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PTOLEMY Collaboration(Betti, M. G. et al), de Salas, P. F., Gariazzo, S., & Pastor, S. (2019). A design for an electromagnetic filter for precision energy measurements at the tritium endpoint. Prog. Part. Nucl. Phys., 106, 120–131.
Abstract: We present a detailed description of the electromagnetic filter for the PTOLEMY project to directly detect the Cosmic Neutrino Background (CNB). Starting with an initial estimate for the orbital magnetic moment, the higher-order drift process of E x B is configured to balance the gradient-B drift motion of the electron in such a way as to guide the trajectory into the standing voltage potential along the mid-plane of the filter. As a function of drift distance along the length of the filter, the filter zooms in with exponentially increasing precision on the transverse velocity component of the electron kinetic energy. This yields a linear dimension for the total filter length that is exceptionally compact compared to previous techniques for electromagnetic filtering. The parallel velocity component of the electron kinetic energy oscillates in an electrostatic harmonic trap as the electron drifts along the length of the filter. An analysis of the phase-space volume conservation validates the expected behavior of the filter from the adiabatic invariance of the orbital magnetic moment and energy conservation following Liouville's theorem for Hamiltonian systems. (C) 2019 Elsevier B.V. All rights reserved.
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Begone, G., Deisenroth, M. P., Kim, J. S., Liem, S., Ruiz de Austri, R., & Welling, M. (2019). Accelerating the BSM interpretation of LHC data with machine learning. Phys. Dark Universe, 24, 100293–5pp.
Abstract: The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent scans of high-dimensional BSM theories is consequently challenging, and in practice unfeasible for very high-dimensional BSM theories. We present here a new machine learning method that accelerates the interpretation of LHC data, by learning the relationship between BSM theory parameters and data. As a proof-of-concept, we demonstrate that this technique accurately predicts natural SUSY signal events in two signal regions at the High Luminosity LHC, up to four orders of magnitude faster than standard techniques. The new approach makes it possible to rapidly and accurately reconstruct the theory parameters of complex BSM theories, should an excess in the data be discovered at the LHC.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., et al. (2019). Search for heavy charged long-lived particles in proton-proton collisions at root s=13 TeV using an ionisation measurement with the ATLAS detector. Phys. Lett. B, 788, 96–116.
Abstract: This Letter presents a search for heavy charged long-lived particles produced in proton-proton collisions at root s= 13 TeV at the LHC using a data sample corresponding to an integrated luminosity of 36.1 fb(-1) collected by the ATLAS experiment in 2015 and 2016. These particles are expected to travel with a velocity significantly below the speed of light, and therefore have a specific ionisation higher than any high-momentum Standard Model particle of unit charge. The pixel subsystem of the ATLAS detector is used in this search to measure the ionisation energy loss of all reconstructed charged particles which traverse the pixel detector. Results are interpreted assuming the pair production of R-hadrons as composite colourless states of a long-lived gluino and Standard Model partons. No significant deviation from Standard Model background expectations is observed, and lifetime-dependent upper limits on R-hadron production cross-sections and gluino masses are set, assuming the gluino always decays to two quarks and a 100 GeV stable neutralino. R-hadrons with lifetimes above 1.0 ns are excluded at the 95% confidence level, with lower limits on the gluino mass ranging between 1290 GeV and 2060 GeV. In the case of stable R-hadrons, the lower limit on the gluino mass at the 95% confidence level is 1890 GeV.
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Barenboim, G., Masud, M., Ternes, C. A., & Tortola, M. (2019). Exploring the intrinsic Lorentz-violating parameters at DUNE. Phys. Lett. B, 788, 308–315.
Abstract: Neutrinos can push our search for new physics to a whole new level. What makes them so hard to be detected, what allows them to travel humongous distances without being stopped or deflected allows to amplify Planck suppressed effects (or effects of comparable size) to a level that we can measure or bound in DUNE. In this work we analyze the sensitivity of DUNE to CPT and Lorentz-violating interactions in a framework that allows a straightforward extrapolation of the bounds obtained to any phenomenological modification of the dispersion relation of neutrinos.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., et al. (2019). Search for light resonances decaying to boosted quark pairs and produced in association with a photon or a jet in proton-proton collisions at root s=13 TeV with the ATLAS detector. Phys. Lett. B, 788, 316–335.
Abstract: This Letter presents a search for new light resonances decaying to pairs of quarks and produced in association with a high-p(T) photon or jet. The dataset consists of proton-proton collisions with an integrated luminosity of 36.1 fb(-1) at a centre-of-mass energy of root s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. Resonance candidates are identified as massive large-radius jets with substructure consistent with a particle decaying into a quark pair. The mass spectrum of the candidates is examined for local excesses above background. No evidence of a new resonance is observed in the data, which are used to exclude the production of a lepto-phobic axial-vector Z' boson. (C) 2018 The Author(s). Published by Elsevier B.V.
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