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Many current and near-future applications of quantum computing utilise parametric families of quantum circuits and variational methods to find optimal values for these parameters. Solving a quantum computational problem with such…

Quantum Physics · Physics 2025-08-05 Tobias Hartung , Karl Jansen

This paper presents a distributed continuous-time optimization framework aimed at overcoming the challenges posed by time-varying cost functions and constraints in multi-agent systems, particularly those subject to disturbances. By…

Systems and Control · Electrical Eng. & Systems 2024-09-10 Zeinab Ebrahimi , Mohammad Deghat

We establish rigorous \emph{a posteriori} error bounds for a space-time finite element method of arbitrary order discretising linear wave problems in second order formulation. The method combines standard finite elements in space and…

Numerical Analysis · Mathematics 2026-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Lorenzo Mascotto , Zuodong Wang

This paper considers smooth convex optimization problems with many functional constraints. To solve this general class of problems we propose a new stochastic perturbed augmented Lagrangian method, called SGDPA, where a perturbation is…

Optimization and Control · Mathematics 2025-04-01 Nitesh Kumar Singh , Ion Necoara

Computationally intractable tasks are often encountered in physics and optimization. Such tasks often comprise a cost function to be optimized over a so-called feasible set, which is specified by a set of constraints. This may yield, in…

Quantum Physics · Physics 2023-04-25 Borja Requena , Gorka Muñoz-Gil , Maciej Lewenstein , Vedran Dunjko , Jordi Tura

Estimating spectral gaps of quantum many-body Hamiltonians is a highly challenging computational task, even under assumptions of locality and translation-invariance. Yet, the quest for rigorous gap certificates is motivated by their broad…

Quantum Physics · Physics 2026-04-15 Kshiti Sneh Rai , Ilya Kull , Patrick Emonts , Jordi Tura , Norbert Schuch , Flavio Baccari

One approach for reducing run time and improving efficiency of machine learning is to reduce the convergence rate of the optimization algorithm used. Shuffling is an algorithm technique that is widely used in machine learning, but it only…

Machine Learning · Computer Science 2023-06-29 Yuetong Xu , Baharan Mirzasoleiman

Two-step hybrid methods specially adapted to the numerical integration of perturbed oscillators are obtained. The formulation of the methods is based on a refinement of classical Taylor expansions due to Scheifele [{\em Z. Angew. Math.…

Numerical Analysis · Mathematics 2007-05-23 Hans Van de Vyver

Recently, several platforms were proposed and demonstrated a proof-of-principle for finding the global minimum of the spin Hamiltonians such as the Ising and XY models using gain-dissipative quantum and classical systems. The implementation…

Emerging Technologies · Computer Science 2018-07-03 Kirill P. Kalinin , Natalia G. Berloff

A genuine feature of projective quantum measurements is that they inevitably alter the mean energy of the observed system if the measured quantity does not commute with the Hamiltonian. Compared to the classical case, Jacobs proved that…

Statistical Mechanics · Physics 2015-06-10 Kay Brandner , Michael Bauer , Michael T. Schmid , Udo Seifert

Schrieffer-Wolff transformation is extensively used in quantum many-body physics to calculate the low energy effective Hamiltonian. It offers a perturbative method to understand the renormalization effects in the strong coupling regime of…

Strongly Correlated Electrons · Physics 2020-04-15 Rukhsan Ul Haq , Keshav Singh

This paper deals with the problem of simulating dense dispersed systems composed by large numbers of particles undergoing ballistic aggregation. The most classical approaches for dealing with such problems are represented by the so-called…

Computational Physics · Physics 2024-09-25 Pierre Degond , Giacomo Dimarco , Marina Ferreira , Sophie Hecht

The alternating least squares algorithm for CP and Tucker decomposition is dominated in cost by the tensor contractions necessary to set up the quadratic optimization subproblems. We introduce a novel family of algorithms that uses…

Numerical Analysis · Mathematics 2021-04-15 Linjian Ma , Edgar Solomonik

In this paper, we study the fundamental open question of finding the optimal high-order algorithm for solving smooth convex minimization problems. Arjevani et al. (2019) established the lower bound $\Omega\left(\epsilon^{-2/(3p+1)}\right)$…

Optimization and Control · Mathematics 2022-05-20 Dmitry Kovalev , Alexander Gasnikov

In this paper, we study optimization methods consisting of iteratively minimizing surrogates of an objective function. By proposing several algorithmic variants and simple convergence analyses, we make two main contributions. First, we…

Machine Learning · Statistics 2013-05-15 Julien Mairal

We develop a Liouville perturbation theory for weakly driven and weakly open quantum systems in situations when the unperturbed system has a number of conservations laws. If the perturbation violates the conservation laws, it drives the…

Strongly Correlated Electrons · Physics 2018-01-24 Zala Lenarčič , Florian Lange , Achim Rosch

This work presents a novel algorithm for impulsive optimal control of linear time-varying systems with the inclusion of input magnitude constraints. Impulsive optimal control problems, where the optimal input solution is a sum of delta…

Optimization and Control · Mathematics 2026-03-17 Ethan Foss , Simone D'Amico

In this study, a variety of methods are tested and compared for the numerical solution of the Schr\"odinger equation for few-body systems with explicitely time-dependent Hamiltonians, with the aim to find the optimal one. The configuration…

Quantum Physics · Physics 2013-02-01 Jonas C. Cremon

The gathering over meeting nodes problem requires the robots to gather at one of the pre-defined meeting nodes. This paper investigates the problem with respect to the objective function that minimizes the total number of moves made by all…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-16 Subhash Bhagat , Abhinav Chakraborty , Bibhuti Das , Krishnendu Mukhopadhyaya

We compute bulk properties of Heisenberg spin-1/2 ladders using Rayleigh-Schr\"odinger perturbation theory in the rung and plaquette bases. We formulate a method to extract high-order perturbative coefficients in the bulk limit from…

Strongly Correlated Electrons · Physics 2016-08-31 J. Piekarewicz , J. R. Shepard
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