Transformational classes of grammars

Given two Chomsky grammars G and \-G, a homomorphism φ from G to \-G is, roughly speaking, a map which assigns to every derivation of G a derivation of \-G in such a manner that φ is uniquely determined by its restriction to the set of productions of G. Two grammars are contained in the same transformational class, if the one can be transformed into the other by a sequence of homomorphisms. If two grammars are related in such a manner, then there are two relations, one concerning the words of the languages generated and the other regarding the derivations of these words. We establish several classifications of context-free grammars in transformational classes which are recursively solvable

Capital process and optimality properties of a Bayesian Skeptic in coin-tossing games

We study capital process behavior in the fair-coin game and biased-coin games in the framework of the game-theoretic probability of Shafer and Vovk (2001). We show that if Skeptic uses a Bayesian strategy with a beta prior, the capital process is lucidly expressed in terms of the past average of Reality's moves. From this it is proved that the Skeptic's Bayesian strategy weakly forces the strong law of large numbers (SLLN) with the convergence rate of O(\sqrt{\log n/n})$ and if Reality violates SLLN then the exponential growth rate of the capital process is very accurately described in terms of the Kullback divergence between the average of Reality's moves when she violates SLLN and the average when she observes SLLN. We also investigate optimality properties associated with Bayesian strategy

Korkin-Zolotarev bases and successive minima of a lattice and its reciprocal lattice

Wetensch. publicatieFaculteit der Wiskunde en Natuurwetenschappe

Solving the Shortest Vector Problem in Lattices Faster Using Quantum Search

By applying Grover's quantum search algorithm to the lattice algorithms of Micciancio and Voulgaris, Nguyen and Vidick, Wang et al., and Pujol and Stehl\'{e}, we obtain improved asymptotic quantum results for solving the shortest vector problem. With quantum computers we can provably find a shortest vector in time $2^{1.799n + o(n)}$, improving upon the classical time complexity of $2^{2.465n + o(n)}$ of Pujol and Stehl\'{e} and the $2^{2n + o(n)}$ of Micciancio and Voulgaris, while heuristically we expect to find a shortest vector in time $2^{0.312n + o(n)}$, improving upon the classical time complexity of $2^{0.384n + o(n)}$ of Wang et al. These quantum complexities will be an important guide for the selection of parameters for post-quantum cryptosystems based on the hardness of the shortest vector problem.Comment: 19 page

Election Verifiability for Helios under Weaker Trust Assumptions

Most electronic voting schemes aim at providing verifiability: voters should trust the result without having to rely on some authorities. Actually, even a prominent voting system like Helios cannot fully achieve verifiability since a dishonest bulletin board may add ballots. This problem is called ballot stuffing. In this paper we give a definition of verifiability in the computational model to account for a malicious bulletin board that may add ballots. Next, we provide a generic construction that transforms a voting scheme that is verifiable against an honest bulletin board and an honest registration authority (weak verifiability) into a verifiable voting scheme under the weaker trust assumption that the registration authority and the bulletin board are not simultaneously dishonest (strong verifiability). This construction simply adds a registration authority that sends private credentials to the voters, and publishes the corresponding public credentials. We further provide simple and natural criteria that imply weak verifiability. As an application of these criteria, we formally prove the latest variant of Helios by Bernhard, Pereira and Warinschi weakly verifiable. By applying our generic construction we obtain a Helios-like scheme that has ballot privacy and strong verifiability (and thus prevents ballot stuffing). The resulting voting scheme, Helios-C, retains the simplicity of Helios and has been implemented and tested

Gradual sub-lattice reduction and a new complexity for factoring polynomials

We present a lattice algorithm specifically designed for some classical applications of lattice reduction. The applications are for lattice bases with a generalized knapsack-type structure, where the target vectors are boundably short. For such applications, the complexity of the algorithm improves traditional lattice reduction by replacing some dependence on the bit-length of the input vectors by some dependence on the bound for the output vectors. If the bit-length of the target vectors is unrelated to the bit-length of the input, then our algorithm is only linear in the bit-length of the input entries, which is an improvement over the quadratic complexity floating-point LLL algorithms. To illustrate the usefulness of this algorithm we show that a direct application to factoring univariate polynomials over the integers leads to the first complexity bound improvement since 1984. A second application is algebraic number reconstruction, where a new complexity bound is obtained as well

Universal fluctuations in subdiffusive transport

Subdiffusive transport in tilted washboard potentials is studied within the fractional Fokker-Planck equation approach, using the associated continuous time random walk (CTRW) framework. The scaled subvelocity is shown to obey a universal law, assuming the form of a stationary Levy-stable distribution. The latter is defined by the index of subdiffusion alpha and the mean subvelocity only, but interestingly depends neither on the bias strength nor on the specific form of the potential. These scaled, universal subvelocity fluctuations emerge due to the weak ergodicity breaking and are vanishing in the limit of normal diffusion. The results of the analytical heuristic theory are corroborated by Monte Carlo simulations of the underlying CTRW

Accelerating lattice reduction with FPGAs

International audienceWe describe an FPGA accelerator for the Kannan­–Fincke­–Pohst enumeration algorithm (KFP) solving the Shortest Lattice Vector Problem (SVP). This is the first FPGA implementation of KFP specifically targeting cryptographically relevant dimensions. In order to optimize this implementation, we theoretically and experimentally study several facets of KFP, including its efficient parallelization and its underlying arithmetic. Our FPGA accelerator can be used for both solving stand-alone instances of SVP (within a hybrid CPU­–FPGA compound) or myriads of smaller dimensional SVP instances arising in a BKZ-type algorithm. For devices of comparable costs, our FPGA implementation is faster than a multi-core CPU implementation by a factor around 2.12