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In this work, we investigate a model order reduction scheme for polynomial parametric systems. We begin with defining the generalized multivariate transfer functions for the system. Based on this, we aim at constructing a reduced-order…

Numerical Analysis · Mathematics 2019-04-29 Peter Benner , Pawan Goyal

We compute the beta functions for the three gauge couplings of the Standard Model in the minimal subtraction scheme to three loops. We take into account contributions from all sectors of the Standard Model. The calculation is performed…

High Energy Physics - Phenomenology · Physics 2015-06-11 Luminita N. Mihaila , Jens Salomon , Matthias Steinhauser

We outline the renormalization of the standard model to all orders of perturbation theory in a way which does not make essential use of a specific subtraction scheme but is based on the Slavnov-Taylor identity. Physical fields and…

High Energy Physics - Theory · Physics 2015-06-26 Elisabeth Kraus , Klaus Sibold

We review the Standard Model in a form conducive to formulating its possible short distance extensions. This depends on the value of the Higgs mass, the only unknown parameter of the model. We suggest methods to reproduce many of the small…

High Energy Physics - Phenomenology · Physics 2015-06-25 P. Ramond

Methods of determination of constants of the Standard Model are considered. The constants values obtained now are presented and experiments for improving some values are pointed out. A few possible generalized models are considered together…

High Energy Physics - Phenomenology · Physics 2007-05-23 V. V. Khruschov

We consider the problem of learning mixtures of generalized linear models (GLM) which arise in classification and regression problems. Typical learning approaches such as expectation maximization (EM) or variational Bayes can get stuck in…

Machine Learning · Computer Science 2016-01-14 Hanie Sedghi , Majid Janzamin , Anima Anandkumar

I briefly review the current theoretical description of Standard Model processes relevant for the LHC, and the tools that are used in the corresponding phenomenological applications. I discuss in particular the recent theoretical progress…

High Energy Physics - Phenomenology · Physics 2015-12-03 M. Grazzini

We introduce a general scheme to consistently truncate equations of motion for Green's functions. Our scheme is guaranteed to generate physical Green's functions with real excitation energies and positive spectral weights. There are free…

Strongly Correlated Electrons · Physics 2021-02-24 Francesco Catalano , Johan Nilsson

Given input-output pairs of an elliptic partial differential equation (PDE) in three dimensions, we derive the first theoretically-rigorous scheme for learning the associated Green's function $G$. By exploiting the hierarchical low-rank…

Numerical Analysis · Mathematics 2022-01-24 Nicolas Boullé , Alex Townsend

The aim of this paper is to propose a strategy to implement the Minimal Model Program in modern computer algebra systems.

Algebraic Geometry · Mathematics 2025-08-22 Vladimir Lazić

In this note we define a generalization of Hall-Littlewood symmetric functions using formal group law and give an elementary proof of the generating function formula for the generalized Hall-Littlewood symmetric functions. We also give some…

Rings and Algebras · Mathematics 2018-09-28 Hiroshi Naruse

Model selection methods are used in different scientific contexts to represent a characteristic data set in terms of a reduced number of parameters. Apparently, these methods have not found their way into the literature on multibody systems…

Robotics · Computer Science 2017-05-30 Javier Ros , Xabier Iriarte , Aitor Plaza , Vicente Mata

This paper presents a nonlinear model reduction method for systems of equations using a structured neural network. The neural network takes the form of a "three-layer" network with the first layer constrained to lie on the Grassmann…

Machine Learning · Computer Science 2020-12-21 Kayla Bollinger , Hayden Schaeffer

We present a data-driven approach to mathematically model physical systems whose governing partial differential equations are unknown, by learning their associated Green's function. The subject systems are observed by collecting…

Numerical Analysis · Mathematics 2023-03-13 Harshwardhan Praveen , Nicolas Boulle , Christopher Earls

We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2012-08-01 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

For many common height functions, it is notoriously hard to compute the essential minimum. Nevertheless there are two classical methods, one giving lower bounds and the other giving upper bounds. In this paper, we show that the two methods…

Number Theory · Mathematics 2026-03-24 José Burgos Gil , Ricardo Menares , Binggang Qu , Martín Sombra

The two-time Green function method in quantum electrodynamics of high-Z few-electron atoms is described in detail. This method provides a simple procedure for deriving formulas for the energy shift of a single level and for the energies and…

Atomic Physics · Physics 2009-11-06 V. M. Shabaev

Systems may depend on parameters which one may control, or which serve to optimise the system, or are imposed externally, or they could be uncertain. This last case is taken as the ``Leitmotiv'' for the following. A reduced order model is…

Machine Learning · Computer Science 2025-02-17 Hermann G. Matthies

Uniform $L^1$ and lower bounds are obtained for the Green's function on compact K\"ahler manifolds. Unlike in the classic theorem of Cheng-Li for Riemannian manifolds, the lower bounds do not depend directly on the Ricci curvature, but only…

Differential Geometry · Mathematics 2022-02-11 Bin Guo , Duong H. Phong , Jacob Sturm

In this letter, we revisit the problem of maximum likelihood estimation (MLE) of parameters of Gaussian Mixture Model (GMM) and show a new derivation for its parameters. The new derivation, unlike the classical approach employing the…

Signal Processing · Electrical Eng. & Systems 2020-01-10 Nitesh Sahu , Prabhu Babu