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Author Strege, C.; Bertone, G.; Besjes, G.J.; Caron, S.; Ruiz de Austri, R.; Strubig, A.; Trotta, R. url  doi
openurl 
  Title Profile likelihood maps of a 15-dimensional MSSM Type Journal Article
  Year 2014 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 09 Issue 9 Pages 081 - 59pp  
  Keywords Supersymmetry Phenomenology  
  Abstract We present statistically convergent profile likelihood maps obtained via global fits of a phenomenological Minimal Supersymmetric Standard Model with 15 free parameters (the MSSM-15), based on over 250M points. We derive constraints on the model parameters from direct detection limits on dark matter, the Planck relic density measurement and data from accelerator searches. We provide a detailed analysis of the rich phenomenology of this model, and determine the SUSY mass spectrum and dark matter properties that are preferred by current experimental constraints. We evaluate the impact of the measurement of the anomalous magnetic moment of the muon (g – 2) on our results, and provide an analysis of scenarios in which the lightest neutralino is a subdominant component of the dark matter. The MSSM-15 parameters are relatively weakly constrained by current data sets, with the exception of the parameters related to dark matter phenomenology (M-1, M-2, mu), which are restricted to the sub-TeV regime, mainly due to the relic density constraint. The mass of the lightest neutralino is found to be < 1.5TeV at 99% C.L., but can extend up to 3 TeV when excluding the g – 2 constraint from the analysis. Low-mass bino-like neutralinos are strongly favoured, with spin-independent scattering cross-sections extending to very small values, similar to 10(-20) pb. ATLAS SUSY null searches strongly impact on this mass range, and thus rule out a region of parameter space that is outside the reach of any current or future direct detection experiment. The best-fit point obtained after inclusion of all data corresponds to a squark mass of 2.3 TeV, a gluino mass of 2.1 TeV and a 130 GeV neutralino with a spin-independent cross-section of 2.4 x 10(-10) pb, which is within the reach of future multi-ton scale direct detection experiments and of the upcoming LHC run at increased centre-of-mass energy.  
  Address [Strege, C.; Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Imperial Ctr Inference & Cosmol, Blackett Lab, Astrophys Grp, London SW7 2AZ, England, Email: charlotte.strege09@imperial.ac.uk;  
  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:000342069700001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 1934  
Permanent link to this record
 
 
Author van Beekveld, M.; Beenakker, W.; Caron, S.; Ruiz de Austri, R. url  doi
openurl 
  Title The case for 100 GeV bino dark matter: a dedicated LHC tri-lepton search Type Journal Article
  Year 2016 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 04 Issue 4 Pages 154 - 26pp  
  Keywords Supersymmetry Phenomenology  
  Abstract Global fit studies performed in the pMSSM and the photon excess signal originating from the Galactic Center seem to suggest compressed electroweak supersymmetric spectra with a similar to 100 GeV bino-like dark matter particle. We find that these scenarios are not probed by traditional electroweak supersymmetry searches at the LHC. We propose to extend the ATLAS and CMS electroweak supersymmetry searches with an improved strategy for bino-like dark matter, focusing on chargino plus next-to-lightest neutralino production, with a subsequent decay into a tri-lepton final state. We explore the sensitivity for pMSSM scenarios with Delta m = m(NLSP) – m(LSF) similar to(5 – 50) GeV in the root s = 14 TeV run of the LHC. Counterintuitively, we find that the requirement of low missing transverse energy increases the sensitivity compared to the current ATLAS and CMS searches. With 300 fb(-1) of data we expect the LHC experiments to be able to discover these supersymmetric spectra with mass gaps down to Am 9 GeV for DM masses between 40 and 140 GeV. We stress the importance of a dedicated search strategy that targets precisely these favored pMSSM spectra.  
  Address [van Beekveld, Melissa; Beenakker, Wim; Caron, Sascha] Radboud Univ Nijmegen, Inst Math Astrophys & Particle Phys, Heyendaalseweg 135, NL-6525 ED Nijmegen, Netherlands, Email: mcbeekveld@gmail.com;  
  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:000375055200007 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 2648  
Permanent link to this record
 
 
Author Caron, S.; Kim, J.S.; Rolbiecki, K.; Ruiz de Austri, R.; Stienen, B. url  doi
openurl 
  Title The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning Type Journal Article
  Year 2017 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 77 Issue 4 Pages 257 - 25pp  
  Keywords  
  Abstract A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300,000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce theATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/.  
  Address [Caron, Sascha; Stienen, Bob] Radboud Univ Nijmegen, IMAPP, Nijmegen, Netherlands, Email: krolb@fuw.edu.pl  
  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:000400079300001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3097  
Permanent link to this record
 
 
Author Caron, S.; Casas, J.A.; Quilis, J.; Ruiz de Austri, R. url  doi
openurl 
  Title Anomaly-free dark matter with harmless direct detection constraints Type Journal Article
  Year 2018 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 12 Issue 12 Pages 126 - 24pp  
  Keywords Beyond Standard Model; Cosmology of Theories beyond the SM  
  Abstract Dark matter (DM) interacting with the SM fields via a Z-boson (Z-portal') remains one of the most attractive WIMP scenarios, both from the theoretical and the phenomenological points of view. In order to avoid the strong constraints from direct detection and dilepton production, it is highly convenient that the Z has axial coupling to DM and leptophobic couplings to the SM particles, respectively. The latter implies that the associated U(1) coincides with baryon number in the SM sector. In this paper we completely classify the possible anomaly-free leptophobic Z with minimal dark sector, including the cases where the coupling to DM is axial. The resulting scenario is very predictive and perfectly viable from the present constraints from DM detection, EW observables and LHC data (di-lepton, di-jet and mono-jet production). We analyze all these constraints, obtaining the allowed areas in the parameter space, which generically prefer mZ less than or similar to 500 GeV, apart from resonant regions. The best chances to test these viable areas come from future LHC measurements.  
  Address [Caron, S.] Radboud Univ Nijmegen, Fac Sci, Inst Math Astrophys & Particle Phys, Mailbox 79,POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: scaron@cern.ch;  
  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:000454274400004 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3856  
Permanent link to this record
 
 
Author van Beekveld, M.; Caron, S.; Ruiz de Austri, R. url  doi
openurl 
  Title The current status of fine-tuning in supersymmetry Type Journal Article
  Year 2020 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 01 Issue 1 Pages 147 - 41pp  
  Keywords Supersymmetry Phenomenology  
  Abstract In this paper, we minimize and compare two different fine-tuning measures in four high-scale supersymmetric models that are embedded in the MSSM. In addition, we determine the impact of current and future dark matter direct detection and collider experiments on the fine-tuning. We then compare the low-scale electroweak measure with the high-scale Barbieri-Giudice measure. We find that they reduce to the same value when the higgsino parameter drives the degree of fine-tuning. We also find spectra where the high-scale measure turns out to be lower than the low-scale measure. Depending on the high-scale model and fine-tuning definition, we find a minimal fine-tuning of 3-38 (corresponding to O(10-1)%) for the low-scale measure, and 63-571 (corresponding to O(1-0.1)%) for the high-scale measure. We stress that it is too early to conclude on the fate of supersymmetry, based only on the fine-tuning paradigm.  
  Address [van Beekveld, Melissa; Caron, Sascha] Radboud Univ Nijmegen, Theoret High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: mcbeekveld@gmail.com;  
  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:000512011100001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4275  
Permanent link to this record
 
 
Author Otten, S.; Rolbiecki, K.; Caron, S.; Kim, J.S.; Ruiz de Austri, R.; Tattersall, J. url  doi
openurl 
  Title DeepXS: fast approximation of MSSM electroweak cross sections at NLO Type Journal Article
  Year 2020 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 80 Issue 1 Pages 12 - 9pp  
  Keywords  
  Abstract We present a deep learning solution to the prediction of particle production cross sections over a complicated, high-dimensional parameter space. We demonstrate the applicability by providing state-of-the-art predictions for the production of charginos and neutralinos at the Large Hadron Collider (LHC) at the next-to-leading order in the phenomenological MSSM-19 and explicitly demonstrate the performance for pp ->(chi) over tilde (+)(1)(chi) over tilde (-)(1), (chi) over tilde (0)(2)(chi) over tilde (0)(2) and (chi) over tilde (0)(2)(chi) over tilde (+/-)(1) as a proof of concept which will be extended to all SUSY electroweak pairs. We obtain errors that are lower than the uncertainty from scale and parton distribution functions with mean absolute percentage errors of well below 0.5% allowing a safe inference at the next-to-leading order with inference times that improve the Monte Carlo integration procedures that have been available so far by a factor of O(10(7)) from O(min) to O(mu s) per evaluation.  
  Address [Otten, Sydney; Caron, Sascha] Radboud Univ Nijmegen, IMAPP, Nijmegen, Netherlands, Email: Sydney.Otten@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 1434-6044 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000513271500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4279  
Permanent link to this record
 
 
Author van Beekveld, M.; Caron, S.; Hendriks, L.; Jackson, P.; Leinweber, A.; Otten, S.; Patrick, R.; Ruiz de Austri, R.; Santoni, M.; White, M. url  doi
openurl 
  Title Combining outlier analysis algorithms to identify new physics at the LHC Type Journal Article
  Year 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 09 Issue 9 Pages 024 - 33pp  
  Keywords Phenomenological Models; Supersymmetry Phenomenology  
  Abstract The lack of evidence for new physics at the Large Hadron Collider so far has prompted the development of model-independent search techniques. In this study, we compare the anomaly scores of a variety of anomaly detection techniques: an isolation forest, a Gaussian mixture model, a static autoencoder, and a beta-variational autoencoder (VAE), where we define the reconstruction loss of the latter as a weighted combination of regression and classification terms. We apply these algorithms to the 4-vectors of simulated LHC data, but also investigate the performance when the non-VAE algorithms are applied to the latent space variables created by the VAE. In addition, we assess the performance when the anomaly scores of these algorithms are combined in various ways. Using supersymmetric benchmark points, we find that the logical AND combination of the anomaly scores yielded from algorithms trained in the latent space of the VAE is the most effective discriminator of all methods tested.  
  Address [van Beekveld, Melissa] Clarendon Lab, Rudolf Peierls Ctr Theoret Phys, 20 Pks Rd, Oxford OX1 3PU, England, Email: mcbeekveld@gmail.com;  
  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:000695421600003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4973  
Permanent link to this record
 
 
Author Caron, S.; Ruiz de Austri, R.; Zhang, Z.Y. url  doi
openurl 
  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 van Beekveld, M.; Beenakker, W.; Caron, S.; Kip, J.; Ruiz de Austri, R.; Zhang, Z.Y. url  doi
openurl 
  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. url  doi
openurl 
  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  
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