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We consider the Schrodinger equation with a generalized uncertainty principle for a free particle. We then transform the problem into a second ordinary differential equation and thereby obtain the corresponding propagator. The result of…

General Physics · Physics 2016-09-01 F. Ghobakhloo , H. Hassanabadi

In this paper, we present efficient quantum algorithms that are exponentially faster than classical algorithms for solving the quantum optimal control problem. This problem involves finding the control variable that maximizes a physical…

Quantum Physics · Physics 2023-10-02 Xiantao Li , Chunhao Wang

The free-particle propagator, a key operator in various algorithms for simulating the time evolution of the Schr\"odinger equation, is studied. A multiscale approximation of this propagator is constructed, representing the semigroup…

Computational Physics · Physics 2024-12-13 Evgueni Dinvay , Yuliya Zabelina , Luca Frediani

Quantum error correction is crucial for universal fault-tolerant quantum computing. Highly accurate and low-time-complexity decoding algorithms play an indispensable role in ensuring quantum error correction works effectively. Among…

Quantum Physics · Physics 2025-07-01 Jiahan Chen , Zhengzhong Yi , Zhipeng Liang , Xuan Wang

Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences…

Quantum Physics · Physics 2009-11-13 Matthew Leifer , David Poulin

Time-dependent quantum mechanics provides an intuitive picture of particle propagation in external fields. Semiclassical methods link the classical trajectories of particles with their quantum mechanical propagation. Many analytical results…

Mesoscale and Nanoscale Physics · Physics 2008-03-07 Tobias Kramer , Eric J. Heller , Robert E. Parrott

Belief propagation is a widely used message passing method for the solution of probabilistic models on networks such as epidemic models, spin models, and Bayesian graphical models, but it suffers from the serious shortcoming that it works…

Statistical Mechanics · Physics 2021-04-27 Alec Kirkley , George T. Cantwell , M. E. J. Newman

The Schroedinger equation with an energy-dependent complex absorbing potential, associated with a scattering system, can be reduced for a special choice of the energy-dependence to a harmonic inversion problem of a discrete pseudo-time…

Chemical Physics · Physics 2009-11-07 A. Neumaier , V. A. Mandelshtam

We explore the possibility of adding complex absorbing potential at the boundaries when solving the one-dimensional real-time Schr\"odinger evolution on a grid using a quantum computer with a fully quantum algorithm described on a $n$ qubit…

Quantum Physics · Physics 2024-04-10 Mariane Mangin-Brinet , Jing Zhang , Denis Lacroix , Edgar Andres Ruiz Guzman

Near optimal decoding of good error control codes is generally a difficult task. However, for a certain type of (sufficiently) good codes an efficient decoding algorithm with near optimal performance exists. These codes are defined via a…

Information Theory · Computer Science 2007-10-30 Uli Sorger

Quantum information science strives to leverage the quantum-mechanical nature of our universe in order to achieve large improvements in certain information processing tasks. In deep-space optical communications, current receivers for the…

Quantum Physics · Physics 2020-04-16 Narayanan Rengaswamy

This paper presents a global optimization approach to quantum mechanics, which describes the most fundamental dynamics of the universe. It suggests that the wave-like behavior of (sub)atomic particles could be the critical characteristic of…

Quantum Physics · Physics 2007-05-23 Xiaofei Huang

This note provides a detailed description and derivation of the domain decomposition algorithm that appears in previous works by the author. Given a large re-estimation problem, domain decomposition provides an iterative method for…

Data Structures and Algorithms · Computer Science 2018-10-25 Brad Lackey

The representation of a Schrodinger equations as a classic Hamiltonian system allows to construct a unified perturbation theory both in classic, and in a quantum mechanics grounded on the theory of canonical transformations, and also to…

Quantum Physics · Physics 2007-05-23 A. G. Chirkov

The belief propagation (BP) based algorithm is investigated as a potential decoder for both of error correcting codes and lossy compression, which are based on non-monotonic tree-like multilayer perceptron encoders. We discuss that whether…

Information Theory · Computer Science 2015-03-18 Kazushi Mimura , Florent Cousseau , Masato Okada

It is shown that Schroedinger's equation may be derived from three postulates. The first is a kind of statistical metamorphosis of classical mechanics, a set of two relations which are obtained from the canonical equations of particle…

Quantum Physics · Physics 2011-03-09 U. Klein

The quantum mechanical time-evolution is studied for a particle under the influence of an explicitly time-dependent rotating potential. We discuss the existence of the propagator and we show that in the limit of rapid rotation it converges…

Mathematical Physics · Physics 2007-05-23 Volker Enss , Vadim Kostrykin , Robert Schrader

A propagation method for the time dependent Schr\"odinger equation was studied leading to a general scheme of solving ode type equations. Standard space discretization of time-dependent pde's usually results in system of ode's of the form…

Quantum Physics · Physics 2012-04-18 Hillel Tal-Ezer , Ronnie Kosloff , Ido Schaefer

This paper introduces a novel deep-learning-based approach for numerical simulation of a time-evolving Schr\"odinger equation inspired by stochastic mechanics and generative diffusion models. Unlike existing approaches, which exhibit…

Machine Learning · Computer Science 2024-09-19 Elena Orlova , Aleksei Ustimenko , Ruoxi Jiang , Peter Y. Lu , Rebecca Willett

Belief propagation is a fundamental message-passing algorithm for probabilistic reasoning and inference in graphical models. While it is known to be exact on trees, in most applications belief propagation is run on graphs with cycles.…

Machine Learning · Computer Science 2019-05-27 Frederic Koehler