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We review the status of the neutrino oscillation physics (as of June 2003), with a particular emphasis on the present knowledge of the neutrino mass-mixing parameters in a three generation approach. We consider first the nu_mu-->nu_tau…

High Energy Physics - Phenomenology · Physics 2009-11-10 G. L. Fogli , E. Lisi , A. Marrone , D. Montanino , A. Palazzo , A. M. Rotunno

We assume that the Pauli exclusion principle is violated for neutrinos, and thus, neutrinos obey at least partly the Bose-Einstein statistics. The parameter sin^2 chi is introduced that characterizes the bosonic (symmetric) fraction of the…

High Energy Physics - Phenomenology · Physics 2008-11-26 A. S. Barabash , A. D. Dolgov , R. Dvornicky , F. Simkovic , A. Yu. Smirnov

We revisit our previous work [Phys. Rev. D 95, 096014 (2017)] where neutrino oscillation and nonoscillation data were analyzed in the standard framework with three neutrino families, in order to constrain their absolute masses and to probe…

High Energy Physics - Phenomenology · Physics 2020-07-01 Francesco Capozzi , Eleonora Di Valentino , Eligio Lisi , Antonio Marrone , Alessandro Melchiorri , Antonio Palazzo

In this paper we introduce a new classification algorithm called Optimization of Distributions Differences (ODD). The algorithm aims to find a transformation from the feature space to a new space where the instances in the same class are as…

Machine Learning · Computer Science 2017-03-06 Mohammad Reza Bonyadi , Quang M. Tieng , David C. Reutens

In this note we describe how to complement the neutrino evolution matrix calculated at a given energy and trajectory with additional information which allows to reliably extrapolate it to nearby energies or trajectories without repeating…

High Energy Physics - Phenomenology · Physics 2023-11-09 Michele Maltoni

We propose and analyze algorithms for distributionally robust optimization of convex losses with conditional value at risk (CVaR) and $\chi^2$ divergence uncertainty sets. We prove that our algorithms require a number of gradient…

Optimization and Control · Mathematics 2020-12-14 Daniel Levy , Yair Carmon , John C. Duchi , Aaron Sidford

Population-based metaheuristic algorithms are powerful tools in the design of neutron scattering instruments and the use of these types of algorithms for this purpose is becoming more and more commonplace. Today there exists a wide range of…

Computational Physics · Physics 2019-08-21 D. D. DiJulio , H. Björgvinsdóttir , C. Zendler , P. M. Bentley

The neutrino oscillation experiments increasingly point towards a mixing pattern that can be parametrised with two near maximal and one small mixing angle. We investigate whether such a mixing pattern can be generated as a fixed point of…

High Energy Physics - Phenomenology · Physics 2007-05-23 Gautam Dutta

We examine the prospects for the resonance spin flavour precession as a solution to the solar neutrino problem. We study seven different realistic solar magnetic field profiles and, by numerically integrating the evolution equations,…

High Energy Physics - Phenomenology · Physics 2008-11-26 J. Pulido , E. Kh. Akhmedov

We discuss the accuracy of the usual procedure for neutrino energy reconstruction which is based on the quasielastic kinematics. Our results are described in terms of a probability distribution for a real neutrino energy value. Several…

High Energy Physics - Phenomenology · Physics 2013-05-30 M. Martini , M. Ericson , G. Chanfray

We propose an adaptive refinement algorithm to solve total variation regularized measure optimization problems. The method iteratively constructs dyadic partitions of the unit cube based on i) the resolution of discretized dual problems and…

Optimization and Control · Mathematics 2023-01-19 Axel Flinth , Frédéric de Gournay , Pierre Weiss

We study in detail the threshold energy dependence of the seasonal variation effect in the energy integrated solar neutrino signal of the Super-Kamiokande detector in the case of the $\nu_{e}\leftrightarrow \nu_{\mu,\tau}$ vacuum…

High Energy Physics - Phenomenology · Physics 2009-10-31 M. Maris , S. T. Petcov

A generalized phenomenological (3 + 2 + 1)-model with three active and three sterile neutrinos is considered for the calculation of the neutrino oscillation characteristics at normal mass hierarchy of active neutrinos and significant…

High Energy Physics - Phenomenology · Physics 2016-12-28 V. V. Khruschov , S. V. Fomichev , O. A. Titov

Differential private optimization for nonconvex smooth objective is considered. In the previous work, the best known utility bound is $\widetilde O(\sqrt{d}/(n\varepsilon_\mathrm{DP}))$ in terms of the squared full gradient norm, which is…

Machine Learning · Computer Science 2023-06-06 Tomoya Murata , Taiji Suzuki

Linear combinations of chi square random variables occur in a wide range of fields. Unfortunately, a closed, analytic expression for the pdf is not yet known. As a first result of this work, an explicit analytic expression for the density…

Probability · Mathematics 2013-11-28 Johannes Bausch

We present the reach of the proposed INO-ICAL in measuring the atmospheric-neutrino-oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ using full event-by-event reconstruction for the first time. We also study the fluctuations in…

High Energy Physics - Experiment · Physics 2019-04-09 Karaparambil Rajan Rebin , Jim Libby , D. Indumathi , Lakshmi S. Mohan

Classical and new numerical schemes are generated using evolutionary computing. Differential Evolution is used to find the coefficients of finite difference approximations of function derivatives, and of single and multi-step integration…

Neural and Evolutionary Computing · Computer Science 2014-01-02 C. D. Erdbrink , V. V. Krzhizhanovskaya , P. M. A. Sloot

A global analysis of the data from all the solar neutrino experiments combined with the recent KamLAND data is presented. A formula frequently used in the literature gives survival probability for three active solar neutrino flavors in…

High Energy Physics - Phenomenology · Physics 2008-11-26 A. B. Balantekin , H. Yuksel

In this notes we describe an algorithm for non-linear fitting which incorporates some of the features of linear least squares into a general minimum $\chi^2$ fit and provide a pure Python implementation of the algorithm. It consists of the…

Numerical Analysis · Computer Science 2012-02-08 Massimo Di Pierro

We study three wave function optimization methods based on energy minimization in a variational Monte Carlo framework: the Newton, linear and perturbative methods. In the Newton method, the parameter variations are calculated from the…

Chemical Physics · Physics 2015-06-26 Julien Toulouse , C. J. Umrigar
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