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We offer a Maple package {\tt Poincare\_Series} for calculating the Poincaré series for the algebras of invariants/covariants of binary forms, for the algebras of joint invariants/covariants of several binary forms, for the kernel of Weitzenböck derivations and for the multivariate Poincaré series of algebras of joint invariants/covariants of several binary forms.
We provide a "shared axiomatization" of natural numbers and hereditarily finite sets built around a polymorphic abstraction of bijective base-2 arithmetics. The "axiomatization" is described as a progressive refinement of Haskell type classes with examples of instances converging to an efficient implementation in terms of arbitrary length integers and bit operations. As an instance, we derive algorithms to perform arithmetic operations efficiently directly with hereditarily finite sets. The self-contained source code of the paper is available at http://logic.cse.unt.edu/tarau/research/2010/unified.hs .
Matrix interpretations generalize linear polynomial interpretations and have been proved useful in the implementation of tools for automatically proving termination of Term Rewriting Systems. In view of the successful use of rational coefficients in polynomial interpretations, we have recently generalized traditional matrix interpretations (using natural numbers in the matrix entries) to incorporate real numbers. However, existing results which formally prove that polynomials over the reals are more powerful than polynomials over the naturals for proving termination of rewrite systems failed to be extended to matrix interpretations. In this paper we get deeper into this problem. We show that, under some conditions, it is possible to transform a matrix interpretation over the rationals satisfying a set of symbolic constraints into a matrix interpretation over the naturals (using bigger matrices) which still satisfies the constraints.
We present an extension of our GPGCD method, an iterative method for calculating approximate greatest common divisor (GCD) of univariate polynomials, to polynomials with the complex coefficients. For a given pair of polynomials and a degree, our algorithm finds a pair of polynomials which has a GCD of the given degree and whose coefficients are perturbed from those in the original inputs, making the perturbations as small as possible, along with the GCD. In our GPGCD method, the problem of approximate GCD is transfered to a constrained minimization problem, then solved with a so-called modified Newton method, which is a generalization of the gradient-projection method, by searching the solution iteratively. While our original method is designed for polynomials with the real coefficients, we extend it to accept polynomials with the complex coefficients in this paper.
The well known algorithm of Volker Strassen for matrix multiplication can only be used for $(m2^k \times m2^k)$ matrices. For arbitrary $(n \times n)$ matrices one has to add zero rows and columns to the given matrices to use Strassen's algorithm. Strassen gave a strategy of how to set $m$ and $k$ for arbitrary $n$ to ensure $n\leq m2^k$. In this paper we study the number $d$ of additional zero rows and columns and the influence on the number of flops used by the algorithm in the worst case ($d=n/16$), best case ($d=1$) and in the average case ($d\approx n/48$). The aim of this work is to give a detailed analysis of the number of additional zero rows and columns and the additional work caused by Strassen's bad parameters. Strassen used the parameters $m$ and $k$ to show that his matrix multiplication algorithm needs less than $4.7n^{\log_2 7}$ flops. We can show in this paper, that these parameters cause an additional work of approx. 20 % in the worst case in comparison to the optimal strategy for the worst case. This is the main reason for the search for better parameters.
We describe how we connected three programs that compute Groebner bases to Coq, to do automated proofs on algebraic, geometrical and arithmetical expressions. The result is a set of Coq tactics and a certificate mechanism (downloadable at http://www-sop.inria.fr/marelle/Loic.Pottier/gb-keappa.tgz). The programs are: F4, GB \, and gbcoq. F4 and GB are the fastest (up to our knowledge) available programs that compute Groebner bases. Gbcoq is slow in general but is proved to be correct (in Coq), and we adapted it to our specific problem to be efficient. The automated proofs concern equalities and non-equalities on polynomials with coefficients and indeterminates in R or Z, and are done by reducing to Groebner computation, via Hilbert's Nullstellensatz. We adapted also the results of Harrison, to allow to prove some theorems about modular arithmetics. The connection between Coq and the programs that compute Groebner bases is done using the "external" tactic of Coq that allows to call arbitrary programs accepting xml inputs and outputs. We also produce certificates in order to make the proof scripts independant from the external programs.
The dominance relationship between two members of the family of Sugeno Weber t-norms is proven by using a quantifer elimination algorithm. Further it is shown that dominance is a transitive, and therefore also an order relation, on this family of t-norms.
We give bit-size estimates for the coefficients appearing in triangular sets describing positive-dimensional algebraic sets defined over Q. These estimates are worst case upper bounds; they depend only on the degree and height of the underlying algebraic sets. We illustrate the use of these results in the context of a modular algorithm. This extends results by the first and last author, which were confined to the case of dimension 0. Our strategy is to get back to dimension 0 by evaluation and inter- polation techniques. Even though the main tool (height theory) remains the same, new difficulties arise to control the growth of the coefficients during the interpolation process.
Factorization of polynomials is one of the foundations of symbolic computation. Its applications arise in numerous branches of mathematics and other sciences. However, the present advanced programming languages such as C++ and J++, do not support symbolic computation directly. Hence, it leads to difficulties in applying factorization in engineering fields. In this paper, we present an algorithm which use numerical method to obtain exact factors of a bivariate polynomial with rational coefficients. Our method can be directly implemented in efficient programming language such C++ together with the GNU Multiple-Precision Library. In addition, the numerical computation part often only requires double precision and is easily parallelizable.
We propose a technique for pattern classification in symbolic streams via selective erasure of observed symbols, in cases where the patterns of interest are represented as Probabilistic Finite State Automata (PFSA). We define an additive abelian group for a slightly restricted subset of probabilistic finite state automata (PFSA), and the group sum is used to formulate pattern-specific semantic annihilators. The annihilators attempt to identify pre-specified patterns via removal of essentially all inter-symbol correlations from observed sequences, thereby turning them into symbolic white noise. Thus a perfect annihilation corresponds to a perfect pattern match. This approach of classification via information annihilation is shown to be strictly advantageous, with theoretical guarantees, for a large class of PFSA models. The results are supported by simulation experiments.
Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies and underlies the inverse protein folding problem. Herein, we outline our theories for fold-recognition in the "twilight-zone" of sequence similarity (<25% identity). Our analyses demonstrate that structural sequence profiles built using Position-Specific Scoring Matrices (PSSMs) significantly outperform multiple popular homology-modeling algorithms for relating and predicting structures given only their amino acid sequences. Importantly, structural sequence profiles reconstitute SCOP fold classifications in control and test datasets. Results from our experiments suggest that structural sequence profiles can be used to rapidly annotate protein folds at proteomic scales. We propose that encoding the entire Protein DataBank (~1070 folds) into structural sequence profiles would extract interoperable information capable of improving most if not all methods of structural modeling.
This paper deals with the index reduction problem for the class of quasi-regular DAE systems. It is shown that any of these systems can be transformed to a generically equivalent first order DAE system consisting of a single purely algebraic (polynomial) equation plus an under-determined ODE (that is, a semi-explicit DAE system of differentiation index 1) in as many variables as the order of the input system. This can be done by means of a Kronecker-type algorithm with bounded complexity.
In this paper, an intersection theory for generic differential polynomials is presented. The intersection of an irreducible differential variety of dimension $d$ and order $h$ with a generic differential hypersurface of order $s$ is shown to be an irreducible variety of dimension $d-1$ and order $h+s$. As a consequence, the dimension conjecture for generic differential polynomials is proved. Based on the intersection theory, the Chow form for an irreducible differential variety is defined and most of the properties of the Chow form in the algebraic case are established for its differential counterpart. Furthermore, the generalized differential Chow form is defined and its properties are proved. As an application of the generalized differential Chow form, the differential resultant of $n+1$ generic differential polynomials in $n$ variables is defined and properties similar to that of the Macaulay resultant for multivariate polynomials are proved.
This system description provides an overview of H-PILoT (Hierarchical Proving by Instantiation in Local Theory extensions), a program for hierarchical reasoning in extensions of logical theories. H-PILoT reduces deduction problems in the theory extension to deduction problems in the base theory. Specialized provers and standard SMT solvers can be used for testing the satisfiability of the formulae obtained after the reduction. For a certain type of theory extension (namely for local theory extensions) this hierarchical reduction is sound and complete and -- if the formulae obtained this way belong to a fragment decidable in the base theory -- H-PILoT provides a decision procedure for testing satisfiability of ground formulae, and can also be used for model generation.
To maximize efficiency in time and space, allocations and deallocations, in the exact linear algebra library \linbox, must always occur in the founding scope. This provides a simple lightweight allocation model. We present this model and its usage for the rebinding of matrices between different coefficient domains. We also present automatic tools to speed-up the compilation of template libraries and a software abstraction layer for the introduction of transparent parallelism at the algorithmic level.
We consider the problem of finding a sparse multiple of a polynomial. Given f in F[x] of degree d over a field F, and a desired sparsity t, our goal is to determine if there exists a multiple h in F[x] of f such that h has at most t non-zero terms, and if so, to find such an h. When F=Q and t is constant, we give a polynomial-time algorithm in d and the size of coefficients in h. When F is a finite field, we show that the problem is at least as hard as determining the multiplicative order of elements in an extension field of F (a problem thought to have complexity similar to that of factoring integers), and this lower bound is tight when t=2.
We present an exact and complete algorithm to isolate the real solutions of a zero-dimensional bivariate polynomial system. The proposed algorithm constitutes an elimination method which improves upon existing approaches in a number of points. First, the amount of purely symbolic operations is significantly reduced, that is, only resultant computation and square-free factorization is still needed. Second, our algorithm neither assumes generic position of the input system nor demands for any change of the coordinate system. The latter is due to a novel inclusion predicate to certify that a certain region is isolating for a solution. Our implementation exploits graphics hardware to expedite the resultant computation. Furthermore, we integrate a number of filtering techniques to improve the overall performance. Efficiency of the proposed method is proven by a comparison of our implementation with two state-of-the-art implementations, that is, LPG and Maple's isolate. For a series of challenging benchmark instances, experiments show that our implementation outperforms both contestants.
We consider the problem of isolating the real roots of a square-free polynomial with integer coefficients using (variants of) the continued fraction algorithm (CF). We introduce a novel way to compute a lower bound on the positive real roots of univariate polynomials. This allows us to derive a worst case bound of $\sOB(d^6 + d^4τ^2 + d^3τ^2)$ for isolating the real roots of a polynomial with integer coefficients using the classic variant of CF, where $d$ is the degree of the polynomial and $τ$ the maximum bitsize of its coefficients. This improves the previous bound by Sharma \cite{sharma-tcs-2008} by a factor of $d^3$ and matches the bound derived by Mehlhorn and Ray \cite{mr-jsc-2009} for another variant of CF; it also matches the worst case bound of the subdivision-based solvers. We present a new variant of CF, we call it iCF, that isolates the real roots of a polynomial with integer coefficients in $\sOB(d^5+d^4τ)$, thus improving the current known bound for the problem by a factor of $d$. If the polynomial has only real roots, then our bound becomes $\sOB(d^4+d^3τ+ d^2τ^2)$, thus matching the bound of the numerical algorithms by Reif \cite{r-focs-1993} and by Ben-Or and Tiwari \cite{bt-joc-1990}. Actually the latter bound holds in a more general setting, that is under the rather mild assumption that $Ω(d/\lg^c{d})$, where $c\geq 0$ is a constant, roots contribute to the sign variations of the coefficient list of the polynomial. This is the only bound on exact algorithms that matches the one of the numerical algorithms by Pan \cite{Pan02jsc} and Schönhage \cite{Sch82}. To our knowledge the presented bounds are the best known for the problem of real root isolation for algorithms based on exact computations.