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As quantum processors grow in scale and reliability, the need for efficient quantum gate decomposition of circuits to a set of specific available gates, becomes ever more critical. The decomposition of a particular algorithm into a sequence…

Quantum Physics · Physics 2025-01-30 Jonathan Nemirovsky , Maya Chuchem , Yotam Shapira

The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious…

Materials Science · Physics 2016-02-12 Venkat Kapil , Joost VandeVondele , Michele Ceriotti

We present a novel strategy to strongly reduce the severity of the sign problem, using line integrals along paths of changing imaginary action. Highly oscillating regions along these paths cancel out, decreasing their contributions. As a…

High Energy Physics - Lattice · Physics 2023-10-18 Rasmus N. Larsen

Monte Carlo integration approximates an integral of a black-box function by taking the average of many evaluations (i.e., samples) of the function (integrand). For $N$ queries of the integrand, Monte Carlo integration achieves the…

Quantum Physics · Physics 2020-04-27 N. H. Shimada , Toshiya Hachisuka

Pricing exotic multi-asset path-dependent options requires extensive Monte Carlo simulations. In the recent years the interest to the Quasi-monte Carlo technique has been renewed and several results have been proposed in order to improve…

Probability · Mathematics 2007-11-01 Piergiacomo Sabino

For a long time, people have been focusing on how to extract more information, such as off-diagonal observables, from the quantum Monte Carlo (QMC) simulation of the partition function, but there have been numerous difficulties, and many of…

Strongly Correlated Electrons · Physics 2026-03-13 Zhiyan Wang , Zhe Wang , Bin-Bin Mao , Zheng Yan

Monte Carlo integration is a commonly used technique to compute intractable integrals and is typically thought to perform poorly for very high-dimensional integrals. To show that this is not always the case, we examine Monte Carlo…

Methodology · Statistics 2023-05-26 Yanbo Tang

Damped mechanical systems with various forms of damping are quantized using the path integral formalism. In particular, we obtain the path integral kernel for the linearly damped harmonic oscillator and a particle in a uniform gravitational…

Quantum Physics · Physics 2012-09-20 Dharmesh Jain , A. Das , Sayan Kar

There is a significant expansion in both volume and range of applications along with the concomitant increase in the variety of data sources. These ever-expanding trends have highlighted the necessity for more versatile analysis tools that…

Numerical Analysis · Mathematics 2021-09-09 Ilya Kisil , Giuseppe G. Calvi , Kriton Konstantinidis , Yao Lei Xu , Danilo P. Mandic

In this paper, we propose a numerical method of computing an integral whose integrand is a slowly decaying oscillatory function. In the proposed method, we consider a complex analytic function in the upper-half complex plane, which is…

Numerical Analysis · Mathematics 2019-09-12 Hidenori Ogata

Warm dense matter (WDM) is an active field of research, with applications ranging from astrophysics to inertial confinement fusion. Ionization degree and continuum lowering are important quantities to understand how materials behave under…

The Fundamental Theorem of Integral Calculus links the integrand and its antiderivative via a simple first order differential equation. A numerical solution of this ode yields the antiderivative and hence the required integral. This…

General Mathematics · Mathematics 2017-04-11 N. Mohankumar , Soubhadra Sen , A. Natarajan

Describing dynamics of a quantum system coupled to a complex many-body environment is a ubiquitous problem in quantum science. General non-Markovian environments are characterized by their influence matrix~(IM) -- a multi-time tensor…

Quantum Physics · Physics 2024-08-06 Ilia A. Luchnikov , Michael Sonner , Dmitry A. Abanin

Matrices arising in scientific applications frequently admit linear low-rank approximations due to smoothness in the physical and/or temporal domain of the problem. In large-scale problems, computing an optimal low-rank approximation can be…

Numerical Analysis · Mathematics 2021-05-05 Alec Michael Dunton , Alireza Doostan

The aim of this work is to present a formulation to solve the one-dimensional Ising model using the elementary technique of mathematical induction. This formulation is physically clear and leads to the same partition function form as the…

Statistical Mechanics · Physics 2020-01-08 Wenlong Wang , Rogelio Díaz-Méndez , Raudys Capdevila

The shift in chemical equilibria due to isotope substitution is often exploited to gain insight into a wide variety of chemical and physical processes. It is a purely quantum mechanical effect, which can be computed exactly using…

Statistical Mechanics · Physics 2014-07-04 Michele Ceriotti , Thomas E. Markland

Optimization problems in disciplines such as machine learning are commonly solved with iterative methods. Gradient descent algorithms find local minima by moving along the direction of steepest descent while Newton's method takes into…

Quantum Physics · Physics 2018-08-20 Patrick Rebentrost , Maria Schuld , Leonard Wossnig , Francesco Petruccione , Seth Lloyd

In this work, we introduce an interior-point method that employs tensor decompositions to efficiently represent and manipulate the variables and constraints of semidefinite programs, targeting problems where the solutions may not be…

Optimization and Control · Mathematics 2025-09-16 Frederik Kelbel , Sergey Dolgov , Dante Kalise , Alessandra Russo

We propose a new method for the efficient approximation of a class of highly oscillatory weighted integrals where the oscillatory function depends on the frequency parameter $\omega \geq 0$, typically varying in a large interval. Our…

Numerical Analysis · Mathematics 2015-03-25 Boris Khoromskij , Alexander Veit

Accurately solving high-dimensional partial differential equations (PDEs) remains a central challenge in computational mathematics. Traditional numerical methods, while effective in low-dimensional settings or on coarse grids, often…

Numerical Analysis · Mathematics 2025-05-26 Lucas Arenstein , Martin Mikkelsen , Michael Kastoryano
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