Finding thek smallest spanning trees

We give improved solutions for the problem of generating thek smallest spanning trees in a graph and in the plane. Our algorithm for general graphs takes timeO(m log(m, n)=k ²); for planar graphs this bound can be improved toO(n+k ²). We also show that thek best spanning trees for a set of points in the plane can be computed in timeO(min(k ² n+n logn,k ²+kn log(n/k))). Thek best orthogonal spanning trees in the plane can be found in timeO(n logn+kn log log(n/k)+k ²).     

On-line coloring of perfect graphs

Lovász, Saks, and Trotter showed that there exists an on-line algorithm which will color any on-linek-colorable graph onn vertices withO(nlog^(2k–3) n/log^(2k–4) n) colors. Vishwanathan showed that at least (log ^k–1 n/k ^k ) colors are needed. While these remain the best known bounds, they give a distressingly weak approximation of the number of colors required. In this article we study the case of perfect graphs. We prove that there exists an on-line algorithm which will color any on-linek-colorable perfect graph onn vertices withn ^10k/loglogn colors and that Vishwanathan's techniques can be slightly modified to show that his lower bound also holds for perfect graphs. This suggests that Vishwanathan's lower bound is far from tight in the general case.Research partially supported by Office of Naval Research grant N00014-90-J-1206.     

Explicit constructions for perfect hash families

Let k, v, t be integers such that k ≥ v ≥ t ≥ 2. A perfect hash family (N; k, v, t) can be defined as an N × k array with entries from a set of v symbols such that every N × t subarray contains at least one row having distinct symbols. Perfect hash families have been studied by over 20 years and they find a wide range of applications in computer sciences and in cryptography. In this paper we focus on explicit constructions for perfect hash families using combinatorial methods. We present many recursive constructions which result in a large number of improved parameters for perfect hash families. The paper also includes extensive tables for parameters with t = 3, 4, 5, 6 of newly constructed perfect hash families.      

An algebraic approach to Cichelli's perfect hashing

The aim of this paper is to describe a new approach to building minimal and perfect hash functions for a predefined set of keys. Several papers have dealt with this problem and proposed various kinds of functions. This study is based on a function whose address depends both on the letter codes and the letter position in the key, and therefore represents an extension of Cichelli's function. The weights associated with the position are considered to be fixed, and letter code computing is considered to be an interpolation problem. As a result, hash building only requires the solution of an algebraic linear system and then the time complexity is polynomialO(n ³).     

Intersection queries in sets of disks

In this paper we develop some new data structures for storing a set of disks that can answer different types of intersection queries efficiency. If the disks are non-intersecting we obtain a linear size data structure that can report allk disks intersecting a query line segment in timeO(n ⁺ +k), wheren is the number of disks,=log₂(1+5)–1 0.695, and is an arbitrarily small positive constant. If the segment is a full line, the query time becomesO(n +k). For intersecting disks we obtain anO(n logn) size data structure that can answer an intersection query in timeO(n ^2/3 log² n+k). We also present a linear size data structure for ray shooting queries, whose query time isO(n ).The research of the first two authors was supported by the ESPRIT Basic Research Action No. 3075 (project ALCOM). The work of the third author was supported byDimacs (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center — NSF-STC88-09648.     

The dominating set problem is fixed parameter tractable for graphs of bounded genus

We describe an algorithm for the dominating set problem with time complexity O((4g+40)^kn²) for graphs of bounded genus g1, where k is the size of the set. It has previously been shown that this problem is fixed parameter tractable for planar graphs. We give a simpler proof for the previous O(8^kn²) result for planar graphs. Our method is a refinement of the earlier techniques.     

Perfect matchings in random uniform hypergraphs

Let ??_k(n, p) be the random k‐uniform hypergraph on V = [n] with edge probability p. Motivated by a theorem of Erd?s and Rényi 7 regarding when a random graph G(n, p) = ??₂(n, p) has a perfect matching, the following conjecture may be raised. (See J. Schmidt and E. Shamir 16 for a weaker version.) Conjecture. Let k|n for fixed k ≥ 3, and the expected degree d(n, p) = p(). Then (Erd?s and Rényi 7 proved this for G(n, p).) Assuming d(n, p)/n^1/2 → ∞, Schmidt and Shamir 16 were able to prove that ??_k(n, p) contains a perfect matching with probability 1 ? o(1). Frieze and Janson 8 showed that a weaker condition d(n, p)/n^1/3 → ∞ was enough. In this paper, we further weaken the condition to A condition for a similar problem about a perfect triangle packing of G(n, p) is also obtained. A perfect triangle packing of a graph is a collection of vertex disjoint triangles whose union is the entire vertex set. Improving a condition p ≥ cn^?2/3+1/15 of Krivelevich 12 , it is shown that if 3|n and p ? n^?2/3+1/18, then © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 23: 111–132, 2003     

A select and insert sorting algorithm

A general sorting algorithm, having the well knownO(n ²) algorithmsStraight Insertion Sort andSelection Sort as special cases, is described. This algorithm is analyzed in the case that certain choices in the algorithm are done randomly, and this yields an algorithm that has an average complexity ofO(n ^1.5) and a worst case complexity ofO(n ²). However, making random choices (by some random number generator) is time consuming, and a simple quasi-random scheme is therefore implemented. Test runs indicate that also this version has average complexity ofO(n ^1.5), and it even seems to perform better than the version using real random choices (even if we disregard the time used for the random choices). This version also needs very little administrative overhead, and it therefore compares favourably to many other sorting algorithms for small and medium sized arrays.     

A superfast algorithm for multi-dimensional Padé systems

For a vector ofk+1 matrix power series, a superfast algorithm is given for the computation of multi-dimensional Padé systems. The algorithm provides a method for obtaining matrix Padé, matrix Hermite Padé and matrix simultaneous Padé approximants. When the matrix power series is normal or perfect, the algorithm is shown to calculate multi-dimensional matrix Padé systems of type (n ₀,...,n _k ) inO(n · log²n) block-matrix operations, where n=n ₀+...+n _k . Whenk=1 and the power series is scalar, this is the same complexity as that of other superfast algorithms for computing Padé systems. Whenk>1, the fastest methods presently compute these matrix Padé approximants with a complexity ofO(n²). The algorithm succeeds also in the non-normal and non-perfect case, but with a possibility of an increase in the cost complexity.Supported in part by NSERC grant No. A8035.Partially supported by NSERC operating grant No. 6194.     

Galerkin approximation for elliptic PDEs on spheres

We discuss a Galerkin approximation scheme for the elliptic partial differential equation -Δu+ω²u=f on SⁿRⁿ⁺¹. Here Δ is the Laplace–Beltrami operator on Sⁿ, ω is a non-zero constant and f belongs to C^2k-2(Sⁿ), where kn/4+1, k is an integer. The shifts of a spherical basis function φ with φH^τ(Sⁿ) and τ>2kn/2+2 are used to construct an approximate solution. An H¹(Sⁿ)-error estimate is derived under the assumption that the exact solution u belongs to C^2k(Sⁿ).     

On ε‐biased generators in NC0

Cryan and Miltersen (Proceedings of the 26th Mathematical Foundations of Computer Science, 2001, pp. 272–284) recently considered the question of whether there can be a pseudorandom generator in NC⁰, that is, a pseudorandom generator that maps n‐bit strings to m‐bit strings such that every bit of the output depends on a constant number k of bits of the seed. They show that for k = 3, if m ≥ 4n + 1, there is a distinguisher; in fact, they show that in this case it is possible to break the generator with a linear test, that is, there is a subset of bits of the output whose XOR has a noticeable bias. They leave the question open for k ≥ 4. In fact, they ask whether every NC⁰ generator can be broken by a statistical test that simply XORs some bits of the input. Equivalently, is it the case that no NC⁰ generator can sample an ε‐biased space with negligible ε? We give a generator for k = 5 that maps n bits into cn bits, so that every bit of the output depends on 5 bits of the seed, and the XOR of every subset of the bits of the output has bias 2. For large values of k, we construct generators that map n bits to bits such that every XOR of outputs has bias . We also present a polynomial‐time distinguisher for k = 4,m ≥ 24n having constant distinguishing probability. For large values of k we show that a linear distinguisher with a constant distinguishing probability exists once m ≥ Ω(2^kn^?k/2?). Finally, we consider a variant of the problem where each of the output bits is a degree k polynomial in the inputs. We show there exists a degree k = 2 pseudorandom generator for which the XOR of every subset of the outputs has bias 2^?Ω(n) and which maps n bits to Ω(n²) bits. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006     

On the Chromatic Number of the Square of the Kneser Graph <Emphasis Type="Italic">K</Emphasis>(2<Emphasis Type="Italic">k</Emphasis>+1, <Emphasis Type="Italic">k</Emphasis>)

The Kneser graph K(n, k) is the graph whose vertices are the k-element subsets of an n-element set, with two vertices adjacent if the sets are disjoint. The chromatic number of the Kneser graph K(n, k) is n–2k+2. Zoltán Füredi raised the question of determining the chromatic number of the square of the Kneser graph, where the square of a graph is the graph obtained by adding edges joining vertices at distance at most 2. We prove that (K²(2k+1, k))4k when k is odd and (K²(2k+1, k))4k+2 when k is even. Also, we use intersecting families of sets to prove lower bounds on (K²(2k+1, k)), and we find the exact maximum size of an intersecting family of 4-sets in a 9-element set such that no two members of the family share three elements.This work was partially supported by NSF grant DMS-0099608Final version received: April 23, 2003     

The order dimension of two levels of the Boolean lattice

LetB _n(s, t) denote the partially ordered set consisting of alls-subsets andt-subsets of ann-element underlying set where these sets are ordered by inclusion. Answering a question of Trotter we prove that dim(B _n(k, n–k))=n–2 for 3k<(1/7)n ^1/3. The proof uses extremal hypergraph theory.     

The Characterization of n ir as a Multiplicative Function

the following assertion is proved. If f is a completely multiplicative function taking values of modulus 1, such that the set of limit points of has k 3 distinct values, then f(n) = n ^ir F(n) with some r R, and F ^k(n) = 1 for every n.     

On the code generated by the incidence matrix of points and k-spaces in and its dual

In this paper, we study the p-ary linear code C_k(n,q), q=p^h, p prime, h1, generated by the incidence matrix of points and k-dimensional spaces in PG(n,q). For kn/2, we link codewords of C_k(n,q)C_k(n,q) of weight smaller than 2q^k to k-blocking sets. We first prove that such a k-blocking set is uniquely reducible to a minimal k-blocking set, and exclude all codewords arising from small linear k-blocking sets. For k<n/2, we present counterexamples to lemmas valid for kn/2. Next, we study the dual code of C_k(n,q) and present a lower bound on the weight of the codewords, hence extending the results of Sachar [H. Sachar, The F_p span of the incidence matrix of a finite projective plane, Geom. Dedicata 8 (1979) 407–415] to general dimension.     

The Parallel Simplicity of Compaction and Chaining

Given a set of values x₁, x₂,..., x_n, of which k are nonzero, the compaction problem is the problem of moving the nonzero elements into the first k consecutive memory locations. The chaining problem asks that the nonzero elements be put into a linked list. One can in addition require that the elements remain in the same order, leading to the problems of ordered compaction and ordered chaining, respectively. This paper introduces a technique involving perfect hash functions that leads to a deterministic algorithm for ordered compaction running on a CRCW PRAM in time O(log k/log log n) using n processors. A matching lower bound for unordered compaction is given. The ordered chaining problem is shown to be solvable in time O(α(k)) with n processors (where α is a functional inverse of Ackermann′s function) and unordered chaining is shown to he solvable in constant time with n processors when k < n^{1/4− ε}.     

On the Complexity of Partial Order Properties

The recognition complexity of ordered set properties is considered in terms of how many questions must be put to an adversary to decide if an unknown partial order has the prescribed property. We prove a lower bound of order n ² for properties that are characterized by forbidden substructures of fixed size. For the properties being connected, and having exactly k comparable pairs, k n ² / 4 we show that the recognition complexity is (n\choose 2). The complexity of interval orders is exactly (n\choose 2) - 1. We further establish bounds for being a lattice, being of height k and having width k.     

Space Efficient Suffix Trees

We give first the representation of a suffix tree that uses n lg n + O(n) bits of space and supports searching for a pattern string in the given text (from a fixed size alphabet) in O(m) time, where n is the size of the text and m is the length of the pattern. The structure is quite simple and answers a question raised by Muthukrishnan (in Proceedings of the FST and TCS Preconference Workshop on Randomization, 1997, pp. 23–27). Previous compact representations of suffix trees had either a higher lower order term in space and had some expectation assumption or required more time for searching. When the size of the alphabet k is not viewed as a constant, this structure can be modified to use the same space but take O(m lg k) time for string searching or to use an additional O(n lg k) bits but take the same O(m) time for searching. We then give several index structures for binary texts, with less space including

• a structure that uses a suffix array (lg  bits) and an additional () bits,

• an indexing structure that takes bits of space, and

• an ( lg ) bit structure which answers in () time, the decision question of whether a given pattern of length occurs in the text.

Each of these structures uses a different technique, either in the storage scheme or in the search algorithm, in reducing the space requirement. The first one uses a suffix array, a sparse suffix tree, and a table structure. Finding all the occurrences of a pattern using this structure takes O(m + s) time, where s is the number of occurrences of the pattern in the text. The second structure constructs a sparse suffix tree for all the suffixes that start with the bit that occurs more times in the given binary text. The last structure uses an iterative algorithm to search for the pattern. This structure is the first o(n lg n) bit index to support the decision version of indexing queries in time linear in the length of the pattern. But this does not support the general indexing queries where we want to find the position of the occurrence of the pattern.Our main contribution is the development of techniques to use the succinct tree representation through balanced parentheses for suffix trees.     

On the uniqueness of a Walsh series converging on subsequences of partial sum

We show that if a Walsh series whose coefficients tend towards zero is such that the subsequence of its partial sums indexed by n_k, where n_k satisfies the condition 2^k–1k2^k (k=0, 1, 2, ...), tends everywhere, except possibly for a denumerable set, towards a bounded functionf(x), then this series is the Fourier series of the functionf(x).Translated from Matematicheskie Zametki, Vol. 16, No. 1, pp. 27–32, July, 1974.