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We consider the use of Quantifier Elimination (QE) technology for automated reasoning in economics. QE dates back to Tarski's work in the 1940s with software to perform it dating to the 1970s. There is a great body of work considering its…

Symbolic Computation · Computer Science 2018-05-16 Casey B. Mulligan , Russell Bradford , James H. Davenport , Matthew England , Zak Tonks

We consider the use of Quantifier Elimination (QE) technology for automated reasoning in economics. There is a great body of work considering QE applications in science and engineering but we demonstrate here that it also has use in the…

Symbolic Computation · Computer Science 2018-11-01 C. Mulligan , J. H. Davenport , M. England

We propose a new quantifier elimination algorithm for the theory of linear real arithmetic. This algorithm uses as subroutine satisfiability modulo this theory, a problem for which there are several implementations available. The quantifier…

Logic in Computer Science · Computer Science 2008-09-04 David Monniaux

This extended abstract accompanies an invited talk at CASC 2024, which surveys recent developments in Real Quantifier Elimination (QE) and Cylindrical Algebraic Decomposition (CAD). After introducing these concepts we will first consider…

Symbolic Computation · Computer Science 2024-08-27 Matthew England

Quantifier-free nonlinear arithmetic (QF_NRA) appears in many applications of satisfiability modulo theories solving (SMT). Accordingly, efficient reasoning for corresponding constraints in SMT theory solvers is highly relevant. We propose…

Logic in Computer Science · Computer Science 2018-04-30 Pascal Fontaine , Mizuhito Ogawa , Thomas Sturm , Xuan Tung Vu

Existing benchmarks for evaluating mathematical reasoning in large language models (LLMs) rely primarily on competition problems, formal proofs, or artificially challenging questions -- failing to capture the nature of mathematics…

Artificial Intelligence · Computer Science 2025-10-21 Jie Zhang , Cezara Petrui , Kristina Nikolić , Florian Tramèr

Mathematical optimization is ubiquitous in modern applications. However, in practice, we often need to use nonlinear optimization models, for which the existing optimization tools such as Cplex or Gurobi may not be directly applicable and…

Logic in Computer Science · Computer Science 2024-08-27 Jian Cao , Liyong Lin , Lele Li

We present a new angle on solving quantified linear integer arithmetic based on combining the automata-based approach, where numbers are understood as bitvectors, with ideas from (nowadays prevalent) algebraic approaches, which work…

Logic in Computer Science · Computer Science 2024-05-21 Peter Habermehl , Vojtěch Havlena , Michal Hečko , Lukáš Holík , Ondřej Lengál

This paper accompanies a new dataset of non-linear real arithmetic problems for the SMT-LIB benchmark collection. The problems come from an automated proof procedure of Gerhold--Kauers, which is well suited for solution by SMT. The problems…

Symbolic Computation · Computer Science 2023-08-22 Ali K. Uncu , James H. Davenport , Matthew England

Nonlinear programming is explicitly analyzed via a novel perspective/method and from a bottom-up manner. The philosophy is based on the recent findings on convex quadratic equation (CQE), which help clarify a geometric interpretation that…

Optimization and Control · Mathematics 2022-10-20 Li-Gang Lin , Yew-Wen Liang

The problem of checking satisfiability of linear real arithmetic (LRA) and non-linear real arithmetic (NRA) formulas has broad applications, in particular, they are at the heart of logic-related applications such as logic for artificial…

This paper builds and extends on the authors' previous work related to the algorithmic tool, Cylindrical Algebraic Decomposition (CAD), and one of its core applications, Real Quantifier Elimination (QE). These topics are at the heart of…

Symbolic Computation · Computer Science 2025-11-20 James H. Davenport , Matthew England , Scott McCallum , Ali K. Uncu

In the contexts of automated reasoning (AR) and formal verification (FV), important decision problems are effectively encoded into Satisfiability Modulo Theories (SMT). In the last decade efficient SMT solvers have been developed for…

Logic in Computer Science · Computer Science 2014-10-23 Roberto Sebastiani , Silvia Tomasi

We discuss the topic of unsatisfiability proofs in SMT, particularly with reference to quantifier free non-linear real arithmetic. We outline how the methods here do not admit trivial proofs and how past formalisation attempts are not…

Logic in Computer Science · Computer Science 2021-08-12 Erika Abraham , James H. Davenport , Matthew England , Gereon Kremer

We propose a quantum algorithm to solve systems of nonlinear algebraic equations. In the ideal case the complexity of the algorithm is linear in the number of variables $n$, which means our algorithm's complexity is less than $O(n^{3})$ of…

Quantum Physics · Physics 2019-03-15 Peng Qian , Wei-Cong Huang , Gui-Lu Long

While there has been some discussion on how Symbolic Computation could be used for AI there is little literature on applications in the other direction. However, recent results for quantifier elimination suggest that, given enough example…

Symbolic Computation · Computer Science 2018-11-01 M. England

Non-linear state estimation and some related topics, like parametric estimation, fault diagnosis, and perturbation attenuation, are tackled here via a new methodology in numerical differentiation. The corresponding basic system theoretic…

Computational Engineering, Finance, and Science · Computer Science 2008-11-06 Michel Fliess , Cédric Join , Hebertt Sira-Ramirez

We create classical (non-quantum) dynamic data structures supporting queries for recommender systems and least-squares regression that are comparable to their quantum analogues. De-quantizing such algorithms has received a flurry of…

Data Structures and Algorithms · Computer Science 2022-06-30 Nadiia Chepurko , Kenneth L. Clarkson , Lior Horesh , Honghao Lin , David P. Woodruff

Eigenvalue problems are critical to several fields of science and engineering. We present a novel unsupervised neural network for discovering eigenfunctions and eigenvalues for differential eigenvalue problems with solutions that…

Computational Physics · Physics 2020-10-13 Henry Jin , Marios Mattheakis , Pavlos Protopapas

Formal theorem-proving benchmarks enable mechanically verifiable evaluation of mathematical reasoning in large language models. However, existing benchmarks mainly focus on Olympiad-style problems and algebraic domains, leaving…

Artificial Intelligence · Computer Science 2026-05-19 Wentao Long , Yunfei Zhang , Chenyi Li , Li Zhou , Chumin Sun , Zaiwen Wen
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