Caron, S., Casas, J. A., Quilis, J., & Ruiz de Austri, R. (2018). Anomaly-free dark matter with harmless direct detection constraints. J. High Energy Phys., 12(12), 126–24pp.
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.
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Otten, S., Caron, S., de Swart, W., van Beekveld, M., Hendriks, L., van Leeuwen, C., et al. (2021). Event generation and statistical sampling for physics with deep generative models and a density information buffer. Nat. Commun., 12(1), 2985–16pp.
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.
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Aarrestad, T. et al, Mamuzic, J., & Ruiz de Austri, R. (2022). Benchmark data and model independent event classification for the large hadron collider. SciPost Phys., 12(1), 043–57pp.
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.
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Ruiz de Austri, R., & Perez de los Heros, C. (2013). Impact of nucleon matrix element uncertainties on the interpretation of direct and indirect dark matter search results. J. Cosmol. Astropart. Phys., 11(11), 049–19pp.
Abstract: We study in detail the impact of the current uncertainty in nucleon matrix elements on the sensitivity of direct and indirect experimental techniques for dark matter detection. We perform two scans in the framework of the cMSSM: one using recent values of the pion-sigma term obtained from Lattice QCD, and the other using values derived from experimental measurements. The two choices correspond to extreme values quoted in the literature and reflect the current tension between different ways of obtaining information about the structure of the nucleon. All other inputs in the scans, astrophysical and from particle physics, are kept unchanged. We use two experiments, XENON100 and IceCube, as benchmark cases to illustrate our case. We find that the interpretation of dark matter search results from direct detection experiments is more sensitive to the choice of the central values of the hadronic inputs than the results of indirect search experiments. The allowed regions of cMSSM parameter space after including XENON100 constrains strongly differ depending on the assumptions on the hadronic matrix elements used. On the other hand, the constraining potential of IceCube is almost independent of the choice of these values.
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Ghosh, P., Lopez-Fogliani, D. E., Mitsou, V. A., Muñoz, C., & Ruiz de Austri, R. (2014). Probing the μnu SSM with light scalars, pseudoscalars and neutralinos from the decay of a SM-like Higgs boson at the LHC. J. High Energy Phys., 11(11), 102–57pp.
Abstract: The “mu from nu” supersymmetric standard model (mu nu SSM) can accommodate the newly discovered Higgs-like scalar boson with a mass around 125GeV. This model provides a solution to the mu-problem and simultaneously reproduces correct neutrino physics by the simple use of right-handed neutrino superfields. These new superfields together with the introduced R-parity violation can produce novel and characteristic signatures of the μnu SSM at the LHC. We explore the signatures produced through two-body Higgs decays into the new states, provided that these states lie below in the mass spectrum. For example, a pair produced light neutralinos depending on the associated decay length can give rise to displaced multi-leptons/taus/jets/photons with small/moderate missing transverse energy. In the same spirit, a Higgs-like scalar decaying to a pair of scalars/pseudoscalars can produce final states with prompt multi-leptons/taus/jets/photons.
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