Lev N. Shchur

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We present an extensive analysis of long-term statistics of the queries to websites using logs collected on several web caches in Russian academic networks and on US IRCache caches. We check the sensitivity of the statistics to several parameters: (1) duration of data collection, (2) geographical location of the cache server collecting data, and (3) the(More)
We propose methods for constructing high-quality pseudorandom number generators (RNGs) based on an ensemble of hyperbolic automorphisms of the unit two-dimensional torus (Sinai-Arnold map or cat map) while keeping a part of the information hidden. The single cat map provides the random properties expected from a good RNG and is hence an appropriate building(More)
Theoretical description and numerical simulation of an evaporating sessile drop are developed. We jointly take into account the hydrodynamics of an evaporating sessile drop, effects of the thermal conduction in the drop, and the diffusion of vapor in air. A shape of the rotationally symmetric drop is determined within the quasistationary approximation.(More)
Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling through Markov chains with elements of sequential Monte Carlo in the form of population control. While it appears to(More)
The library PRAND for pseudorandom number generation for modern CPUs and GPUs is presented. It contains both single-threaded and multi-threaded realizations of a number of modern and most reliable generators recently proposed and studied in [1, 2, 3, 4, 5] and the efficient SIMD realizations proposed in [6]. One of the useful features for using PRAND in(More)
We investigate the mechanism that leads to systematic deviations in cluster Monte Carlo simulations when correlated pseudo-random numbers are used. We present a simple model, which enables an analysis of the effects due to correlations in several types of pseudo-random-number sequences. This model provides qualitative understanding of the bias mechanism in(More)
In this update, we present the new version of the random number generator (RNG) library RNGSSELIB, which, in particular, contains fast SSE realizations of a number of modern and most reliable generators [1]. The new features are: i) Fortran compatibility and examples of using the library in Fortran; ii) new modern and reliable generators; iii) the abilities(More)
The large-scale simulations in statistical physics use some deterministic procedures to generate a sequence of uniformly distributed (pseudo)random numbers. It is possible to generate 10 numbers per second and 10 numbers in 100 days on the best processors. The widely known linear congruential methods cannot be used in a such simulations on 32-bit computers(More)