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We consider a six-parameter family of the square integrable wave functions for the simple harmonic oscillator, which cannot be obtained by the standard separation of variables. They are given by the action of the corresponding maximal…

Quantum Physics · Physics 2012-01-04 Raquel M. Lopez , Sergei K. Suslov , Jose M. Vega-Guzman

Many combinatorial optimization problems can be mapped to finding the ground states of the corresponding Ising Hamiltonians. The physical systems that can solve optimization problems in this way, namely Ising machines, have been attracting…

Emerging Technologies · Computer Science 2017-10-16 Tianshi Wang , Jaijeet Roychowdhury

We develop an exact analytical formulation of neutrino oscillations in matter within the framework of the Standard Neutrino Model assuming 3 Dirac Neutrinos. Our Hamiltonian formulation, which includes CP violation, leads to expressions for…

High Energy Physics - Phenomenology · Physics 2016-06-14 Mikkel B. Johnson , Ernest M. Henley , Leonard S. Kisslinger

In this paper we continue investigation of the interior problem of tomography that was started in \cite{BKT2}. As is known, solving the interior problem {with prior data specified on a finite collection of intervals $I_i$} is equivalent to…

Mathematical Physics · Physics 2014-03-10 Marco Bertola , Alexander Katsevich , Alexander Tovbis

We establish sample complexity results for stochastic optimization over the integers, especially with a view to understand the complexity with respect to the corresponding continuous optimization problem. We show that integer optimization…

Machine Learning · Computer Science 2026-05-11 Hongyu Cheng , Yinghao Zheng , Marco Molinaro , Amitabh Basu

We study the behaviour of fractional Sobolev spaces $H^s(\Omega_\varepsilon)$ with $s\in(0,1/2)$ defined on ``thin films'' $\Omega_\varepsilon=\omega\times (0,\varepsilon)$ in $\mathbb R^d$, and prove that they tend to the space…

Analysis of PDEs · Mathematics 2026-03-18 Andrea Braides , Andrea Pinamonti , Margherita Solci

We study the recovery of multivariate functions from reproducing kernel Hilbert spaces in the uniform norm. Our main interest is to obtain preasymptotic estimates for the corresponding sampling numbers. We obtain results in terms of the…

Numerical Analysis · Mathematics 2024-10-29 Kateryna Pozharska , Tino Ullrich

We consider $\mathbb{L}_2$-approximation of elements of a Hermite space of analytic functions over $\mathbb{R}^s$. The Hermite space is a weighted reproducing kernel Hilbert space of real valued functions for which the Hermite coefficients…

Numerical Analysis · Mathematics 2015-10-09 Christian Irrgeher , Peter Kritzer , Friedrich Pillichshammer , Henryk Wozniakowski

We study d-variate approximation problems in the average case setting with respect to a zero-mean Gaussian measure. Our interest is focused on measures having a structure of non-homogeneous linear tensor product, where covariance kernel is…

Probability · Mathematics 2012-12-04 M. A. Lifshits , A. Papageorgiou , H. Woźniakowski

We investigate the numerical approximation of integrals over $\mathbb{R}^d$ equipped with the standard Gaussian measure $\gamma$ for integrands belonging to the Gaussian-weighted Sobolev spaces $W^\alpha_p(\mathbb{R}^d, \gamma)$ of mixed…

Numerical Analysis · Mathematics 2023-06-21 Dinh Dũng , Van Kien Nguyen

In this paper, we study bounds of expected $L_2-$discrepancy to give mean square error of uniform integration approximation for functions in Sobolev space $\mathcal{H}^{\mathbf{1}}(K)$, where $\mathcal{H}$ is a reproducing Hilbert space…

Numerical Analysis · Mathematics 2021-10-05 Jun Xian , Xiaoda Xu

We consider optimization problems in the fractional order Sobolev spaces $H^s(\Omega)$, $s\in (0,1)$, with sparsity promoting objective functionals containing $L^p$-pseudonorms, $p\in (0,1)$. Existence of solutions is proven. By means of a…

Optimization and Control · Mathematics 2023-06-30 Harbir Antil , Daniel Wachsmuth

A regularization algorithm using inexact function values and inexact derivatives is proposed and its evaluation complexity analyzed. This algorithm is applicable to unconstrained problems and to problems with inexpensive constraints (that…

Optimization and Control · Mathematics 2019-04-22 S. Bellavia , G. Gurioli , B. Morini , Ph. L. Toint

We give a sufficient (and, in the case of a compact domain, a necessary) condition for the embedding of Sobolev space of functions with integrable gradient into Besov-Orlicz spaces to be bounded. The condition has a form of a simple…

Functional Analysis · Mathematics 2021-10-26 Aleksander Pawlewicz , Michał Wojciechowski

Inspired by Solomonoffs theory of inductive inference, we propose a prior based on circuit complexity. There are several advantages to this approach. First, it relies on a complexity measure that does not depend on the choice of UTM. There…

Machine Learning · Computer Science 2023-06-27 Cole Wyeth , Carl Sturtivant

This paper establishes isomorphisms for the Laplace operator in weighted Sobolev spaces (WSS). These spaces are similar to standard Sobolev spaces, but they are endowed with weights prescribing functions growth or decay at infinity.…

Analysis of PDEs · Mathematics 2013-02-19 Vuk Milisic , Ulrich Razafison

In this paper, we present some results on information, complexity and entropy as defined below and we discuss their relations with the Kolmogorov-Sinai entropy which is the most important invariant of a dynamical system. These results have…

Dynamical Systems · Mathematics 2019-08-17 Vieri Benci , Claudio Bonanno , Stefano Galatolo , Giulia Menconi , Federico Ponchio

For one-dimensional interval and integrable weight function $w$ we define via completion a weighted Sobolev space $H^{m,p}_{\mu_w}$ of arbitrary integer order $m$. The weights in consideration may suffer strong degeneration so that, in…

Functional Analysis · Mathematics 2019-06-03 Karol Bołbotowski

Learning rates for least-squares regression are typically expressed in terms of $L_2$-norms. In this paper we extend these rates to norms stronger than the $L_2$-norm without requiring the regression function to be contained in the…

Machine Learning · Statistics 2020-10-27 Simon Fischer , Ingo Steinwart

The membership problem asks to maintain a set $S\subseteq[u]$, supporting insertions and membership queries, i.e., testing if a given element is in the set. A data structure that computes exact answers is called a dictionary. When a (small)…

Data Structures and Algorithms · Computer Science 2020-04-28 Mingmou Liu , Yitong Yin , Huacheng Yu
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