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At least 145 records · Page 8Linked to original sources

Computing rational points in convex semi-algebraic sets and SOS decompositions

Let ${\cal P}=\{h_1, ..., h_s\}\subset \Z[Y_1, ..., Y_k]$, $D\geq °(h_i)$ for $1\leq i \leq s$, $σ$ bounding the bit length of the coefficients of the $h_i$'s, and $Φ$ be a quantifier-free ${\cal P}$-formula defining a convex semi-algebraic set. We design an algorithm returning a rational point in ${\cal S}$ if and only if ${\cal S}\cap \Q\neq\emptyset$. It requires $σ^{\bigO(1)}D^{\bigO(k^3)}$ bit operations. If a rational point is outputted its coordinates have bit length dominated by $σD^{\bigO(k^3)}$. Using this result, we obtain a procedure deciding if a polynomial $f\in \Z[X_1, >..., X_n]$ is a sum of squares of polynomials in $\Q[X_1, ..., X_n]$. Denote by $d$ the degree of $f$, $τ$ the maximum bit length of the coefficients in $f$, $D={{n+d}\choose{n}}$ and $k\leq D(D+1)-{{n+2d}\choose{n}}$. This procedure requires $τ^{\bigO(1)}D^{\bigO(k^3)}$ bit operations and the coefficients of the outputted polynomials have bit length dominated by $τD^{\bigO(k^3)}$.

cs.SC↗

Bounding the radii of balls meeting every connected component of semi-algebraic sets

We prove explicit bounds on the radius of a ball centered at the origin which is guaranteed to contain all bounded connected components of a semi-algebraic set $S \subset \mathbbm{R}^k$ defined by a quantifier-free formula involving $s$ polynomials in $\mathbbm{Z}[X_1, ..., X_k]$ having degrees at most $d$, and whose coefficients have bitsizes at most $τ$. Our bound is an explicit function of $s, d, k$ and $τ$, and does not contain any undetermined constants. We also prove a similar bound on the radius of a ball guaranteed to intersect every connected component of $S$ (including the unbounded components). While asymptotic bounds of the form $2^{τd^{O (k)}}$ on these quantities were known before, some applications require bounds which are explicit and which hold for all values of $s, d, k$ and $τ$. The bounds proved in this paper are of this nature.

cs.SC↗

From Abstract Rewriting Systems to Abstract Proof Systems

Some personal recollections on the introduction of `abstract proof systems' as a framework for formulating syntax-independent, general results about rule derivability and admissibility. With a particular eye on the inspiration I owe to Roel de Vrijer: the analogy with abstract rewriting systems.

cs.LO↗

Faster exponentials of power series

We describe a new algorithm for computing exp(f) where f is a power series in C[[x]]. If M(n) denotes the cost of multiplying polynomials of degree n, the new algorithm costs (2.1666... + o(1)) M(n) to compute exp(f) to order n. This improves on the previous best result, namely (2.333... + o(1)) M(n).

cs.SC↗

The Hilbert scheme of points and its link with border basis

In this paper, we give new explicit representations of the Hilbert scheme of $μ$ points in $\PP^{r}$ as a projective subvariety of a Grassmanniann variety. This new explicit description of the Hilbert scheme is simpler than the previous ones and global. It involves equations of degree $2$. We show how these equations are deduced from the commutation relations characterizing border bases. Next, we consider infinitesimal perturbations of an input system of equations on this Hilbert scheme and describe its tangent space. We propose an effective criterion to test if it is a flat deformation, that is if the perturbed system remains on the Hilbert scheme of the initial equations. This criterion involves in particular formal reduction with respect to border bases.

cs.SC↗

Deciding Regularity of the Set of Instances of a Set of Terms with Regular Constraints is EXPTIME-Complete

Finite-state tree automata are a well studied formalism for representing term languages. This paper studies the problem of determining the regularity of the set of instances of a finite set of terms with variables, where each variable is restricted to instantiations of a regular set given by a tree automaton. The problem was recently proved decidable, but with an unknown complexity. Here, the exact complexity of the problem is determined by proving EXPTIME-completeness. The main contribution is a new, exponential time algorithm that performs various exponential transformations on the involved terms and tree automata, and decides regularity by analyzing formulas over inequality and height predicates.

cs.SC↗

A computational definition of the notion of vectorial space

We usually define an algebraic structure by a set, some operations defined on this set and some propositions that the algebraic structure must validate. In some cases, we can replace these propositions by an algorithm on terms constructed upon these operations that the algebraic structure must validate. We show in this note that this is the case for the notions of vectorial space and bilinear operation. KEYWORDS: Rewrite system, vector space, bilinear operation, tensorial product, semantics, quantum programming languages, probabilistic programming languages.

cs.LO↗

Efficient Higher Order Derivatives of Objective Functions Composed of Matrix Operations

This paper is concerned with the efficient evaluation of higher-order derivatives of functions $f$ that are composed of matrix operations. I.e., we want to compute the $D$-th derivative tensor $\nabla^D f(X) \in \mathbb R^{N^D}$, where $f:\mathbb R^{N} \to \mathbb R$ is given as an algorithm that consists of many matrix operations. We propose a method that is a combination of two well-known techniques from Algorithmic Differentiation (AD): univariate Taylor propagation on scalars (UTPS) and first-order forward and reverse on matrices. The combination leads to a technique that we would like to call univariate Taylor propagation on matrices (UTPM). The method inherits many desirable properties: It is easy to implement, it is very efficient and it returns not only $\nabla^D f$ but yields in the process also the derivatives $\nabla^d f$ for $d \leq D$. As performance test we compute the gradient $\nabla f(X)$ % and the Hessian $\nabla_A^2 f(A)$ by a combination of forward and reverse mode of $f(X) = \trace (X^{-1})$ in the reverse mode of AD for $X \in \mathbb R^{n \times n}$. We observe a speedup of about 100 compared to UTPS. Due to the nature of the method, the memory footprint is also small and therefore can be used to differentiate functions that are not accessible by standard methods due to limited physical memory.

cs.DS↗

Shortest Two-way Linear Recurrences

Let $s$ be a finite sequence over a field of length $n$. It is well-known that if $s$ satisfies a linear recurrence of order $d$ with non-zero constant term, then the reverse of $s$ also satisfies a recurrence of order $d$ (with coefficients in reverse order). A recent article of A. Salagean proposed an algorithm to find such a shortest 'two-way' recurrence -- which may be longer than a linear recurrence for $s$ of shortest length $\LC_n$. We give a new and simpler algorithm to compute a shortest two-way linear recurrence. First we show that the pairs of polynomials we use to construct a minimal polynomial iteratively are always relatively prime; we also give the extended multipliers. Then we combine degree lower bounds with a straightforward rewrite of a published algorithm due to the author to obtain our simpler algorithm. The increase in shortest length is $\max\{n+1-2\LC_n,0\}$.

cs.IT↗

Linear Solving for Sign Determination

We give a specific method to solve with quadratic complexity the linear systems arising in known algorithms to deal with the sign determination problem. In particular, this enable us to improve the complexity bound for sign determination in the univariate case.

math.AG↗

Completeness of the WDS method in Checking Positivity of Integral Forms

Examples show that integral forms can be efficiently proved positive semidefinite by the WDS method, but it was unknown that how many steps of substitutions are needed, or furthermore, which integral forms is this method applicable for. In this paper, we give upper bounds of step numbers of WDS required in proving that an integral form is positive definite, positive semidefinite, or not positive semidefinite, thus deducing that the WDS method is complete.

cs.SC↗

Simplex Subdivisions and Nonnegativity Decision of Forms

This paper mainly studies nonnegativity decision of forms based on variable substitutions. Unlike existing research, the paper regards simplex subdivisions as new perspectives to study variable substitutions, gives some subdivisions of the simplex T_n, introduces the concept of convergence of the subdivision sequence, and presents a sufficient and necessary condition for the convergent self-similar subdivision sequence. Then the relationships between subdivisions and their corresponding substitutions are established. Moreover, it is proven that if the form F is indefinite on T_n and the sequence of the successive L-substitution sets is convergent, then the sequence of sets {SLS^(m)(F)} is negatively terminating, and an algorithm for deciding indefinite forms with a counter-example is obtained. Thus, various effective substitutions for deciding positive semi-definite forms and indefinite forms are gained, which are beyond the weighted difference substitutions characterized by "difference".

cs.SC↗

The weighted difference substitutions and Nonnegativity Decision of Forms

In this paper, we study the weighted difference substitutions from geometrical views. First, we give the geometric meanings of the weighted difference substitutions, and introduce the concept of convergence of the sequence of substitution sets. Then it is proven that the sequence of the successive weighted difference substitution sets is convergent. Based on the convergence of the sequence of the successive weighted difference sets, a new, simpler method to prove that if the form F is positive definite on T_n, then the sequence of sets {SDS^m(F)} is positively terminating is presented, which is different from the one given in [11]. That is, we can decide the nonnegativity of a positive definite form by successively running the weighted difference substitutions finite times. Finally, an algorithm for deciding an indefinite form with a counter-example is obtained, and some examples are listed by using the obtained algorithm.

cs.SC↗

A Complete Method for Checking Hurwitz Stability of a Polytope of Matrices

We present a novel method for checking the Hurwitz stability of a polytope of matrices. First we prove that the polytope matrix is stable if and only if two homogenous polynomials are positive on a simplex, then through a newly proposed method, i.e., the weighted difference substitution method, the latter can be checked in finite steps. Examples show the efficiency of our method.

cs.SC↗

A complete algorithm to find exact minimal polynomial by approximations

We present a complete algorithm for finding an exact minimal polynomial from its approximate value by using an improved parameterized integer relation construction method. Our result is superior to the existence of error controlling on obtaining an exact rational number from its approximation. The algorithm is applicable for finding exact minimal polynomial of an algebraic number by its approximate root. This also enables us to provide an efficient method of converting the rational approximation representation to the minimal polynomial representation, and devise a simple algorithm to factor multivariate polynomials with rational coefficients. Compared with the subsistent methods, our method combines advantage of high efficiency in numerical computation, and exact, stable results in symbolic computation. we also discuss some applications to some transcendental numbers by approximations. Moreover, the Digits of our algorithm is far less than the LLL-lattice basis reduction technique in theory. In this paper, we completely implement how to obtain exact results by numerical approximate computations.

cs.SC↗

The Berlekamp-Massey Algorithm via Minimal Polynomials

We present a recursive minimal polynomial theorem for finite sequences over a commutative integral domain $D$. This theorem is relative to any element of $D$. The ingredients are: the arithmetic of Laurent polynomials over $D$, a recursive 'index function' and simple mathematical induction. Taking reciprocals gives a 'Berlekamp-Massey theorem' i.e. a recursive construction of the polynomials arising in the Berlekamp-Massey algorithm, relative to any element of $D$. The recursive theorem readily yields the iterative minimal polynomial algorithm due to the author and a transparent derivation of the iterative Berlekamp-Massey algorithm. We give an upper bound for the sum of the linear complexities of $s$ which is tight if $s$ has a perfect linear complexity profile. This implies that over a field, both iterative algorithms require at most $2\lfloor \frac{n^2}{4}\rfloor$ multiplications.

cs.IT↗

Parallel computation of real solving bivariate polynomial systems by zero-matching method

We present a new algorithm for solving the real roots of a bivariate polynomial system $Σ=\{f(x,y),g(x,y)\}$ with a finite number of solutions by using a zero-matching method. The method is based on a lower bound for bivariate polynomial system when the system is non-zero. Moreover, the multiplicities of the roots of $Σ=0$ can be obtained by a given neighborhood. From this approach, the parallelization of the method arises naturally. By using a multidimensional matching method this principle can be generalized to the multivariate equation systems.

cs.SC↗