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We present exact solutions of a class of models, which describe the parametric down conversion of photons. The Hamiltonians of this models are related to the classes of finite orthogonal polynomials. The spectra and explicit expressions for…

Mathematical Physics · Physics 2014-11-03 Maciej Horowski , Goce Chadzitaskos , Anatol Odzijewicz , Agnieszka Tereszkiewicz

In this work, a new approach has been developed to obtain numerical solution of linear Volterra type integral equations by obtaining asymptotic approximation to solutions. Using the classical Bernoulli polynomials, a set of orthonormal…

Numerical Analysis · Mathematics 2020-07-22 Udaya Pratap Singh

Quantum versions of the hydrogen atom and the harmonic oscillator are studied on non Euclidean spaces of dimension N. 2N-1 integrals, of arbitrary order, are constructed via a multi-dimensional version of the factorization method, thus…

Mathematical Physics · Physics 2015-06-23 Sarah Post , Danilo Riglioni

Variational integrators are well-suited for simulation of mechanical systems because they preserve mechanical quantities about a system such as momentum, or its change if external forcing is involved, and holonomic constraints. While they…

Optimization and Control · Mathematics 2017-09-04 Elliot Johnson , Jarvis Schultz , Todd Murphey

This paper explores the relationship between numerical integrators and optimal control algorithms. Specifically, the performance of the differential dynamical programming (DDP) algorithm is examined when a variational integrator and a newly…

Optimization and Control · Mathematics 2017-09-13 Gerardo De La Torre , Todd Murphey

We consider integrable systems that are connected with orthogonal separation of variables in complex Riemannian spaces of constant curvature. An isomorphism with the hyperbolic Gaudin magnet, previously pointed out by one of us, extends to…

High Energy Physics - Theory · Physics 2012-08-27 E. G. Kalnins , V. B. Kuznetsov , Willard Miller,

Quantum algorithms for electronic-structure simulations are actively being developed, yet many hybrid quantum-classical approaches are bottlenecked by the measurement overhead associated with large molecular Hamiltonians. Here we introduce…

Quantum Physics · Physics 2026-03-10 Benjamin Mokhtar , Noboru Inoue , Takashi Tsuchimochi

A new family of methods involving complex coefficients for the numerical integration of differential equations is presented and analyzed. They are constructed as linear combinations of symmetric-conjugate compositions obtained from a basic…

Numerical Analysis · Mathematics 2021-10-14 Fernando Casas , Alejandro Escorihuela-Tomàs

We extend the method for constructing symmetry operators of higher order for two-dimensional quantum Hamiltonians by Kalnins, Kress and Miller (2010). This expansion method expresses the integral in a finite power series in terms of lower…

Mathematical Physics · Physics 2025-05-26 Ian Marquette , Anthony Parr

We introduce a novel technique for constructing higher-order variational integrators for Hamiltonian systems of ODEs. In particular, we are concerned with generating globally smooth approximations to solutions of a Hamiltonian system. Our…

Numerical Analysis · Mathematics 2015-03-17 Melvin Leok , Tatiana Shingel

Spectral representations of the dilation and translation operators on $L^2({\mathbb R})$ are built through appropriate bases. Orthonormal wavelets and multiresolution analysis are then described in terms of rigid operator-valued functions…

Functional Analysis · Mathematics 2009-05-07 F. Gómez-Cubillo , Z. Suchanecki

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou

Computer representations of three-dimensional (3D) geometries are crucial for simulating systems and processes in engineering and science. In medicine, and more specifically, biomechanics and orthopaedics, obtaining and using 3D geometries…

Quantitative Methods · Quantitative Biology 2024-04-05 Thor E. Andreassen , Donald R. Hume , Landon D. Hamilton , Sean E. Higinbotham , Kevin B. Shelburne

This paper is a summary of the theory of discrete embeddings introduced in [5]. A discrete embedding is an algebraic procedure associating a numerical scheme to a given ordinary differential equation. Lagrangian systems possess a…

Numerical Analysis · Mathematics 2016-01-20 Loïc Bourdin , Jacky Cresson , Isabelle Greff , Pierre Inizan

In this paper, we introduce the algorithms of Orthogonal Deep Neural Networks (OrthDNNs) to connect with recent interest of spectrally regularized deep learning methods. OrthDNNs are theoretically motivated by generalization analysis of…

Machine Learning · Computer Science 2019-10-16 Kui Jia , Shuai Li , Yuxin Wen , Tongliang Liu , Dacheng Tao

Numerically efficient and stable algorithms are essential for kernel-based regularized system identification. The state of art algorithms exploit the semiseparable structure of the kernel and are based on the generator representation of the…

Numerical Analysis · Mathematics 2025-11-04 Zhuohua Shen , Junpeng Zhang , Martin S. Andersen , Tianshi Chen

We provide an algorithm to compute generators of the orthogonal group of the discriminant group associated to an integral quadratic lattice over the integers. We give a closed formula for its order.

Number Theory · Mathematics 2024-04-09 Simon Brandhorst , Davide Cesare Veniani

Integrable systems in low dimensions, constructed through the symmetry reduction method, are studied using phase portrait and variable separation techniques. In particular, invariant quantities and explicit periodic solutions are…

solv-int · Physics 2009-10-31 J. A. Calzada , M. A. del Olmo , M. A. Rodriguez

Integral transformations are used to estimate high order derivatives of various special functions. Applications are given to numerical integration, where estimates of high order derivatives of the integrand are needed to achieve bounds on…

Numerical Analysis · Mathematics 2007-06-21 David M. Bradley

We investigate numerically efficient approximations of eigenspaces associated to symmetric and general matrices. The eigenspaces are factored into a fixed number of fundamental components that can be efficiently manipulated (we consider…

Machine Learning · Computer Science 2021-09-29 Cristian Rusu , Lorenzo Rosasco