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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., et al. (2018). Measurements of the branching fractions of Lambda(+)(c) -> p pi(-)pi(+), Lambda(+)(c) -> pK(-)K(+), and Lambda(+)(c) -> p pi K-(+). J. High Energy Phys., 03(3), 043–23pp.
Abstract: The ratios of the branching fractions of the decays do Lambda(+)(c) -> , p pi(-)pi(+), Lambda(+->)(c) pK(-)K(+), and Lambda(+)(c) -> p pi K--(+) with respect to the Cabibbo-favoured Lambda(+)(c) -> pK(-)pi(+) decay are measured using proton-proton collision data collected with the LHCb experiment at a 7 TeV centre-of-mass energy and corresponding to an integrated luminosity of 1.0 fb(-1): B(Lambda(+)(c) -> p pi(-)pi(+))/B(Lambda(+)(c) -> pK(-)pi(+)) = (7.44 +/- 0.08 +/- 0.18)%. B(Lambda(+)(c) -> pK(-)K(+))/B(Lambda(+)(c) -> pK(-)pi(+) = (1.70 +/- 0.03 +/- 0.03)%, B(Lambda(+)(c) -> p pi(-)pi K-+(+))/B(Lambda(+)(c) -> pK(-)pi(+) = (0.165 +/- 0.015 +/- 0.005)%, where the uncertainties are statistical and systematic, respectively. These results are the most precise measurements of these quantities to date. When multiplied by the world average value for B(Lambda(+)(c) -> p pi(-)pi(+)), the corresponding branching fractions are B(Lambda(+)(c) -> p pi(-)pi(+) = (4.72 +/- 0.05 +/- 0.11 +/- 0.25) x 10(-3), B(Lambda(+)(c) -> pK(-)K(+)) = (1.08 +/- 0.02 +/- 0.02 +/- 0.06) x 10(-3), B(Lambda(+)(c) -> , p pi K--(+)) = (1.04 +/- 0.09 +/- 0.03 +/- 0.05) x 10(-4), where the final uncertainty is due to B(Lambda(+)(c) -> pK(-)pi(+)).
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Arbelaez, C., Carcamo Hernandez, A. E., Cepedello, R., Kovalenko, S., & Schmidt, I. (2020). Sequentially loop suppressed fermion masses from a single discrete symmetry. J. High Energy Phys., 06(6), 043–24pp.
Abstract: We propose a systematic and renormalizable sequential loop suppression mechanism to generate the hierarchy of the Standard Model fermion masses from one discrete symmetry. The discrete symmetry is sequentially softly broken in order to generate one-loop level masses for the bottom, charm, tau and muon leptons and two-loop level masses for the lightest Standard Model charged fermions. The tiny masses for the light active neutrinos are produced from radiative type-I seesaw mechanism, where the Dirac mass terms are effectively generated at two-loop level.
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T2K Collaboration(Abe, K. et al), Antonova, M., Cervera-Villanueva, A., & Novella, P. (2021). Measurements of (nu)over-bar(mu) and (nu)over-bar(mu) + nu(mu) charged-current cross-sections without detected pions or protons on water and hydrocarbon at a mean anti-neutrino energy of 0.86 GeV. Prog. Theor. Exp. Phys., 2021(4), 043C01–28pp.
Abstract: We report measurements of the flux-integrated (nu) over bar (mu) and (nu) over bar (mu) + nu(mu) charged-current cross -sections on water and hydrocarbon targets using the T2K anti-neutrino beam with a mean beam energy of 0.86 GeV. The signal is defined as the (anti -)neutrino charged-current interaction with one induced mu(+/-) and no detected charged pion or proton. These measurements are performed using a new WAGASCI module recently added to the T2K setup in combination with the INGRID Proton Module. The phase space of muons is restricted to the high-detection efficiency region, p(mu) > 400 MeV/c and theta(mu) < 30 degrees, in the laboratory frame. An absence of pions and protons in the detectable phase spaces of p(pi) > 200 MeV/c, theta(pi) < 70 degrees and p(p) > 600 MeV/c, theta(p) < 70 degrees is required. In this paper, both the <(nu)over bar>(mu), cross-sections and (nu) over bar (mu) + nu(mu), cross-sections on water and hydrocarbon targets and their ratios are provided by using the D'Agostini unfolding method. The results of the integrated (nu) over bar (mu), cross-section measurements over this phase space are sigma(H2O) = (1.082 +/- 0.068(stat.)(+0.145)(-0.128)(syst.)) x 10(-39) cm(2)/nucleon, sigma(CH) = (1.096 +/- 0.054 (stat.)(+0.132)(-0.117)(syst.)) x 10(-39) cm(2) /nucleon, and sigma(H2O)/sigma(CH) = 0.987 +/- 0.078 (stat.)(+0.093)(-0.090)(syst.). The (nu) over bar (mu), + nu(mu), cross-section is sigma(H2O) = (1.155 +/- 0.064(stat.)(+0.148)(-0.129)(syst.)) x 10(-39) cm(2)/nucleon, sigma(CH) = (1.159 +/- 0.049(stat.)(+0.129)(-0.115)(syst.)) x 10(-39) cm(2)/nucleon, and sigma(H2O)/sigma(CH) = 0.996 +/- 0.069(stat.)(+0.083)(-0.078)(syst.).
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2021). Angular analysis of the rare decay B-s(0) -> phi mu(+)mu(-). J. High Energy Phys., 11(11), 043–45pp.
Abstract: An angular analysis of the rare decay B-s(0) -> phi mu(+)mu(-) is presented, using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13TeV, corresponding to an integrated luminosity of 8.4 fb(-1). The observables describing the angular distributions of the decay B-s(0) -> phi mu(+)mu(-) are determined in regions of q(2), the square of the dimuon invariant mass. The results are consistent with Standard Model predictions.
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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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