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We propose a modification of a recently introduced generalized translation operator, by including a $q$-exponential factor, which implies in the definition of a Hermitian deformed linear momentum operator $\hat{p}_q$, and its canonically…

Mathematical Physics · Physics 2015-06-16 Bruno G. da Costa , Ernesto P. Borges

In a series of previous articles by the author, it was shown that one could effectively give a variational formulation to non-conservative mechanical systems, as well as ones that subject to non-holonomic constraints by starting with the…

Mathematical Physics · Physics 2011-09-05 D. H. Delphenich

We prove that every completely monotone function defined on a right-unbounded open interval admits a Newton series expansion at every point of that interval. This result can be viewed as an analog of Bernstein's little theorem for…

Classical Analysis and ODEs · Mathematics 2025-10-14 Thomas Lamby , Jean-Luc Marichal , Naïm Zenaïdi

In this paper we prove Implicit Function Theorems (IFT) for algebraic varieties defined by regular quadratic equations and, more generally, regular NTQ systems over free groups. In the model theoretic language these results state the…

Group Theory · Mathematics 2016-09-07 Olga Kharlampovich , Alexei Myasnikov

Recently, the Elementary Process Theory (EPT) has been developed as a set of fundamental principles that might underlie a gravitational repulsion of matter and antimatter. This paper presents set matrix theory (SMT) as the foundation of the…

Logic · Mathematics 2014-01-16 Marcoen J. T. F. Cabbolet , Harrie C. M. de Swart

While concepts and tools from Theoretical Computer Science are regularly applied to, and significantly support, software development for discrete problems, Numerical Engineering largely employs recipes and methods whose correctness and…

Computational Complexity · Computer Science 2018-01-23 Akitoshi Kawamura , Martin Ziegler

In this paper, we discuss a gravitational theory based on the generalized gauge field. Our Lagrangian is invariant not only under local Lorentz transformation and the ordinary gauge transformation but also under a new gauge transformation.…

High Energy Physics - Theory · Physics 2012-07-03 Kouzou Nishida

The detailed fluctuation theorem implies symmetry in the generating function of entropy production probability. The integral fluctuation theorem directly follows from this symmetry and the normalization of the probability. In this paper, we…

Statistical Mechanics · Physics 2024-06-06 Zhiqiang Huang

Generalization is a central aspect of learning theory. Here, we propose a framework that explores an auxiliary task-dependent notion of generalization, and attempts to quantitatively answer the following question: given two sets of patterns…

Disordered Systems and Neural Networks · Physics 2020-01-08 Francesco Borra , Marco Cosentino Lagomarsino , Pietro Rotondo , Marco Gherardi

We employ an algebraic procedure based on quantum mechanics to propose a `quantum number theory' (QNT) as a possible extension of the `classical number theory'. We built our QNT by defining pure quantum number operators ($q$-numbers) of a…

Quantum Physics · Physics 2021-08-24 Lucas Daiha , Roberto Rivelino

Number Theoretic Transform (NTT) is an essential mathematical tool for computing polynomial multiplication in promising lattice-based cryptography. However, costly division operations and complex data dependencies make efficient and…

Hardware Architecture · Computer Science 2023-04-25 Jingyao Zhang , Mohsen Imani , Elaheh Sadredini

The need to describe abrupt changes or response of nonlinear systems to impulsive stimuli is ubiquitous in applications. Also the informal use of infinitesimal and infinite quantities is still a method used to construct idealized but…

Mathematical Physics · Physics 2024-01-17 Aleksandr Bryzgalov , Kevin Islami , Paolo Giordano

Usually such area of mathematics as differential equations acts as a consumer of results given by functional analysis. This article will give an example of the reverse interaction of these two fields of knowledge. Namely, the derivation and…

Classical Analysis and ODEs · Mathematics 2026-05-14 Alexey Gorshkov

This paper extends the concept of generalized polarization tensors (GPTs), which was previously defined for inclusions with homogeneous conductivities, to inhomogeneous conductivity inclusions. We begin by giving two slightly different but…

Analysis of PDEs · Mathematics 2013-07-31 Habib Ammari , Youjun Deng , Hyeonbae Kang , Hyundae Lee

This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical…

Optimization and Control · Mathematics 2010-09-03 T. Hoheisel , C. Kanzow , B. S. Mordukhovich , H. Phan

A Generalized Kinetic Theory was proposed in order to have the possibility to treat particles which obey a very general statistics. By adopting the same approach, we generalize here the Kinetic Theory of electrons and phonons. Equilibrium…

Mathematical Physics · Physics 2015-06-26 A. Rossani

We discuss field theories appearing as a result of applying field transformations with derivatives (differential field transformations, DFT) to a known theory. We begin with some simple examples of DFTs to see the basic properties of the…

General Relativity and Quantum Cosmology · Physics 2020-02-06 A. A. Sheykin , D. P. Solovyev , V. V. Sukhanov , S. A. Paston

Density functional theory (DFT) offers a desirable balance between quantitative accuracy and computational efficiency in practical many-electron calculations. Its central component, the exchange-correlation energy functional, has been…

Newton's standard theory of gravitation is reformulated as a {\it gauge} theory of the {\it extended} Galilei Group. The Action principle is obtained by matching the {\it gauge} technique and a suitable limiting procedure from the ADM-De…

General Relativity and Quantum Cosmology · Physics 2010-04-06 R. De Pietri , L. Lusanna , M. Pauri

Neural-net-induced Gaussian process (NNGP) regression inherits both the high expressivity of deep neural networks (deep NNs) as well as the uncertainty quantification property of Gaussian processes (GPs). We generalize the current NNGP to…

Machine Learning · Computer Science 2019-03-27 Guofei Pang , Liu Yang , George Em Karniadakis