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Open Non-uniform Cylindrical Algebraic Decompositions

Published: 24 June 2015 Publication History

Abstract

This paper introduces the notion of an Open Non-uniform Cylindrical Algebraic Decomposition (NuCAD), and presents an efficient model-based algorithm for constructing an Open NuCAD from an input formula. Using a limited experimental implementation of the algorithm, we demonstrate the effectiveness of the approach. NuCAD generalizes Cylindrical Algebraic Decomposition (CAD) as defined by Collins in his seminal work from the early 1970s, and extended in concepts like Hong's partial CAD. A NuCAD, like a CAD, is a decomposition of Rn into cylindrical cells. But unlike a CAD, the cells in a NuCAD need not be arranged cylindrically. It is in this sense that NuCADs are not uniformly cylindrical. However, NuCADs, like CADs, carry a tree-like structure that relates different cells. It is a very different tree but, as with the CAD tree structure, it allows some operations to be performed efficiently, for example locating the containing cell for an arbitrary input point.

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Cited By

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  • (2024)On Projective Delineability2024 26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)10.1109/SYNASC65383.2024.00015(9-16)Online publication date: 16-Sep-2024
  • (2024)Recent Developments in Real Quantifier Elimination and Cylindrical Algebraic Decomposition (Extended Abstract of Invited Talk)Computer Algebra in Scientific Computing10.1007/978-3-031-69070-9_1(1-10)Online publication date: 1-Sep-2024
  • (2022)The DEWCAD projectACM Communications in Computer Algebra10.1145/3511528.351153855:3(107-111)Online publication date: 12-Jan-2022
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    cover image ACM Conferences
    ISSAC '15: Proceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation
    June 2015
    374 pages
    ISBN:9781450334358
    DOI:10.1145/2755996
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 24 June 2015

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    Author Tags

    1. cylindrical algebraic decomposition
    2. polynomial inequalities

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    ISSAC '15 Paper Acceptance Rate 43 of 71 submissions, 61%;
    Overall Acceptance Rate 395 of 838 submissions, 47%

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    View all
    • (2024)On Projective Delineability2024 26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)10.1109/SYNASC65383.2024.00015(9-16)Online publication date: 16-Sep-2024
    • (2024)Recent Developments in Real Quantifier Elimination and Cylindrical Algebraic Decomposition (Extended Abstract of Invited Talk)Computer Algebra in Scientific Computing10.1007/978-3-031-69070-9_1(1-10)Online publication date: 1-Sep-2024
    • (2022)The DEWCAD projectACM Communications in Computer Algebra10.1145/3511528.351153855:3(107-111)Online publication date: 12-Jan-2022
    • (2022)New Heuristic to Choose a Cylindrical Algebraic Decomposition Variable Ordering Motivated by Complexity AnalysisComputer Algebra in Scientific Computing10.1007/978-3-031-14788-3_17(300-317)Online publication date: 22-Aug-2022
    • (2021)Choosing the Variable Ordering for Cylindrical Algebraic Decomposition via Exploiting Chordal StructureProceedings of the 2021 International Symposium on Symbolic and Algebraic Computation10.1145/3452143.3465520(281-288)Online publication date: 18-Jul-2021
    • (2020)Cylindrical algebraic decomposition with equational constraintsJournal of Symbolic Computation10.1016/j.jsc.2019.07.019100:C(38-71)Online publication date: 1-Sep-2020
    • (2020)Symbolic computation and satisfiability checkingJournal of Symbolic Computation10.1016/j.jsc.2019.07.017100:C(1-10)Online publication date: 1-Sep-2020
    • (2020)Applying Machine Learning to Heuristics for Real Polynomial Constraint SolvingMathematical Software – ICMS 202010.1007/978-3-030-52200-1_29(292-301)Online publication date: 13-Jul-2020
    • (2019)Regular cylindrical algebraic decompositionJournal of the London Mathematical Society10.1112/jlms.12257101:1(43-59)Online publication date: 29-Jul-2019
    • (2019)Using Machine Learning to Improve Cylindrical Algebraic DecompositionMathematics in Computer Science10.1007/s11786-019-00394-813:4(461-488)Online publication date: 3-Apr-2019
    • Show More Cited By

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