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McCallum-style Cylindrical Algebra Decomposition (CAD) is a major improvement on the original Collins version, and has had many subsequent advances, notably for total or partial equational constraints. But it suffers from a problem with…

Symbolic Computation · Computer Science 2023-12-08 James H. Davenport , Akshar S. Nair , Gregory K. Sankaran , Ali K. Uncu

This paper presents key enhancements to our previous work~\cite{naghmouchi2024mixed} on a hybrid Benders decomposition (HBD) framework for solving mixed integer linear programs (MILPs). In our approach, the master problem is reformulated as…

Quantum Physics · Physics 2026-01-23 Anna Joliot , M. Yassine Naghmouchi , Wesley Coelho

In this paper, we propose an incremental algorithm for computing cylindrical algebraic decompositions. The algorithm consists of two parts: computing a complex cylindrical tree and refining this complex tree into a cylindrical tree in real…

Symbolic Computation · Computer Science 2012-10-23 Changbo Chen , Marc Moreno Maza

Optimization problems become fundamentally challenging as the number of variables increases. Because the volume of the search space grows exponentially, classical algorithms frequently fail to locate the global minimum of non-convex…

Quantum Physics · Physics 2026-04-23 Dominik Soós , Marc Paterno , John Stenger , Nikos Chrisochoides

In this paper, we introduce a quantum-enhanced algorithm for simulation-based optimization. Simulation-based optimization seeks to optimize an objective function that is computationally expensive to evaluate exactly, and thus, is…

Quantum Physics · Physics 2021-03-08 Julien Gacon , Christa Zoufal , Stefan Woerner

We consider cylindrical algebraic decompositions (CADs) as a tool for representing semi-algebraic subsets of $\mathbb{R}^n$. In this framework, a CAD $\mathscr{C}$ is adapted to a given set $S$ if $S$ is a union of cells of $\mathscr{C}$.…

Symbolic Computation · Computer Science 2026-01-15 Lucas Michel , Pierre Mathonet , Naïm Zénaïdi

When applying eigenvalue decomposition on the quadratic term matrix in a type of linear equally constrained quadratic programming (EQP), there exists a linear mapping to project optimal solutions between the new EQP formulation where $Q$ is…

Optimization and Control · Mathematics 2020-10-22 Shi Yu

Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the…

Machine Learning · Computer Science 2023-09-06 Lukáš Novák , Himanshu Sharma , Michael D. Shields

In the present work, a multi-scale framework for neural network enhanced methods is proposed for approximation of function and solution of partial differential equations (PDEs). By introducing the multi-scale concept, the total solution of…

Numerical Analysis · Mathematics 2022-09-07 Xiaodan Ren

Extended formulations are an important tool in polyhedral combinatorics. Many combinatorial optimization problems require an exponential number of inequalities when modeled as a linear program in the natural space of variables. However, by…

Optimization and Control · Mathematics 2024-06-07 Christoph Buchheim

Qualitative numerical planning is classical planning extended with non-negative real variables that can be increased or decreased "qualitatively", i.e., by positive indeterminate amounts. While deterministic planning with numerical…

Artificial Intelligence · Computer Science 2020-11-30 Blai Bonet , Hector Geffner

The compensated quotient-difference (Compqd) algorithm is proposed along with some applications. The main motivation is based on the fact that the standard quotient-difference (qd) algorithm can be numerically unstable. The Compqd algorithm…

Numerical Analysis · Mathematics 2017-02-20 Peibing Du , Roberto Barrio , Hao Jiang , Lizhi Cheng

CylindricalAlgebraicDecomposition.m2 is the first implementation of Cylindrical Algebraic Decomposition (CAD) in Macaulay2. CAD decomposes space into 'cells' where input polynomials are sign-invariant. This package computes an Open CAD…

Symbolic Computation · Computer Science 2025-04-01 Corin Lee , Tereso del Río , Hamid Rahkooy

The objective of this paper is to introduce and demonstrate a robust methodology for solving multi-constrained 3D topology optimization problems. The proposed methodology is a combination of the topological level-set formulation, augmented…

Computational Engineering, Finance, and Science · Computer Science 2022-03-31 Shiguang Deng , Suresh Krishnan

Quantum optimization has gained increasing attention as advances in quantum hardware enable the exploration of problem instances approaching real-world scale. Among existing approaches, variational quantum algorithms and quantum annealing…

First principles approaches have revolutionized our ability in using computers to predict, explore and design materials. A major advantage commonly associated with these approaches is that they are fully parameter free. However, numerically…

Materials Science · Physics 2025-12-25 Jan Janssen , Edgar Makarov , Tilmann Hickel , Alexander V. Shapeev , Jörg Neugebauer

Quadratic Unconstrained Binary Optimization (QUBO) is a broad class of optimization problems with many practical applications. To solve its hard instances in an exact way, known classical algorithms require exponential time and several…

Quantum Physics · Physics 2021-01-21 Gian Giacomo Guerreschi

Cylindrical algebraic decomposition (CAD) is a key tool for problems in real algebraic geometry and beyond. When using CAD there is often a choice over the variable ordering to use, with some problems infeasible in one ordering but simple…

Symbolic Computation · Computer Science 2015-02-12 Zongyan Huang , Matthew England , David Wilson , James H. Davenport , Lawrence C. Paulson

The only known constructive factorization algorithm for linear partial differential operators (LPDOs) is Beals-Kartashova (BK) factorization \cite{bk2005}. One of the most interesting features of BK-factorization: at the beginning all the…

Mathematical Physics · Physics 2007-05-23 Elena Kartashova , Scott McCallum

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is…

Quantum Physics · Physics 2017-12-12 Beili Gong , Wei Cui