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Jasper Nalbach

Publications and source records attributed to Jasper Nalbach.

9 recordsLinked to original sources

More is Less: Adding Polynomials for Faster Explanations in NLSAT

To check the satisfiability of (non-linear) real arithmetic formulas, modern satisfiability modulo theories (SMT) solving algorithms like NLSAT depend heavily on single cell construction, the task of generalizing a sample point to a connected subset (cell) of $\mathbb{R}^n$, that contains the sample and over which a given set of polynomials is sign-invariant. In this paper, we propose to speed up the computation and simplify the representation of the resulting cell by dynamically extending the considered set of polynomials with further linear polynomials. While this increases the total number of (smaller) cells generated throughout the algorithm, our experiments show that it can pay off when using suitable heuristics due to the interaction with Boolean reasoning.

cs.SC

A Variant of Non-uniform Cylindrical Algebraic Decomposition for Real Quantifier Elimination

The Cylindrical Algebraic Decomposition (CAD) method is currently the only complete algorithm used in practice for solving real-algebraic problems. To ameliorate its doubly-exponential complexity, different exploration-guided adaptations try to avoid some of the computations. The first such adaptation named NLSAT was followed by Non-uniform CAD (NuCAD) and the Cylindrical Algebraic Covering (CAlC). Both NLSAT and CAlC have been developed and implemented in SMT solvers for satisfiability checking, and CAlC was recently also adapted for quantifier elimination. However, NuCAD was designed for quantifier elimination only, and no complete implementation existed before this work. In this paper, we present a novel variant of NuCAD for both real quantifier elimination and SMT solving, provide an implementation, and evaluate the method by experimentally comparing it to CAlC.

cs.SC

Projective Delineability for Single Cell Construction

The cylindrical algebraic decomposition (CAD) is the only complete method used in practice for solving problems like quantifier elimination or SMT solving related to real algebra, despite its doubly exponential complexity. Recent exploration-guided algorithms like NLSAT, NuCAD, and CAlC rely on CAD technology but reduce the computational effort heuristically. Single cell construction is a paradigm that is used in each of these algorithms. The central property on which the CAD algorithm is based is called delineability. Recently, we introduced a weaker notion called projective delineability which can require fewer computations to guarantee, but needs to be applied carefully. This paper adapts the single cell construction for exploiting projective delineability and reports on experimental results.

cs.SC

On Projective Delineability

We consider cylindrical algebraic decomposition (CAD) and the key concept of delineability which underpins CAD theory. We introduce the novel concept of projective delineability which is easier to guarantee computationally. We prove results about this which can allow reduced CAD computations.

math.AG

Extensions of the Cylindrical Algebraic Covering Method for Quantifiers

The cylindrical algebraic covering method was originally proposed to decide the satisfiability of a set of non-linear real arithmetic constraints. We reformulate and extend the cylindrical algebraic covering method to allow for checking the truth of arbitrary non-linear arithmetic formulas, adding support for both quantifiers and Boolean structure. Furthermore, we also propose a variant to perform quantifier elimination on such formulas. After introducing the algorithm, we elaborate on various extensions, optimizations and heuristics. Finally, we present an experimental evaluation of our implementation and provide a comparison with state-of-the-art SMT solvers and quantifier elimination tools.

cs.SC

FMplex: A Novel Method for Solving Linear Real Arithmetic Problems

In this paper we introduce a novel quantifier elimination method for conjunctions of linear real arithmetic constraints. Our algorithm is based on the Fourier-Motzkin variable elimination procedure, but by case splitting we are able to reduce the worst-case complexity from doubly to singly exponential. The adaption of the procedure for SMT solving has strong correspondence to the simplex algorithm, therefore we name it FMplex. Besides the theoretical foundations, we provide an experimental evaluation in the context of SMT solving.

cs.SC

FMplex: Exploring a Bridge between Fourier-Motzkin and Simplex

In this paper we present a quantifier elimination method for conjunctions of linear real arithmetic constraints. Our algorithm is based on the Fourier-Motzkin variable elimination procedure, but by case splitting we are able to reduce the worst-case complexity from doubly to singly exponential. The adaption of the procedure for SMT solving has strong correspondence to the simplex algorithm, therefore we name it FMplex. Besides the theoretical foundations, we provide an experimental evaluation in the context of SMT solving. This is an extended version of the authors' work previously published at the fourteenth International Symposium on Games, Automata, Logics, and Formal Verification (GandALF 2023).

cs.SC

Levelwise construction of a single cylindrical algebraic cell

Satisfiability Modulo Theories (SMT) solvers check the satisfiability of quantifier-free first-order logic formulas. We consider the theory of non-linear real arithmetic where the formulae are logical combinations of polynomial constraints. Here a commonly used tool is the Cylindrical Algebraic Decomposition (CAD) to decompose real space into cells where the constraints are truth-invariant through the use of projection polynomials. An improved approach is to repackage the CAD theory into a search-based algorithm: one that guesses sample points to satisfy the formula, and generalizes guesses that conflict constraints to cylindrical cells around samples which are avoided in the continuing search. Such an approach can lead to a satisfying assignment more quickly, or conclude unsatisfiability with fewer cells. A notable example of this approach is Jovanović and de Moura's NLSAT algorithm. Since these cells are produced locally to a sample we might need fewer projection polynomials than the traditional CAD projection. The original NLSAT algorithm reduced the set a little; while Brown's single cell construction reduced it much further still. However, the shape and size of the cell produced depends on the order in which the polynomials are considered. This paper proposes a method to construct such cells levelwise, i.e. built level-by-level according to a variable ordering. We still use a reduced number of projection polynomials, but can now consider a variety of different reductions and use heuristics to select the projection polynomials in order to optimise the shape of the cell under construction. We formulate all the necessary theory as a proof system: while not a common presentation for work in this field, it allows an elegant decoupling of heuristics from the algorithm and its proof of correctness.

cs.SC

Exploiting Strict Constraints in the Cylindrical Algebraic Covering

One of the few available complete methods for checking the satisfiability of sets of polynomial constraints over the reals is the cylindrical algebraic covering (CAlC) method. In this paper, we propose an extension for this method to exploit the strictness of input constraints for reducing the computational effort. We illustrate the concepts on a multidimensional example and provide experimental results to evaluate the usefulness of our proposed extension.

cs.SC