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We propose a new method to obtain approximate solutions for the Schr\"{o}dinger equation with an arbitrary potential that possesses bound states. This method, relying on the auxiliary field technique, allows in many cases to find analytical…

Quantum Physics · Physics 2008-06-13 B. Silvestre-Brac , C. Semay , F. Buisseret

We propose in this work a subgradient extragradient method with inertial and correction terms for solving equilibrium problems in a real Hilbert space. We obtain that the sequence generated by our proposed method converges weakly to a point…

Optimization and Control · Mathematics 2025-11-25 Chidi Elijah Nwakpa , Chinedu Izuchukwu , Chibueze CHristian Okeke , Dilber Uzun Ozsahin , Abubakar Adamu

We propose a new type of multilevel method for solving eigenvalue problems based on Newton iteration. With the proposed iteration method, solving eigenvalue problem on the finest finite element space is replaced by solving a small scale…

Numerical Analysis · Mathematics 2015-11-13 Yunhui He , Yu Li , Hehu Xie

In this paper the isogeometric Nystr\"om method is presented. It's outstanding features are: it allows the analysis of domains described by many different geometrical mapping methods in computer aided geometric design and it requires only…

Numerical Analysis · Computer Science 2015-06-15 Jürgen Zechner , Benjamin Marussig , Gernot Beer , Thomas-Peter Fries

We present an application of a nonstandard approximate method---the finite-rank approximation---to solving the time-independent Schr\"odinger equation for a bound-state problem. The method is illustrated on the example of a…

Quantum Physics · Physics 2014-09-18 Vladimir B. Belyaev , Andrej Babič

The essential difficulty of gradient-based bilevel optimization using implicit differentiation is to estimate the inverse Hessian vector product with respect to neural network parameters. This paper proposes to tackle this problem by the…

Machine Learning · Computer Science 2023-02-21 Ryuichiro Hataya , Makoto Yamada

The Nystr\"om method offers an effective way to obtain low-rank approximation of SPD matrices, and has been recently extended and analyzed to nonsymmetric matrices (leading to the generalized Nystr\"om method). It is a randomized,…

Numerical Analysis · Mathematics 2024-04-24 Alberto Bucci , Leonardo Robol

In the present paper, a Nystrom-type method for second kind Volterra integral equations is introduced and studied. The method makes use of generalized Bernstein polynomials, defined for continuous functions and based on equally spaced…

Numerical Analysis · Mathematics 2022-07-15 Luisa Fermo , Domenico Mezzanotte , Donatella Occorsio

The Nystrom method is a popular technique that uses a small number of landmark points to compute a fixed-rank approximation of large kernel matrices that arise in machine learning problems. In practice, to ensure high quality…

Machine Learning · Statistics 2019-12-04 Farhad Pourkamali-Anaraki , Stephen Becker

The Nystr\"om method is a popular choice for finding a low-rank approximation to a symmetric positive semi-definite matrix. The method can fail when applied to symmetric indefinite matrices, for which the error can be unboundedly large. In…

Numerical Analysis · Mathematics 2023-10-10 Taejun Park , Yuji Nakatsukasa

This paper is concerned with the low-rank approximation for large-scale nonsymmetric matrices. Inspired by the classical Nystrom method, which is a popular method to find the low-rank approximation for symmetric positive semidefinite…

Numerical Analysis · Mathematics 2024-10-30 Yatian Wang , Hua Xiang , Chi Zhang , Songling Zhang

A new approach in solution of simple quantum mechanical problems in deformed space with minimal length is presented. We propose the generalization of Schro\"edinger equation in momentum representation on the case of deformed Heisenberg…

Quantum Physics · Physics 2016-06-14 M. I. Samar , V. M. Tkachuk

The auxiliary field method is a powerful technique to obtain approximate closed-form energy formulas for eigenequations in quantum mechanics. Very good results can be obtained for Schr\"odinger and semirelativistic Hamiltonians with various…

Quantum Physics · Physics 2010-06-04 Claude Semay , Bernard Silvestre-Brac

A procedure is described for matching a given stationary axisymmetric perfect fluid solution to a not necessarily asymptotically flat vacuum exterior. Using data on the zero pressure surface, the procedure yields the Ernst potential of the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 I. Hauser , F. J. Ernst

By converting the rectangular basis potential V(x,y) into the form as V(r)+V(r, phi) described by the pseudo central plus noncentral potential, particular solutions of the two dimensional Schrodinger equation in plane-polar coordinates have…

Quantum Physics · Physics 2011-09-06 Metin Aktas

Recently developed simple approach for the exact/approximate solution of Schrodinger equations with constant/position-dependent mass, in which the potential is considered as in the perturbation theory, is shown to be equivalent to the one…

Quantum Physics · Physics 2007-05-23 B. Gonul , K. Koksal

Many kernel methods suffer from high time and space complexities and are thus prohibitive in big-data applications. To tackle the computational challenge, the Nystr\"om method has been extensively used to reduce time and space complexities…

Machine Learning · Computer Science 2014-04-02 Shusen Wang , Zhihua Zhang

The Lagrange mesh method is a very simple procedure to accurately solve eigenvalue problems starting from a given nonrelativistic or semirelativistic two-body Hamiltonian with local or nonlocal potential. We show in this work that it can be…

Computational Physics · Physics 2007-05-23 F. Buisseret , C. Semay

Employing the phase-space representation of second order ordinary differential equations we developed a method to find the eigenvalues and eigenfunctions of the 1-dimensional time independent Schr\"odinger equation for quantum model…

Quantum Physics · Physics 2021-08-27 Juan C. Morales , Carlos A. Arango

This paper develops a scalable new algorithm, called NysADMM, to minimize a smooth convex loss function with a convex regularizer. NysADMM accelerates the inexact Alternating Direction Method of Multipliers (ADMM) by constructing a…

Optimization and Control · Mathematics 2022-07-05 Shipu Zhao , Zachary Frangella , Madeleine Udell