Results 251 to 260 of about 20,745 (303)

Light-Induced Entropy for Secure Vision. [PDF]

Adv Mater
Seo J, Kang S, Kim C, Park T, Yoo Y, Kim YK, Shin W, Jang BC, Kim YJ, Yoo H.   +9 more
europepmc   +1 more source

Scalable Boltzmann generators for equilibrium sampling of large-scale materials. [PDF]

Nat Commun
Schebek M, Noé F, Rogal J.
europepmc   +1 more source

Preface to the Special Issue: Quantum Probability and Randomness V. [PDF]

Entropy (Basel)
Khrennikov A, Svozil K.
europepmc   +1 more source

Time-optimal trajectory planning algorithm for robotic arms based on ADFMSSA chaotic optimization. [PDF]

Sci Rep
Yue G, Wan-Ting W, Yu-Han L, Guo-Lan W, Hai-Fang L.   +4 more
europepmc   +1 more source

Aim high, stay private: differentially private synthetic data enables public release of behavioral health information with high utility. [PDF]

JAMIA Open
Ghasemizade M, Lovato J, Danforth C, Dodds PS, Bloomfield LSP, Price M, Near J.   +6 more
europepmc   +1 more source

Testing parallel random number generators

Parallel Computing, 2003
Monte Carlo computations are considered easy to parallelize. However, the results can be adversely affected by defects in the parallel pseudorandom number generator used.
Ashok Srinivasan, Michael Mascagni, D M Ceperley   +2 more
exaly   +2 more sources

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Random number generators are chaotic

ACM SIGPLAN Notices, 1989
We observe that pseudo-random number generators, familiar to all programmers, are examples of deterministic chaotic dynamical systems. We discuss the implications of this finding and compare computer generation of pseudo-random numbers to the theoretical ideal of a (noncomputable) random sequence.
Charles Herring, Julian I. Palmore
openaire   +1 more source

Random Number Generation [PDF]

, 2011
The fields of probability and statistics are built over the abstract concepts of probability space and random variable. This has given rise to elegant and powerful mathematical theory, but exact implementation of these concepts on conventional computers seems impossible.
openaire   +2 more sources

Uniform Random Number Generators

Journal of the ACM, 1965
Abstract : This paper discusses the testing of methods for generating uniform numbers in a computer--the commonly used multiplicative and mixed congruential generators as well as two methods. Tests proposed here are more stringent than those usually applied, because the usual tests for randomness have passed several of the commonly used pprocedures ...
M. Donald MacLaren, George Marsaglia
openaire   +1 more source