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In this contribution, we discuss a total cross-section model which can be applied to both photon and purely hadronic processes. We find that the model can reproduce photo-production cross-sections, as well as extrapolations of gamma* p…

High Energy Physics - Phenomenology · Physics 2009-11-13 R. M. Godbole , A. Grau , G. Pancheri , Y. N. Srivastava

Bayesian methods have become a popular way to incorporate prior knowledge and a notion of uncertainty into machine learning models. At the same time, the complexity of modern machine learning makes it challenging to comprehend a model's…

Machine Learning · Computer Science 2021-09-09 Sarem Seitz

We present a method for symbolic calculation of Feynman amplitudes for processes involving both massless and massive fermions. With this approach fermion strings in a specific amplitude can be easily evaluated and expressed as basic Lorentz…

High Energy Physics - Phenomenology · Physics 2008-11-26 Cong-Feng Qiao

This paper is concerned with the study of the embedding circulant matrix method to simulate stationary complex-valued Gaussian sequences. The method is, in particular, shown to be well-suited to generate circularly-symmetric stationary…

Statistics Theory · Mathematics 2016-04-04 Jean-Francois Coeurjolly , Emilio Porcu

We present technical details of an analysis of pseudo-scalar data from a QCD simulation with staggered fermions. The data were obtained close to the physical point with an inverse lattice spacing of about 3 GeV, and $N_f=2+1+1$. We compare…

High Energy Physics - Lattice · Physics 2019-10-25 Maximilian Ammer , Stephan Durr

I present a numerical algorithm for direct evaluation of multiple Grassmann integrals. The approach is exact and suffers no Fermion sign problems. Memory requirements grow exponentially with the interaction range and the transverse size of…

High Energy Physics - Lattice · Physics 2009-10-31 Michael Creutz

Majorana zero modes (MZMs) promise a platform for topologically protected fermionic quantum computation. However, creating multiple MZMs and generating (directly or via measurements) the requisite transformations (e.g., braids) pose…

Quantum Physics · Physics 2022-05-06 Campbell K. McLauchlan , Benjamin Béri

We propose and analyze an approach to realize quantum computation and simulation using fermionic particles under quantum gas microscopes. Our work is inspired by a recent experimental demonstration of large-scale quantum registers, where…

Quantum Physics · Physics 2023-06-07 Xiangkai Sun , Di Luo , Soonwon Choi

We obtain a complete classification of complex-valued sequences which are both multiplicative and automatic.

Number Theory · Mathematics 2021-01-19 Jakub Konieczny , Mariusz Lemańczyk , Clemens Müllner

We derive a systematic procedure to compute Green functions for the massive Schwinger model via a perturbation expansion in the fermion mass. The known exact solution of the massless Schwinger model is used as a starting point. We compute…

High Energy Physics - Phenomenology · Physics 2009-10-28 C. Adam

The CompHEP software package allows the evaluation of cross section and decays of elementary particles with a high level of automation. Arbitrary tree levelp rocesses can be calculated starting from the set of vertices prescribed by a given…

High Energy Physics - Phenomenology · Physics 2009-11-07 A. Semenov

We provide a new kriging procedure of processes on graphs. Based on the construction of Gaussian random processes indexed by graphs, we extend to this framework the usual linear prediction method for spatial random fields, known as kriging.…

Statistics Theory · Mathematics 2014-06-26 Thibault Espinasse , Jean-Michel Loubes

This paper proposes a new methodology to perform Bayesian inference for a class of multidimensional Cox processes in which the intensity function is piecewise constant. Poisson processes with piecewise constant intensity functions are…

Methodology · Statistics 2022-11-16 Flavio B. Gonçalves , Barbara C. C. Dias

This work presents a family of parsimonious Gaussian process models which allow to build, from a finite sample, a model-based classifier in an infinite dimensional space. The proposed parsimonious models are obtained by constraining the…

Methodology · Statistics 2012-06-18 Charles Bouveyron , Stéphane Girard , Mathieu Fauvel

We present a method to approximate partition functions of quantum systems using mixed-state quantum computation. For positive semi-definite Hamiltonians, our method has expected running-time that is almost linear in $(M/(\epsilon_{\rm…

Quantum Physics · Physics 2021-03-24 Anirban N. Chowdhury , Rolando D. Somma , Yigit Subasi

The program package GoSam is presented which aims at the automated calculation of one-loop amplitudes for multi-particle processes. The amplitudes are generated in terms of Feynman diagrams and can be reduced using either D-dimensional…

High Energy Physics - Phenomenology · Physics 2015-06-03 G. Cullen , N. Greiner , G. Heinrich , G. Luisoni , P. Mastrolia , G. Ossola , T. Reiter , F. Tramontano

In this paper, we introduce a novel and general method for computing partition functions of solvable lattice models with free fermionic Boltzmann weights. The method is based on the ``permutation graph'' and the ``$F$-matrix'': the…

Mathematical Physics · Physics 2022-11-15 Chenyang Zhong

To target challenges in differentiable optimization we analyze and propose strategies for derivatives of the Mat\'ern kernel with respect to the smoothness parameter. This problem is of high interest in Gaussian processes modelling due to…

Numerical Analysis · Mathematics 2022-01-04 Oana Marin , Christopher Geoga , Michel Schanen

We accelerate the computation of spherical harmonic transforms, using what is known as the butterfly scheme. This provides a convenient alternative to the approach taken in the second paper from this series on "Fast algorithms for spherical…

Numerical Analysis · Computer Science 2015-05-14 Mark Tygert

We present the first fully variational Bayesian inference scheme for continuous Gaussian-process-modulated Poisson processes. Such point processes are used in a variety of domains, including neuroscience, geo-statistics and astronomy, but…

Machine Learning · Statistics 2015-07-29 Chris Lloyd , Tom Gunter , Michael A. Osborne , Stephen J. Roberts
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