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Related papers: An improvement of a cryptanalysis algorithm

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Randomness is both a useful way to model natural systems and a useful tool for engineered systems, e.g. in computation, communication and control. Fully random transformations require exponential time for either classical or quantum…

Quantum Physics · Physics 2016-05-04 Fernando G. S. L. Brandao , Aram W. Harrow , Michal Horodecki

Differential cryptanalysis is one of the most popular methods in attacking block ciphers. However, there still some limitations in traditional differential cryptanalysis. On the other hand, researches of quantum algorithms have made great…

Quantum Physics · Physics 2015-12-01 Hong-Wei Li , Li Yang

We introduce a computational problem of distinguishing between the output of an ideal coarse-grained boson sampler and the output of a true random number generator, as a resource for cryptographic schemes, which are secure against…

Quantum Physics · Physics 2022-11-29 Georgios M. Nikolopoulos

The fundamental principles of quantum mechanics, such as its probabilistic nature, allow for the theoretical ability of quantum computers to generate statistically random numbers, as opposed to classical computers which are only able to…

Quantum Physics · Physics 2024-01-24 Owen Root , Maria Becker

We have carried out extensive statistical, bit level and visual tests of several random number generators used in the applications of physics. Two of the generators tested were recently included in a paper by Ferrenberg {\it et al.} (Phys.…

Condensed Matter · Physics 2007-05-23 I. Vattulainen , K. Kankaala , J. Saarinen , T. Ala-Nissila

Nowadays random number generation plays an essential role in technology with important applications in areas ranging from cryptography, which lies at the core of current communication protocols, to Monte Carlo methods, and other…

With the widespread use of communication technologies, cryptosystems are therefore critical to guarantee security over open networks as the Internet. Pseudo-random number generators (PRNGs) are fundamental in cryptosystems and information…

Cryptography and Security · Computer Science 2011-12-06 Jacques M. Bahi , Jean-François Couchot , Christophe Guyeux , Qianxue Wang

Pseudo-random number generators (PRNGs) are widely used in modern computing and are expected to exhibit excellent statistical performance and repeatability. This study evaluates and compares modern PRNGs used in high performance computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-19 Théau Wartel , David R. C. Hill

It is known that quantum computers can speed up Monte Carlo simulation compared to classical counterparts. There are already some proposals of application of the quantum algorithm to practical problems, including quantitative finance. In…

Quantum Physics · Physics 2020-09-02 Koichi Miyamoto , Kenji Shiohara

Chaos and its applications in the field of secure communications have attracted a lot of attention. Chaos-based pseudo-random number generators are critical to guarantee security over open networks as the Internet. We have previously…

Cryptography and Security · Computer Science 2016-11-17 Jacques M. Bahi , Xiaole Fang , Christophe Guyeux , Qianxue Wang

We derive a stochastic gradient algorithm for semidefinite optimization using randomization techniques. The algorithm uses subsampling to reduce the computational cost of each iteration and the subsampling ratio explicitly controls…

Optimization and Control · Mathematics 2011-08-30 Alexandre d'Aspremont

The generation of pseudo-random numbers is one of the interesting problems in Monte Carlo simulations, mostly because the common computer generators produce periodic numbers. We used simple pseudo-random numbers generated with the simplest…

Other Condensed Matter · Physics 2009-11-13 Gaston E. Barberis

We investigate the cryptanalysis of affine ciphers using a hybrid neural network architecture that combines modular arithmetic-aware and statistical feature-based learning. Inspired by recent advances in interpretable neural networks for…

Cryptography and Security · Computer Science 2025-07-22 Vanja Stojanović , Žiga Lesar , CIril Bohak

Monte Carlo simulations are one of the major tools in statistical physics, complex system science, and other fields, and an increasing number of these simulations is run on distributed systems like clusters or grids. This raises the issue…

Other Condensed Matter · Physics 2007-07-03 Heiko Bauke , Stephan Mertens

Quantum computer algorithms can exploit the structure of random satisfiability problems. This paper extends a previous empirical evaluation of such an algorithm and gives an approximate asymptotic analysis accounting for both the average…

Quantum Physics · Physics 2007-05-23 Tad Hogg

Pseudorandom circuits generate quantum states and unitary operators which are approximately distributed according to the unitarily invariant Haar measure. We explore how several design parameters affect the efficiency of pseudo-random…

Quantum Physics · Physics 2009-11-13 Yaakov S. Weinstein , Winton G. Brown , Lorenza Viola

We develop cryptographically secure techniques to guarantee unconditional privacy for respondents to polls. Our constructions are efficient and practical, and are shown not to allow cheating respondents to affect the ``tally'' by more than…

Computational Complexity · Computer Science 2007-05-23 Andris Ambainis , Markus Jakobsson , Helger Lipmaa

Random number generation is a key technology that is useful in a variety of ways. Random numbers are often used to generate keys for data encryption. Random numbers generated at a sufficiently long length can encrypt sensitive data and make…

Hardware Architecture · Computer Science 2022-09-12 Jacob Hammond

Quantum computers are analog devices; thus they are highly susceptible to accumulative errors arising from classical control electronics. Fast operation--as necessitated by decoherence--makes gating errors very likely. In most current…

Quantum Physics · Physics 2009-11-07 Mark Friesen , Robert Joynt , M. A. Eriksson

This note proposes a procedure for enhancing the quality of probabilistic prediction algorithms via betting against their predictions. It is inspired by the success of the conformal test martingales that have been developed recently.

Machine Learning · Computer Science 2021-05-19 Vladimir Vovk
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