, Theoret Particle Phys & Cosmol Grp, London, England
Corporate Author Thesis
Publisher (down) Nature Portfolio Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0028-0836 ISBN Medium
Area Expedition Conference
Notes WOS:000750429600019 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5191
Permanent link to this record
 
 
Author Trotta, R.; Johannesson, G.; Moskalenko, I.V.; Porter, T.A.; Ruiz de Austri, R.; Strong, A.W.
Title Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis Type Journal Article
Year 2011 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.
Volume 729 Issue 2 Pages 106 - 16pp
Keywords astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical
Abstract Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.
Address [Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Astrophys Grp, Blackett Lab, London SW7 2AZ, England
Corporate Author Thesis
Publisher (down) Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-637x ISBN Medium
Area Expedition Conference
Notes ISI:000288608700029 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 541
Permanent link to this record