Showing papers on "Las Vegas algorithm published in 2017"

Dynamic Minimum Spanning Forest with Subpolynomial Worst-Case Update Time

Abstract: We present a Las Vegas algorithm for dynamically maintaining a minimum spanning forest of an n-node graph undergoing edge insertions and deletions. Our algorithm guarantees an O(n^{o(1)})} worst-case} update time with high probability. This significantly improves the two recent Las Vegas algorithms by Wulff-Nilsen \cite{Wulff-Nilsen16a} with update time O(n^{0.5-≥ilon}) for some constant ≥ilon 0 and, independently, by Nanongkai and Saranurak \cite{NanongkaiS16} with update time O(n^{0.494}) (the latter works only for maintaining a spanning forest).Our result is obtained by identifying the common framework that both two previous algorithms rely on, and then improve and combine the ideas from both works. There are two main algorithmic components of the framework that are newly improved and critical for obtaining our result. First, we improve the update time from O(n^{0.5-≥ilon}) in \cite{Wulff-Nilsen16a} to O(n^{o(1)}) for decrementally removing all low-conductance cuts in an expander undergoing edge deletions. Second, by revisiting the contraction technique by Henzinger and King \cite{HenzingerK97b} and Holm et al. \cite{HolmLT01, we show a new approach for maintaining a minimum spanning forest in connected graphs with very few (at most (1+o(1))n) edges. This significantly improves the previous approach in \cite{Wulff-Nilsen16a, NanongkaiS16} which is based on Fredericksons 2-dimensional topology tree \cite{Frederickson85} and illustrates a new application to this old technique.

Naming a channel with beeps

Abstract: We consider a communication channel in which the only possible communication mode is transmitting beeps, which reach all the nodes instantaneously. Nodes are anonymous, in that they do not have any individual identifiers. The algorithmic goal is to randomly assign names to the nodes in such a manner that the names make a contiguous segment of positive integers starting from $1$. We give a Las Vegas naming algorithm for the case when the number of nodes $n$ is known, and a Monte Carlo algorithm for the case when the number of nodes $n$ is not known. The algorithms are provably optimal with respect to the expected time $O(n\log n)$, the number of used random bits $O(n\log n)$, and the probability of error.

Dynamic Minimum Spanning Forest with Subpolynomial Worst-case Update Time

Abstract: We present a Las Vegas algorithm for dynamically maintaining a minimum spanning forest of an $n$-node graph undergoing edge insertions and deletions. Our algorithm guarantees an $O(n^{o(1)})$ worst-case update time with high probability. This significantly improves the two recent Las Vegas algorithms by Wulff-Nilsen [STOC'17] with update time $O(n^{0.5-\epsilon})$ for some constant $\epsilon>0$ and, independently, by Nanongkai and Saranurak [STOC'17] with update time $O(n^{0.494})$ (the latter works only for maintaining a spanning forest). Our result is obtained by identifying the common framework that both two previous algorithms rely on, and then improve and combine the ideas from both works. There are two main algorithmic components of the framework that are newly improved and critical for obtaining our result. First, we improve the update time from $O(n^{0.5-\epsilon})$ in Wulff-Nilsen [STOC'17] to $O(n^{o(1)})$ for decrementally removing all low-conductance cuts in an expander undergoing edge deletions. Second, by revisiting the "contraction technique" by Henzinger and King [1997] and Holm et al. [STOC'98], we show a new approach for maintaining a minimum spanning forest in connected graphs with very few (at most $(1+o(1))n$) edges. This significantly improves the previous approach in [Wulff-Nilsen STOC'17] and [Nanongkai and Saranurak STOC'17] which is based on Frederickson's 2-dimensional topology tree and illustrates a new application to this old technique.

Sparse suffix tree construction in optimal time and space

Abstract: Suffix tree (and the closely related suffix array) are fundamental structures capturing all substrings of a given text essentially by storing all its suffixes in the lexicographical order. In some applications, such as sparse text indexing, we work with a subset of b interesting suffixes, which are stored in the so-called sparse suffix tree. Because the size of this structure is Θ(b), it is natural to seek a construction algorithm using only O(b) words of space assuming read-only random access to the text. We design a linear-time Monte Carlo algorithm for this problem, hence resolving an open question explicitly stated by Bille et al. [TALG 2016]. The best previously known algorithm by I et al. [STACS 2014] works in O(n log b) time. As opposed to previous solutions, which were based on the divide-and-conquer paradigm, our solution proceeds in n/b rounds. In the r-th round, we consider all suffixes starting at positions congruent to r modulo n/b. By maintaining rolling hashes, we can lexicographically sort all interesting suffixes starting at such positions, and then we can merge them with the already considered suffixes. For efficient merging, we also need to answer LCE queries efficiently (and in small space). By plugging in the structure of Bille et al. [CPM 2015] we obtain O(n + b log b) time complexity. We improve this structure by a recursive application of the so-called difference covers, which then implies a linear-time sparse suffix tree construction algorithm.We complement our Monte Carlo algorithm with a deterministic verification procedure. The verification takes [EQUATION] time, which improves upon the bound of O(n log b) obtained by I et al. [STACS 2014]. This is obtained by first observing that the pruning done inside the previous solution has a rather clean description using the notion of graph spanners with small multiplicative stretch. Then, we are able to decrease the verification time by applying difference covers twice. Combined with the Monte Carlo algorithm, this gives us an [EQUATION]-time and O(b)-space Las Vegas algorithm.

Improved Complexity Bounds for Counting Points on Hyperelliptic Curves.

Abstract: We present a probabilistic Las Vegas algorithm for computing the local zeta function of a hyperelliptic curve of genus $g$ defined over $\mathbb{F}_q$. It is based on the approaches by Schoof and Pila combined with a modeling of the $\ell$-torsion by structured polynomial systems. Our main result improves on previously known complexity bounds by showing that there exists a constant $c>0$ such that, for any fixed $g$, this algorithm has expected time and space complexity $O((\log q)^{cg})$ as $q$ grows and the characteristic is large enough.

A Las Vegas algorithm to solve the elliptic curve discrete logarithm problem

Abstract: In this paper, we describe a new Las Vegas algorithm to solve the elliptic curve discrete logarithm problem. The algorithm depends on a property of the group of rational points of an elliptic curve and is thus not a generic algorithm. The algorithm that we describe has some similarities with the most powerful index-calculus algorithm for the discrete logarithm problem over a finite field.

Functional Decomposition using Principal Subfields

Abstract: Let $f\in K(t)$ be a univariate rational function. It is well known that any non-trivial decomposition $g \circ h$, with $g,h\in K(t)$, corresponds to a non-trivial subfield $K(f(t))\subsetneq L \subsetneq K(t)$ and vice-versa. In this paper we use the idea of principal subfields and fast subfield-intersection techniques to compute the subfield lattice of $K(t)/K(f(t))$. This yields a Las Vegas algorithm with improved complexity and better run times for finding all non-equivalent complete decompositions of $f$.