An Efficient Algorithm for the Complex Roots Problem

Given a univariate polynomialf(z) of degreenwith complex coefficients, whose norms are less than 2^min magnitude, the root problem is to find all the roots off(z) up to specified precision 2^−μ. Assuming the arithmetic model for computation, we provide an algorithm which has complexityO(nlog⁵nlogB), whereb= χ + μ, and χ = max{n,m}. This improves on the previous best known algorithm of Pan for the problem, which has complexityO(n²log²nlog(m+ μ)). A remarkable property of our algorithm is that it does not require any assumptions about the root separation off, which were either explicitly, or implicitly, required by previous algorithms. Moreover it also has a work-efficient parallel implementation. We also show that both the sequential and parallel implementations of the algorithm work without modification in the Boolean model of arithmetic. In this case, it follows from root perturbation estimates that we need only specify θ = ⌈n(B+ logn+ 3)⌉ bits of the binary representations of the real and imaginary parts of each of the coefficients off. We also show that by appropriate rounding of intermediate values, we can bound the number of bits required to represent all complex numbers occurring as intermediate quantities in the computation. The result is that we can restrict the numbers we use in every basic arithmetic operation to those having real and imaginary parts with at most φ bits, where[formula]and[formula]Thus, in the Boolean model, the overall work complexity of the algorithm is only increased by a multiplicative factor ofM(φ) (whereM(ψ) =O(ψ(log ψ) log log ψ) is the bit complexity for multiplication of integers of length ψ). The key result on which the algorithm is based, is a new theorem of Coppersmith and Neff relating the geometric distribution of the zeros of a polynomial to the distribution of the zeros of its high order derivatives. We also introduce several new techniques (splitting sets and “centered” points) which hinge on it. We also observe that our root finding algorithm can be efficiently parallelized to run in parallel timeO(log⁶nlogB) usingnprocessors.     

Determination of the limits for multivariate rational functions

The purpose of this paper is to solve the problem of determining the limits of multivariate rational functions.It is essential to decide whether or not limxˉ→0f g=0 for two non-zero polynomials f,g∈R[x1,...,xn]with f(0,...,0)=g(0,...,0)=0.For two such polynomials f and g,we establish two necessary and sufcient conditions for the rational functionf g to have its limit 0 at the origin.Based on these theoretic results,we present an algorithm for deciding whether or not lim(x1,...,xn)→(0,...,0)f g=0,where f,g∈R[x1,...,xn]are two non-zero polynomials.The design of our algorithm involves two existing algorithms:one for computing the rational univariate representations of a complete chain of polynomials,another for catching strictly critical points in a real algebraic variety.The two algorithms are based on the well-known Wu’s method.With the aid of the computer algebraic system Maple,our algorithm has been made into a general program.In the final section of this paper,several examples are given to illustrate the efectiveness of our algorithm.     

Quasi-GCD computations

For univariate polynomials with real or complex coefficients and a given error bound ? > 0, h is called a quasi-gcd of f and g, if h is an ?-approximate divisor of f and of g and if any (exact) common divisor of f, g is an approximate divisor of h. Extended quasi-gcd computation means to find such h and additional cofactors u, ν such that | uf + νg ? h | < ? | h | holds. Suitable “pivoting” leads to a numerically stable version of Euclid's algorithm for solving this task. Further refinements by a divide-and-conquer technique and by means of fast algorithms for polynomial arithmetic then yield the worst case upper bound O(n² lg n(lg(1/?) + n lg n)) of “pointer time” for nth-degree polynomials. In the particular case of integer polynomials, however, an immediate reduction to fast integer gcd computation is recommended, instead.     

Two new triangles of q-integers via q-Eulerian polynomials of type A and B

The classical Eulerian polynomials can be expanded in the basis t ^k?1(1+t) ^n+1?2k (1≤k≤?(n+1)/2?) with positive integral coefficients. This formula implies both the symmetry and the unimodality of the Eulerian polynomials. In this paper, we prove a q-analogue of this expansion for Carlitz’s q-Eulerian polynomials as well as a similar formula for Chow–Gessel’s q-Eulerian polynomials of type B. We shall give some applications of these two formulas, which involve two new sequences of polynomials in the variable q with positive integral coefficients. It is an open problem to give a combinatorial interpretation for these polynomials.     

Global residues for sparse polynomial systems

We consider families of sparse Laurent polynomials f₁,…,f_n with a finite set of common zeros Z_f in the torus Tⁿ=(C−{0})ⁿ. The global residue assigns to every Laurent polynomial g the sum of its Grothendieck residues over Z_f. We present a new symbolic algorithm for computing the global residue as a rational function of the coefficients of the f_i when the Newton polytopes of the f_i are full-dimensional. Our results have consequences in sparse polynomial interpolation and lattice point enumeration in Minkowski sums of polytopes.     

Exact algorithms for dominating set

The measure and conquer approach has proven to be a powerful tool to analyse exact algorithms for combinatorial problems like Dominating Set and Independent Set. This approach is used in this paper to obtain a faster exact algorithm for Dominating Set. We obtain this algorithm by considering a series of branch and reduce algorithms. This series is the result of an iterative process in which a mathematical analysis of an algorithm in the series with measure and conquer results in a convex or quasiconvex programming problem. The solution, by means of a computer, to this problem not only gives a bound on the running time of the algorithm, but can also give an indication on where to look for a new reduction rule, often giving a new, possibly faster algorithm. As a result, we obtain an O(1.4969ⁿ) time and polynomial space algorithm.     

Stirling polynomials

An investigation is made of the polynomials f_k(n) = S(n + k, n) and g_k(n) = (?1)^ks(n, n ? k), where S and s denote the Stirling numbers of the second and first kind, respectively. The main result gives a combinatorial interpretation of the coefficients of the polynomial (1 ? x)^2k+1Σ_n=0^∞f_k(n)xⁿ analogous to the well-known combinatorial interpretation of the Eulerian numbers in terms of descents of permutations.     

The least common multiple of a sequence of products of linear polynomials

Let f(x) be the product of several linear polynomials with integer coefficients. In this paper, we obtain the estimate log?lcm?(f(1),…,f(n))～An as n→∞, where A is a constant depending on?f.     

Modifications of Newton’s method for even-grade palindromic polynomials and other twined polynomials

The paper describes some modifications of Newton??s method for refining the zeros of even-grade f(x)-twined (f(x)-egt) polynomials, defined as polynomials whose roots appear in pairs {x _i ,f(x _i )}. Particular attention is given to even-grade palindromic (egp) polynomials. The algorithms are derived from certain symmetric division processes for computing a symmetric quotient and a symmetric remainder of two given f(x)-egt polynomials. Numerical results indicate that the presented algorithms can be more accurate than other methods which do not take into consideration the symmetry of the coefficients.     

Some Complexity Results for Polynomial Ideals

In this paper, we survey some of our new results on the complexity of a number of problems related to polynomial ideals. We consider multivariate polynomials over some ring, like the integers or the rationals. For instance, a polynomial ideal membership problem is a (w+ 1)-tupleP= (f,g₁,g₂, …g_wwherefand theg_iare multivariate polynomials, and the problem is to determine whetherfis in the ideal generated by theg_i. For polynomials over the integers or rationals, this problem is known to be exponential space complete. We discuss further complexity results for problems related to polynomial ideals, like the word and subword problems for commutative semigroups, a quantitative version of Hilbert's Nullstellensatz in a complexity theoretic version, and problems concerning the computation of reduced polynomials and Gröbner bases.     

Optimal bounds for sign-representing the intersection of two halfspaces by polynomials

The threshold degree of a function f: {0,1} ⁿ → {?1,+1} is the least degree of a real polynomial p with f(x) ≡ sgnp(x). We prove that the intersection of two halfspaces on {0,1} ⁿ has threshold degree Ω(n), which matches the trivial upper bound and solves an open problem due to Klivans (2002). The best previous lower bound was Ω({ie73-1}). Our result shows that the intersection of two halfspaces on {0,1} ⁿ only admits a trivial {ie73-2}-time learning algorithm based on sign-representation by polynomials, unlike the advances achieved in PAC learning DNF formulas and read-once Boolean formulas.     

Efficient algorithms for merging

Efficient algorithms are given to find the maximum lengthn of an ordered list in which 4 elements can be merged using exactlyk comparisons. A top down algorithm for the (2,n) merge problem is discussed and is shown to obtain the optimal merge length first reported by Hwang and Lin. Our algorithms combine this top down approach and strong heuristics, some of which derived from Hwang's optimal algorithm for the (3,n) problem, and produce a lengthn which is close to the optimal lengthf ₄(k).     

On cographic regular matroids

The presentation of alternating permutatioas via labelled binary trees is used to define polynomials H_2n?1(x) as enumerating polynomials for the height of peaks in alternating permutations of length 2n?1. A divisibility property of the coefficients of these polynomials is proved, which generalizes and explains combinatirially a well-known property of the tangent numbers. Furthermore, a version of the exponential generating function for the H_2n?1(x) is given, leading to a new combinatorial interpretation of Dumont's modified Ghandi-polynomials.     

Sum of degrees of irreducible factors for polynomials in several variables

New lower bounds are given for the sum of degrees of simple and distinct irreducible factors of the polynomial f₁+?+fn, where fi(1?i?n) are pairwise relatively prime polynomials of several variables with coefficients in C.     

Connection coefficients, orthogonal polynomials and the WZ-algorithms

In this paper we explore the relationship between the coefficients in the expansion of a function f(x) in orthogonal polynomials and the coefficients for the expansion of (1-x) ^m f(x), with particular attention to the case of Jacobi polynomials. Such problems arise frequently in computational chemistry. The analysis of the situation is substantially assisted by the use of two of the so-called Wilf-Zeilberger algorithms: the algorithm zeil and the algorithm hyper. We explain these algorithms and give several examples. This revised version was published online in June 2006 with corrections to the Cover Date.     

Complex brackets and balanced complex 1st-order difference polynomials in 4-dimensional Minkowski space

This paper investigates complex brackets and balanced complex 1st-order di?erence (BCD) polynomials. Then we propose an algorithm of O(n log n) complexity to check the equality of brackets. It substitutes exponential algorithms before. Also, BCD polynomials have some usages in geometric calculation.     

A class of quadratically convergent algorithms for constrained function minimization

The problem of minimizing a functionf(x) subject to the constraint ?(x)=0 is considered. Here,f is a scalar,x is ann-vector, and ? is anm-vector, wherem <n. A general quadratically convergent algorithm is presented. The conjugate-gradient algorithm and the variable-metric algorithms for constrained function minimization can be obtained as particular cases of the general algorithm. It is shown that, for a quadratic function subject to a linear constraint, all the particular algorithms behave identically if the one-dimensional search for the stepsize is exact. Specifically, they all produce the same sequence of points and lead to the constrained minimal point in no more thann ?r descent steps, wherer is the number of linearly independent constraints. The algorithms are then modified so that they can also be employed for a nonquadratic function subject to a nonlinear constraint. Some particular algorithms are tested through several numerical examples.     

On pedigree polytopes and Hamiltonian cycles

In this paper we define a combinatorial object called a pedigree, and study the corresponding polytope, called the pedigree polytope. Pedigrees are in one-to-one correspondence with the Hamiltonian cycles on K_n. Interestingly, the pedigree polytope seems to differ from the standard tour polytope, Q_n with respect to the complexity of testing whether two given vertices of the polytope are nonadjacent. A polynomial time algorithm is given for nonadjacency testing in the pedigree polytope, whereas the corresponding problem is known to be NP-complete for Q_n. We also discuss some properties of the pedigree polytope and illustrate with examples.     

A cumulative not-first/not-last filtering algorithm in O(n 2log(n))

In cumulative and disjunctive constraint-based scheduling, the resource constraint is enforced by several filtering rules. Among these rules, we have (extended) edge-finding and not-first/not-last rules. The not-first/not-last rule detects tasks that cannot run first/last relatively to a set of tasks and prunes their time bounds. In this paper, it is presented a sound O (n ² log n) algorithm for the cumulative not-first/not-last rule where n is the number of tasks. This algorithm reaches the same fix point as previous not-first/not-last algorithms, although it may take additional iterations to do so. The worst case complexity of this new algorithm for the maximal adjustment is the same as our previous complete O (n ²|H| log n) not-first/not-last algorithm [7] where |H| is the maximum between the number of distinct earliest completion and latest start times of tasks. But, experimental results on benchmarks from the Project Scheduling Problem Library (PSPLib) and the Baptiste and Le Pape data set (BL) suggest that the new not-first/not-last algorithm has a substantially reduced runtime. Furthermore, the results demonstrate that in practice the new algorithm rarely requires more propagations than previous not-first/not-last algorithms.