Randomness is a fundamental feature in nature and a valuable resource for applications ranging from cryptography and gambling to numerical simulation of physical and biological systems. Ran-dom numbers, however, are difficult to characterize mathematically [1], and their generation must rely on an unpredictable physical process [2, 3, 4, 5, 6]. Inaccuracies in the theoretical modelling of such processes or failures of the devices, possibly due to adversarial attacks, limit the reliability of random number generators in ways that are difficult to control and detect. Here, inspired b
A physical random number generator based on the intrinsic randomness of quantum mechanics is describ...
Abstract—The use of random numbers is essential in randomized algorithms, and many statistical metho...
What does it mean to have random numbers? Without understanding where a group of numbers came from, ...
The ability to produce random numbers is an important aspect of many cryptographic applications. Thi...
Winner, ScienceGood random number generators (RNGs) are required for many applications in science an...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
International audienceRandom number generators (RNGs) are computational or physical functions genera...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
International audienceThe issue of random number generation is crucial for the implementation of cry...
Abstract Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulati...
In many applications, for example cryptography and Monte Carlo simulation, there is need for random ...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
To simulate chance occurrences, a computer can't literally toss a coin or roll a die. Instead, ...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
Many computer simulations use random number generators and since most computer languages have a buil...
A physical random number generator based on the intrinsic randomness of quantum mechanics is describ...
Abstract—The use of random numbers is essential in randomized algorithms, and many statistical metho...
What does it mean to have random numbers? Without understanding where a group of numbers came from, ...
The ability to produce random numbers is an important aspect of many cryptographic applications. Thi...
Winner, ScienceGood random number generators (RNGs) are required for many applications in science an...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
International audienceRandom number generators (RNGs) are computational or physical functions genera...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
International audienceThe issue of random number generation is crucial for the implementation of cry...
Abstract Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulati...
In many applications, for example cryptography and Monte Carlo simulation, there is need for random ...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
To simulate chance occurrences, a computer can't literally toss a coin or roll a die. Instead, ...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
Many computer simulations use random number generators and since most computer languages have a buil...
A physical random number generator based on the intrinsic randomness of quantum mechanics is describ...
Abstract—The use of random numbers is essential in randomized algorithms, and many statistical metho...
What does it mean to have random numbers? Without understanding where a group of numbers came from, ...