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I provide an alternative way of seeing quantum computation. First, I describe an idealized classical problem solving machine that, thanks to a many body interaction, reversibly and nondeterministically produces the solution of the problem…

Quantum Physics · Physics 2007-10-10 Giuseppe Castagnoli

Quantum entanglement plays a key role in quantum computation and quantum information processing. It is of great significance to find efficient and experimentally friend separability criteria to detect entanglement. In this paper, we firstly…

Quantum Physics · Physics 2024-05-09 Yiding Wang , Tinggui Zhang , Xiaofen Huang , Shao-Ming Fei

We propose to solve polynomial hyperbolic partial differential equations (PDEs) with convex optimization. This approach is based on a very weak notion of solution of the nonlinear equation, namely the measure-valued (mv) solution,…

Analysis of PDEs · Mathematics 2018-07-09 Swann Marx , Tillmann Weisser , Didier Henrion , Jean Lasserre

This paper presents a comprehensive exploration of semi-definite programming (SDP) techniques within the context of quantum information. It examines the mathematical foundations of convex optimization, duality, and SDP formulations,…

Quantum Physics · Physics 2024-04-18 Piotr Mironowicz

We give two quantum algorithms for solving semidefinite programs (SDPs) providing quantum speed-ups. We consider SDP instances with $m$ constraint matrices, each of dimension $n$, rank at most $r$, and sparsity $s$. The first algorithm…

Tensor networks represent the state-of-the-art in computational methods across many disciplines, including the classical simulation of quantum many-body systems and quantum circuits. Several applications of current interest give rise to…

Quantum Physics · Physics 2021-03-17 Johnnie Gray , Stefanos Kourtis

This work proposes a model-reduction approach for the material point method on nonlinear manifolds. Our technique approximates the $\textit{kinematics}$ by approximating the deformation map using an implicit neural representation that…

Machine Learning · Computer Science 2023-02-13 Peter Yichen Chen , Maurizio M. Chiaramonte , Eitan Grinspun , Kevin Carlberg

Multipartite entanglement plays an essential role in both quantum information science and many-body physics. Due to the exponentially large dimension and complex geometric structure of the state space, the detection of entanglement in…

Quantum Physics · Physics 2023-02-10 Zhenhuan Liu , Yifan Tang , Hao Dai , Pengyu Liu , Shu Chen , Xiongfeng Ma

Set-membership estimation is usually formulated in the context of set-valued calculus and no probabilistic calculations are necessary. In this paper, we show that set-membership estimation can be equivalently formulated in the probabilistic…

Optimization and Control · Mathematics 2016-04-13 Alessio Benavoli , Dario Piga

In this work, we propose a new local optimization method to solve a class of nonconvex semidefinite programming (SDP) problems. The basic idea is to approximate the feasible set of the nonconvex SDP problem by inner positive semidefinite…

Optimization and Control · Mathematics 2012-02-27 Quoc Tran Dinh , Wim Michiels , Moritz Diehl

The geometric measure of entanglement is a widely used entanglement measure for quantum pure states. The key problem of computation of the geometric measure is to calculate the entanglement eigenvalue, which is equivalent to computing the…

Optimization and Control · Mathematics 2019-01-04 Mengshi Zhang , Xinzhen Zhang , Guyan Ni

Mixed state entanglement measures can act as a versatile probes of many-body systems. However, they are generally hard to compute, often relying on tricky optimizations. One measure that is straightforward to compute is the logarithmic…

Quantum Physics · Physics 2018-09-07 Johnnie Gray

We describe several algorithms for matrix completion and matrix approximation when only some of its entries are known. The approximation constraint can be any whose approximated solution is known for the full matrix. For low rank…

Numerical Analysis · Mathematics 2014-07-01 Gil Shabat , Yaniv Shmueli , Amir Averbuch

Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem.…

Strongly Correlated Electrons · Physics 2016-08-18 Dominic Bergeron , A. -M. S. Tremblay

Finite element methods usually construct basis functions and quadrature rules for multidimensional domains via tensor products of one-dimensional counterparts. While straightforward, this approach results in integration spaces larger than…

Numerical Analysis · Mathematics 2026-01-09 Tomas Teijeiro , Pouria Behnoudfar , Jamie M. Taylor , David Pardo , Victor M. Calo

Any given density matrix can be represented as an infinite number of ensembles of pure states. This leads to the natural question of how to uniquely select one out of the many, apparently equally suitable, possibilities. Following Jaynes'…

Quantum Physics · Physics 2025-04-23 Fabio Anza , James P. Crutchfield

The Finite element method (FEM) has long served as the computational backbone for topology optimization (TO). However, for designing structures undergoing large deformations, conventional FEM-based TO often exhibits numerical instabilities…

Computational Engineering, Finance, and Science · Computer Science 2026-03-17 Rahul Kumar Padhy , Aaditya Chandrasekhar , Krishnan Suresh

We investigate entanglement properties at quantum phase transitions of an integrable extended Hubbard model in the momentum space representation. Two elementary subsystems are recognized: the single mode of an electron, and the pair of…

Quantum Physics · Physics 2008-10-31 Alberto Anfossi , Paolo Giorda , Arianna Montorsi

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy is piecewise linear, approximates the expected length of the…

Information Theory · Computer Science 2026-01-27 Cheuk Ting Li

$\renewcommand{\Re}{\mathbb{R}}$ We develop a general randomized technique for solving "implic it" linear programming problems, where the collection of constraints are defined implicitly by an underlying ground set of elements. In many…

Computational Geometry · Computer Science 2021-12-24 Timothy M. Chan , Sariel Har-Peled , Mitchell Jones