English
Related papers

Related papers: A modular framework for randomness extraction base…

200 papers

We consider the problem of estimating the total probability of all symbols that appear with a given frequency in a string of i.i.d. random variables with unknown distribution. We focus on the regime in which the block length is large yet no…

Information Theory · Computer Science 2016-11-15 Aaron B. Wagner , Pramod Viswanath , Sanjeev R. Kulkarni

Randomness is an indispensable resource in modern science and information technology. Fortunately, an experimentally simple procedure exists to generate randomness with well-characterized devices: measuring a quantum system in a basis…

Quantum Physics · Physics 2016-08-24 Le Phuc Thinh , Jean-Daniel Bancal , Eduardo Martin-Martinez

Measuring quantum states provides means to generate genuine random numbers. It has been shown that genuine randomness can be obtained even with an uncharacterized quantum source. In this work, we propose a framework that formalizes the idea…

Quantum Physics · Physics 2019-05-23 Jiajun Ma , Xiao Yuan , Aishwarya Hakande , Xiongfeng Ma

We have introduced in former work the concept of Deep Randomness and its interest to design Unconditionally Secure communication protocols. We have in particular given an example of such protocol and introduced how to design a Deep Random…

Cryptography and Security · Computer Science 2019-01-09 Thibault de Valroger

Quantum coherence is an essential resource to gain advantage over classical physics and technology. Recently, it has been proposed that a low-temperature environment can induce quantum coherence of a spin without an external coherent pump.…

Quantum Physics · Physics 2022-04-20 Artur Slobodeniuk , Tomáš Novotný , Radim Filip

In this work we study the estimation of the density of a totally positive random vector. Total positivity of the distribution of a random vector implies a strong form of positive dependence between its coordinates and, in particular, it…

Statistics Theory · Mathematics 2023-05-10 Ali Zartash , Elina Robeva

In this article, we study a notion of the extraction rate of Turing functionals that translate between notions of randomness with respect to different underlying probability measures. We analyze several classes of extraction procedures: a…

Logic · Mathematics 2021-03-09 Douglas Cenzer , Christopher P. Porter

Random number generators (RNG) based on quantum mechanics are captivating due to their security and unpredictability compared to conventional generators, such as pseudo-random number generators and hardware-random number generators. This…

How much cryptographically-secure randomness can be extracted from a quantum state? This fundamental question probes the absolute limits of quantum random number generation (QRNG) and yet, despite the technological maturity of QRNGs, it…

Quantum Physics · Physics 2024-11-05 Kriss Gutierrez Anco , Tristan Nemoz , Peter Brown

Tensors are a fundamental operation in distributed computing, \emph{e.g.,} machine learning, that are commonly distributed into multiple parallel tasks for large datasets. Stragglers and other failures can severely impact the overall…

Information Theory · Computer Science 2024-10-30 Pedro Soto

We prove that every randomized Boolean function admits a supersimulator: a randomized polynomial-size circuit whose output on random inputs cannot be efficiently distinguished from reality with constant advantage, even by polynomially…

Computational Complexity · Computer Science 2026-04-08 Cynthia Dwork , Pranay Tankala

The non-convexity and intractability of distributionally robust chance constraints make them challenging to cope with. From a data-driven perspective, we propose formulating it as a robust optimization problem to ensure that the…

Optimization and Control · Mathematics 2023-06-23 Zhiping Chen , Wentao Ma , Bingbing Ji

This article presents an efficient algorithm to generate a discrete uniform distribution on a set of $p$ elements using a biased random source for $p$ prime. The algorithm generalizes Von Neumann's method and improves computational…

Probability · Mathematics 2023-01-18 Xiaoyu Lei

The relative power of quantum algorithms, using an adaptive access to quantum devices, versus classical post-processing methods that rely only on an initial quantum data set, remains the subject of active debate. Here, we present evidence…

Quantum Physics · Physics 2025-10-02 Oleksandr Kyriienko , Chukwudubem Umeano , Zoë Holmes

Quantum computers provide an opportunity to efficiently sample from probability distributions that include non-trivial interference effects between amplitudes. Using a simple process wherein all possible state histories can be specified by…

Quantum Physics · Physics 2019-08-22 Davide Provasoli , Benjamin Nachman , Wibe A. de Jong , Christian W Bauer

The Diffie-Hellman key agreement protocol is based on taking large powers of a generator of a prime-order cyclic group. Some generators allow faster exponentiation. We show that to a large extent, using the fast generators is as secure as…

Cryptography and Security · Computer Science 2010-08-02 Boaz Tsaban

A key problem in constrained random verification (CRV) concerns generation of input stimuli that result in good coverage of the system's runs in targeted corners of its behavior space. Existing CRV solutions however provide no formal…

Logic in Computer Science · Computer Science 2020-08-18 Supratik Chakraborty , Aditya A. Shrotri , Moshe Y. Vardi

The ultimate random number generators are those certified to be unpredictable -- including to an adversary. The use of simple quantum processes promises to provide numbers that no physical observer could predict but, in practice, unwanted…

Conformal predictors provide set or functional predictions that are valid under the assumption of randomness, i.e., under the assumption of independent and identically distributed data. The question asked in this paper is whether there are…

Machine Learning · Computer Science 2025-06-10 Vladimir Vovk

This paper proposes strategies for designing a system whose computational model is subject to aleatory and epistemic uncertainty. Aleatory variables, which are caused by randomness in physical parameters, are draws from a possibly unknown…

Methodology · Statistics 2026-02-18 Luis G. Crespo