The weight distributions of cyclic codes with two zeros and zeta functions

We consider the weight distribution of the binary cyclic code of length 2ⁿ−1$2^n-1$ with two zeros α^a,α^b${\alpha }^a,{\alpha }^b$. Our proof gives information in terms of the zeta function of an associated variety. We carry out an explicit determination of the weight distribution in two cases, for the cyclic codes with zeros α³,α⁵${\alpha }^3,{\alpha }^5$ and α,α¹¹$\alpha ,{\alpha }^{11}$. These are the smallest cases of two infinite families where finding the weight distribution is an open problem. Finally, an interesting application of our methods is that we can prove that these two codes have the same weight distribution for all odd n$n$.     

Alternative proof of the Lyndon–Schützenberger Theorem

Some observations on products of primitive words are discussed. By these results, alternative proof is given for the Lyndon–Schützenberger Theorem, which says that every solution of the equation a^mbⁿ=c^k$a^m{b}^n=c^k$ over Σ^*${\Sigma }^{*}$ is trivial.     

OptQC: An optimized parallel quantum compiler

The software package Qcompiler (Chen and Wang 2013) provides a general quantum compilation framework, which maps any given unitary operation into a quantum circuit consisting of a sequential set of elementary quantum gates. In this paper, we present an extended software OptQC  , which finds permutation matrices P$P$ and Q$Q$ for a given unitary matrix U$U$ such that the number of gates in the quantum circuit of U=Q^TP^TU^′PQ$U=Q^T{P}^T{U}^{\prime }PQ$ is significantly reduced, where U^′$U^{\prime }$ is equivalent to U$U$ up to a permutation and the quantum circuit implementation of each matrix component is considered separately. We extend further this software package to make use of high-performance computers with a multiprocessor architecture using MPI. We demonstrate its effectiveness in reducing the total number of quantum gates required for various unitary operators.     

Rational two-parameter families of spheres and rational offset surfaces

The present paper investigates two-parameter families of spheres in R³${\mathbb{R}}^3$ and their corresponding two-dimensional surfaces Φ$\Phi$ in R⁴${\mathbb{R}}^4$. Considering a rational surface Φ$\Phi$ in R⁴${\mathbb{R}}^4$, the envelope surface Ψ$\Psi$ of the corresponding family of spheres in R³${\mathbb{R}}^3$ is typically non-rational. Using a classical sphere-geometric approach, we prove that the envelope surface Ψ$\Psi$ and its offset surfaces admit rational parameterizations if and only if Φ$\Phi$ is a rational sub-variety of a rational isotropic hyper-surface in R⁴${\mathbb{R}}^4$. The close relation between the envelope surfaces Ψ$\Psi$ and rational offset surfaces in R³${\mathbb{R}}^3$ is elaborated in detail. This connection leads to explicit rational parameterizations for all rational surfaces Φ$\Phi$ in R⁴${\mathbb{R}}^4$ whose corresponding two-parameter families of spheres possess envelope surfaces admitting rational parameterizations. Finally we discuss several classes of surfaces sharing this property.     

Faster two-dimensional pattern matching with rotations

The most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of O(n²m³)$\mathrm{O}(n^2{m}^3)$, where the size of the text is n×n$n\times n$ and the size of the pattern is m×m$m\times m$. In this paper we present a new algorithm for the problem whose running time is O(n²m²)$\mathrm{O}(n^2{m}^2)$.     

A state-space search approach for optimizing reliability and cost of execution in distributed sensor networks

Sensor networks are increasingly being used for applications which require fast processing of data, such as multimedia processing and collaboration among sensors to relay observed data to a base station (BS). Distributed computing can be used on a sensor network to reduce the completion time of a task (an application) and distribute the energy consumption equitably across all sensors, so that certain sensors do not die out faster than the others. The distribution of task modules to sensors should consider not only the time and energy savings, but must also improve reliability of the entire task execution. We formulate the above as an optimization problem, and use the A^∗$A^{\ast }$ algorithm with improvements to determine an optimal static allocation of modules among a set of sensors. We also suggest a faster algorithm, called the greedy A^∗$A^{\ast }$ algorithm, if a sub-optimal solution is sufficient. Both algorithms have been simulated, and the results have been compared in terms of energy savings, decrease in completion time of the task, and the deviation of the sub-optimal solution from the optimal one. The sub-optimal solution required 8%–35% less computation, at the cost of 2.5%–15% deviation from the optimal solution in terms of average energy spent per sensor node. Both the A^∗$A^{\ast }$ and greedy A^∗$A^{\ast }$ algorithms have been shown to distribute energy consumption more uniformly across sensors than centralized execution. The greedy A^∗$A^{\ast }$ algorithm is found to be scalable, as the number of evaluations in determining the allocation increases linearly with the number of sensors.     

On the size of Boyer–Moore automata

In this work we study the size of Boyer–Moore automata introduced in Knuth, Morris & Pratt’s famous paper on pattern matching. We experimentally show that a finite class of binary patterns produce very large Boyer–Moore automata, and find one particular case which we conjecture, generates automata of size Ω(m⁶)$\Omega \left(m^6\right)$. Further experimental results suggest that the maximal size could be a polynomial of O(m⁷)$O\left(m^7\right)$, or even an exponential O(2^0.4m)$O\left(2^{0.4m}\right)$, where m$m$ is the length of the pattern.     

Conjunctive query evaluation by search-tree revisited

The most natural and perhaps most frequently used method for testing membership of an individual tuple in a conjunctive query is based on searching trees of partial solutions, or search-trees. We investigate the question of evaluating conjunctive queries with a time-bound guarantee that is measured as a function of the size of the optimal search-tree. We provide an algorithm that, given a database D$D$, a conjunctive query Q$Q$, and a tuple a$a$, tests whether Q(a)$Q\left(a\right)$ holds in D$D$ in time bounded by a polynomial in (sn)^logk(sn)^loglogn${\left(sn\right)}^{logk}{\left(sn\right)}^{loglogn}$ and n^r$n^r$, where n$n$ is the size of the domain of the database, k$k$ is the number of bound variables of the conjunctive query, s$s$ is the size of the optimal search-tree, and r$r$ is the maximum arity of the relations. In many cases of interest, this bound is significantly smaller than the n^O(k)$n^{O\left(k\right)}$ bound provided by the naive search-tree method. Moreover, our algorithm has the advantage of guaranteeing the bound for any given conjunctive query. In particular, it guarantees the bound for queries that admit an equivalent form that is much easier to evaluate, even when finding such a form is an NP-hard task. Concrete examples include the conjunctive queries that can be non-trivially folded into a conjunctive query of bounded size or bounded treewidth. All our results translate to the context of constraint-satisfaction problems via the well-publicized correspondence between both frameworks.     

Digital Steiner sets and Matheron semi-groups

There are various ways to define digital convexity in Zⁿ$Z^n$. The proposed approach focuses on structuring elements (and not the sets under study), whose digital versions should allow to construct hierarchies of operators satisfying Matheron semi-groups law _γλγμ=_γmax(λ,_μ)${\gamma }_{\lambda }{\gamma }_{\mu }={\gamma }_{\max (\lambda \text{,}\mu )}$, where λ$\lambda$ is a size factor. In Rⁿ$R^n$ the convenient class is the Steiner one. Its elements are Minkowski sums of segments. We prove that it admits a digital equivalent when the segments of Zⁿ$Z^n$ are Bezout. The conditions under which the Steiner sets are convex in Zⁿ$Z^n$, and are connected, are established. The approach is then extended to structuring elements that vary according to the law of perspective, and also to anamorphoses, so that the digital Steiner class and its properties can extend to digital spaces as a sphere or a torus.     

A parameterized view on matroid optimization problems

Matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. However, several natural matroid problems, such as 3-matroid intersection, are NP-hard. Here we investigate these problems from the parameterized complexity point of view: instead of the trivial n^O(k)$n^{O\left(k\right)}$ time brute force algorithm for finding a k$k$-element solution, we try to give algorithms with uniformly polynomial (i.e., f(k)⋅n^O(1)$f\left(k\right)\cdot n^{O\left(1\right)}$) running time. The main result is that if the ground set of a represented linear matroid is partitioned into blocks of size ?$?$, then we can determine in randomized time f(k,?)⋅n^O(1)$f(k,?)\cdot n^{O\left(1\right)}$ whether there is an independent set that is the union of k$k$ blocks. As a consequence, algorithms with similar running time are obtained for other problems such as finding a k$k$-element set in the intersection of ?$?$ matroids, or finding k$k$ terminals in a network such that each of them can be connected simultaneously to the source by ?$?$ disjoint paths.     

State-complexity hierarchies of uniform languages of alphabet-size length

We study the state complexity of certain simple languages. If A$A$ is an alphabet of k$k$ letters, then a k$k$-language   is a nonempty set of words of length k$k$, that is, a uniform language of length k$k$. We show that the minimal state complexity of a k$k$-language is k+2$k+2$, and the maximal, (k^k−1−1)/(k−1)+2^k+1$(k^{k-1}-1)/(k-1)+2^k+1$. We prove constructively that, for every i$i$ between the minimal and maximal bounds, there is a language of state complexity i$i$. We introduce a class of automata accepting sets of words that are permutations of A$A$; these languages define a complete hierarchy of complexities between k²−k+3$k^2-k+3$ and 2^k+1$2^k+1$. The languages of another class of automata, based on k$k$-ary trees, define a complete hierarchy of complexities between 2^k+1$2^k+1$ and (k^k−1−1)/(k−1)+2^k+1$(k^{k-1}-1)/(k-1)+2^k+1$. This provides new examples of uniform languages of maximal complexity.     

Computational topology for isotopic surface reconstruction

New computational topology techniques are presented for surface reconstruction of 2-manifolds with boundary, while rigorous proofs have previously been limited to surfaces without boundary. This is done by an intermediate construction of the envelope   (as defined herein) of the original surface. For any compact C²$C^2$-manifold M$M$ embedded in R³${\mathbf{R}}^3$, it is shown that its envelope is C^1,1$C^{1,1}$. Then it is shown that there exists a piecewise linear (PL) subset of the reconstruction of the envelope that is ambient isotopic to M$M$, whenever M$M$ is orientable. The emphasis of this paper is upon the formal mathematical proofs needed for these extensions. (Practical application examples have already been published in a companion paper.) Possible extensions to non-orientable manifolds are also discussed. The mathematical exposition relies heavily on known techniques from differential geometry and topology, but the specific new proofs are intended to be sufficiently specialized to prompt further algorithmic discoveries.     

An efficient construction of one-to-many node-disjoint paths in folded hypercubes

A folded hypercube is basically a hypercube with additional links augmented, where the additional links connect all pairs of nodes with longest distance in the hypercube. In an n$n$-dimensional folded hypercube, it has been shown that n+1$n+1$ node-disjoint paths from one source node to other n+1$n+1$ (mutually) distinct destination nodes, respectively, can be constructed in O(n⁴)$O\left(n^4\right)$ time so that their maximal length is not greater than ⌈n/2⌉+1$\lceil n/2\rceil +1$, where n+1$n+1$ is the connectivity and ⌈n/2⌉$\lceil n/2\rceil$ is the diameter. Besides, their maximal length is minimized in the worst case. In this paper, we further show that by minimizing the computations of minimal routing functions, these node-disjoint paths can be constructed in O(n³)$O\left(n^3\right)$ time, which is more efficient, and is hard to be reduced because it must take O(n³)$O\left(n^3\right)$ time to compute a minimal routing function by solving a corresponding maximum weighted bipartite matching problem with the best known algorithm.     

Swapping a failing edge of a shortest paths tree by minimizing the average stretch factor

We consider a two-edge connected, undirected graph G=(V,E)$G=(V,E)$, with n$n$ nodes and m$m$ non-negatively real weighted edges, and a single source shortest paths tree (SPT) T$T$ of G$G$ rooted at an arbitrary node r$r$. If an edge in T$T$ is temporarily removed, it makes sense to reconnect the nodes disconnected from the root by adding a single non-tree edge, called a swap edge  , instead of rebuilding a new optimal SPT from scratch. In the past, several optimality criteria have been considered to select a best possible swap edge. In this paper we focus on the most prominent one, that is the minimization of the average distance between the root and the disconnected nodes. To this respect, we present an O(mlog²n)$O\left(m{log}^{2}n\right)$ time and O(m)$O\left(m\right)$ space algorithm to find a best swap edge for every edge of T$T$, thus improving for m=o(n²/log²n)$m=o(n^2/{log}^{2}n)$ the previously known O(n²)$O\left(n^2\right)$ time and space complexity algorithm.