Schaffter, T. et al, Albiol, F., & Caballero, L. (2020). Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms. JAMA Netw. Open, 3(3), e200265–15pp.
Abstract: Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.
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Vento, V. (2018). Ions, Protons, and Photons as Signatures of Monopoles. Universe, 4(11), 117–12pp.
Abstract: Magnetic monopoles have been a subject of interest since Dirac established the relationship between the existence of monopoles and charge quantization. The Dirac quantization condition bestows the monopole with a huge magnetic charge. The aim of this study was to determine whether this huge magnetic charge allows monopoles to be detected by the scattering of charged ions and protons on matter where they might be bound. We also analyze if this charge favors monopolium (monopole-antimonopole) annihilation into many photons over two photon decays.
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Gersabeck, E., & Pich, A. (2020). Tau and charm decays. C. R. Phys., 21(1), 75–92.
Abstract: A summary of recent precise results in tau and charm physics is presented. Topics include leptonic and hadronic tau decays, lepton flavour and lepton number violation, charm mixing and CP violation, leptonic and semileptonic charm decays, rare decays and spectroscopy.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2024). Search for quantum black hole production in lepton plus jet final states using proton-proton collisions at √s=13 TeV with the ATLAS detector. Phys. Rev. D, 109(3), 032010–28pp.
Abstract: A search for quantum black holes in electron + jet and muon + jet invariant mass spectra is performed with 140 fb(-1) of data collected by the ATLAS detector in proton-proton collisions at root s = 13 TeV at the Large Hadron Collider. The observed invariant mass spectrum of lepton + jet pairs is consistent with Standard Model expectations. Upper limits are set at 95% confidence level on the production cross section times branching fractions for quantum black holes decaying into a lepton and a quark in a search region with invariant mass above 2.0 TeV. The resulting quantum black hole lower mass threshold limit is 9.2 TeV in the Arkani-Hamed-Dimopoulos-Dvali model, and 6.8 TeV in the Randall-Sundrum model.
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Cervantes, D., Fioresi, R., Lledo, M. A., & Nadal, F. A. (2016). Quantum Twistors. P-Adic Num., 8(1), 2–30.
Abstract: We compute explicitly a star product on the Minkowski space whose Poisson bracket is quadratic. This star product corresponds to a deformation of the conformal spacetime, whose big cell is the Minkowski spacetime. The description of Minkowski space is made in the twistor formalism and the quantization follows by substituting the classical conformal group by a quantum group.
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BABAR Collaboration(Lees, J. P. et al), Martinez-Vidal, F., Oyanguren, A., & Villanueva-Perez, P. (2017). Evidence for CP violation in B+ -> K*(892)(+)pi(0) from a Dalitz plot analysis of B+ -> K-S(0) pi(+)pi(0) decays. Phys. Rev. D, 96(7), 072001–21pp.
Abstract: We report a Dalitz plot analysis of charmless hadronic decays of charged B mesons to the final state K-S(0)pi(1) pi(0) using the full BABAR data set of 470.9 +/- 2.8 million B (B) over bar events collected at the gamma (4S) resonance. We measure the overall branching fraction and CP asymmetry to be B(B+ -> K-0 pi(+)pi(0)) = (31.8 +/- 1.8 +/- 2.1(-0.0)(+6.0)) x 10(-6) and A(CP)(B+ -> K-0 pi(+)pi(0)) = 0.07 +/- 0.05 +/- 0.03(-0.03)(+0.02), where the uncertainties are statistical, systematic, and due to the signal model, respectively. This is the first measurement of the branching fraction for B+ -> K-0 pi(+)pi(0). We find first evidence of a CP asymmetry in B+ -> K*(892)(+) pi(0) decays: A(CP)(B+ -> K*(892)(+)pi(0)) = -0.52 +/- 0.14 +/- 0.04(-0.02)(+0.04). The significance of this asymmetry, including systematic and model uncertainties, is 3.4 standard deviations. We also measure the branching fractions and CP asymmetries for three other intermediate decay modes.
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Flores-Tlalpa, A., Lopez Castro, G., & Roig, P. (2016). Five-body leptonic decays of muon and tau lepton. J. High Energy Phys., 04(4), 185–21pp.
Abstract: We study the five-body decays u(-) -> e(-)e(+)e(-)nu u (nu) over bar (e) and tau(-) -> l(-)l'+l'-nu(tau)(nu) over bar (l) for l, l' = e, u within the Standard Model (SM) and in a general effective field theory description of the weak interactions at low energies. We compute the branching ratios and compare our results with two previous – mutually discrepan – SM calculations. By assuming a general structure for the weak currents we derive the expressions for the energy and angular distributions of the three charged leptons when the decaying lepton is polarized, which will be useful in precise tests of the weak charged current at Belle II. In these decays, leptonic T-odd correlations in triple products of spin and momenta – which may signal time reversal violation in the leptonic sector – are suppressed by the tiny neutrino masses. Therefore, a measurement of such T-violating observables would be associated to neutrinoless lepton flavor violating (LFV) decays, where this effect is not extremely suppressed. We also study the backgrounds that the SM five-lepton lepton decays constitute to searches of LFV L- -> ? l(-)l'+l'(-) decays. Searches at high values of the invariant mass of the l'(+)l'(-) pair look the most convenient way to overcome the background.
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Allanach, B. C., Martin, S. P., Robertson, D. G., & Ruiz de Austri, R. (2017). The inclusion of two-loop SUSYQCD corrections to gluino and squark pole masses in the minimal and next-to-minimal supersymmetric standard model: SOFTSUSY3.7. Comput. Phys. Commun., 219, 339–345.
Abstract: We describe an extension of the SOFTSUSY spectrum calculator to include two-loop supersymmetric QCD (SUSYQCD) corrections of order O(alpha(2)(s)) to gluino and squark pole masses, either in the minimal supersymmetric standard model (MSSM) or the next-to-minimal supersymmetric standard model (NMSSM). This document provides an overview of the program and acts as a manual for the new version of SOFTSUSY, which includes the increase in accuracy in squark and gluino pole mass predictions. Program summary Program title: SOFTSUSY Program Files doi: http://dx.doLorg/10.17632/sh77x9j7hs.1 Licensing provisions: GNU GPLv3 Programming language: C++, fortran, C Nature of problem: Calculating supersymmetric particle spectrum, mixing parameters and couplings in the MSSM or the NMSSM. The solution to the renormalization group equations must be consistent with theoretical boundary conditions on supersymmetry breaking parameters, as well as a weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Solution method: Nested fixed point iteration. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is nonphysical for some reason (for example because the electroWeak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the MSSM (R-parity conserving or violating) or the real R-parity conserving NMSSM only. Journal reference of previous version: Comput. Phys. Comm. 189 (2015) 192. Does the new version supersede the previous version?: Yes. Reasons for the new version: It is desirable to improve the accuracy of the squark and gluinos mass predictions, since they strongly affect supersymmetric particle production cross-sections at colliders. Summary of revisions: The calculation of the squark and gluino pole masses is extended to be of next-to next-to leading order in SUSYQCD, i.e. including terms up to O(g(s)(4)/(16 pi(2))(2)). Additional comments: Program obtainable from http://softsusy.hepforge.org/
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., Costa, M. J., et al. (2017). Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1. Eur. Phys. J. C, 77(7), 490–73pp.
Abstract: The reconstruction of the signal from hadrons and jets emerging from the proton-proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.
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Rocha-Moran, P., & Vicente, A. (2016). Lepton Flavor Violation in the singlet-triplet scotogenic model. J. High Energy Phys., 07(7), 078–25pp.
Abstract: We investigate lepton flavor violation (LFV) in the the singlet-triplet scotogenic model in which neutrinos acquire non-zero masses at the 1-loop level. In contrast to the most popular variant of this setup, the singlet scotogenic model, this version includes a triplet fermion as well as a triplet scalar, leading to a scenario with a richer dark matter phenomenology. Taking into account results from neutrino oscillation experiments, we explore some aspects of the LFV phenomenology of the model. In particular, we study the relative weight of the dipole operators with respect to other contributions to the LFV amplitudes and determine the most constraining observables. We show that in large portions of the parameter space, the most promising experimental perspectives are found for LFV 3-body decays and for coherent mu-e conversion in nuclei.
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