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Matrix factorization methods are extensively employed to understand complex data. In this paper, we introduce the cross-product penalized component analysis (XCAN), a sparse matrix factorization based on the optimization of a loss function…

Machine Learning · Statistics 2020-11-19 José Camacho , Evrim Acar , Morten A. Rasmussen , Rasmus Bro

Exotic topologically protected zero modes with parafermionic statistics (also called fractionalized Majorana modes) have been proposed to emerge in devices fabricated from a fractional quantum Hall system and a superconductor. The…

We suggest a natural split mechanism for sfermions based on $N$=2 supersymmetry (SUSY). $N$=2 SUSY protects a sfermion in an $N$=2 multiplet from gaining weight by SUSY breaking. Therefore, if partly $N$=2 SUSY is effectively obtained, a…

High Energy Physics - Phenomenology · Physics 2016-01-21 Yasuhiro Shimizu , Wen Yin

We present the Stochastic Green Function (SGF) algorithm designed for bosons on lattices. This new quantum Monte Carlo algorithm is independent of the dimension of the system, works in continuous imaginary time, and is exact (no error…

Statistical Mechanics · Physics 2008-11-03 V. G. Rousseau

In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discards a large part of training data, we show provable guarantees…

Machine Learning · Statistics 2019-01-29 Kohei Hayashi , Masaaki Imaizumi , Yuichi Yoshida

We propose a predictive model based on the $SU(3)_C\times SU(3)_L\times U(1)_X$ gauge symmetry, which is supplemented by the $D_4$ family symmetry and several auxiliary cyclic symmetries whose spontaneous breaking produces the observed SM…

High Energy Physics - Phenomenology · Physics 2022-09-02 A. E. Cárcamo Hernández , H. N. Long , M. L. Mora-Urrutia , N. H. Thao , V. V. Vien

We calculate the spatially resolved tunneling conductance of topological superconductors (TSCs) based on ferromagnetic chains, measured by means of spin-polarised scanning tunneling microscopy (SPSTM). Our analysis reveals novel signatures…

Mesoscale and Nanoscale Physics · Physics 2015-09-22 Panagiotis Kotetes , Daniel Mendler , Andreas Heimes , Gerd Schön

A compact method for amplitude calculations in theories with Dirac and Majorana effective operators is discussed. Using the renormalizable formalism of Denner et al., [1,2] for propagators, vertices and fermion (number) flow and introducing…

High Energy Physics - Phenomenology · Physics 2018-03-02 Michael Paraskevas

We present the Fortran code SDECAY, which calculates the decay widths and branching ratios of all the supersymmetric particles in the Minimal Supersymmetric Standard Model, including higher order effects. Besides the usual two-body decays…

High Energy Physics - Phenomenology · Physics 2008-11-26 M. Muhlleitner , A. Djouadi , Y. Mambrini

We place constraints on the parameter space of the minimal supergravity (SUGRA) inspired supersymmetric (SUSY) extension of the standard model (SM), i.e. the mSUGRA model, by studying the loop-level contributions of supersymmetric particles…

High Energy Physics - Phenomenology · Physics 2007-05-23 G. C. Cho , K. Hagiwara , C. Kao , R. Szalapski

CP violation, fermion masses and mixing angles including that of neutrinos are studied in an SUSY SO(10)$\times \Delta(48) \times$ U(1) model with small $tan \beta$. It is amazing that the model can provide a successful prediction on twenty…

High Energy Physics - Phenomenology · Physics 2009-10-28 K. C. Chou , Yue-Liang Wu

We discuss a simulation algorithm for dynamical fermions, which combines the multiboson technique with the Hybrid Monte Carlo algorithm. The algorithm turns out to give a substantial gain over standard methods in practical simulations and…

High Energy Physics - Lattice · Physics 2009-10-30 Roberto Frezzotti , Karl Jansen

Simulating samples from arbitrary probability distributions is a major research program of statistical computing. Recent work has shown promise in an old idea, that sampling from a discrete distribution can be accomplished by perturbing and…

Computation · Statistics 2016-04-13 Chris J. Maddison

Deep model-based architectures (DMBAs) integrating physical measurement models and learned image regularizers are widely used in parallel magnetic resonance imaging (PMRI). Traditional DMBAs for PMRI rely on pre-estimated coil sensitivity…

Image and Video Processing · Electrical Eng. & Systems 2024-06-07 Yuyang Hu , Weijie Gan , Chunwei Ying , Tongyao Wang , Cihat Eldeniz , Jiaming Liu , Yasheng Chen , Hongyu An , Ulugbek S. Kamilov

Majorana zero modes are quasiparticles that hold promise as building blocks for topological quantum computing. However, the litmus test for their detection, the observation of exotic non-abelian statistics revealed by braiding, has so far…

We present a variation of a quantum algorithm for the machine learning task of classification with graph-structured data. The algorithm implements a feature extraction strategy that is based on Gaussian boson sampling (GBS) a near term…

Quantum Physics · Physics 2026-05-13 Amanuel Anteneh , Olivier Pfister

Version 2 of 'carlomat', a program for automatic computation of the lowest order cross sections of multiparticle reactions, is described. The substantial modifications with respect to version 1 of the program include: generation of a single…

High Energy Physics - Phenomenology · Physics 2015-06-16 Karol Kolodziej

Investigation of composite Higgs models (CHMs) is of importance in contemporary particle physics. In this article, we present lattice computations of the chimera baryon masses in $Sp(4)$ gauge theory with two and three Dirac flavours of…

In the Minimal Supersymmetric Standard Model with complex parameters (cMSSM) we calculate higher order corrections to the Higgs boson sector in the Feynman-diagrammatic approach using the on-shell renormalization scheme. The application of…

High Energy Physics - Phenomenology · Physics 2011-09-13 S. Heinemeyer

We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We…

Computation · Statistics 2024-11-13 Joseph Mathews , Giri Gopalan , James Gattiker , Sean Smith , Devin Francom