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We study the problem of extracting random bits from weak sources that are sampled by algorithms with limited memory. This model of small-space sources was introduced by Kamp, Rao, Vadhan and Zuckerman (STOC'06), and falls into a line of…

Computational Complexity · Computer Science 2021-08-25 Eshan Chattopadhyay , Jesse Goodman

We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method --- an extractor for two independent…

Computational Complexity · Computer Science 2015-03-10 Xin Li

We consider the problem of extracting randomness from \textit{sumset sources}, a general class of weak sources introduced by Chattopadhyay and Li (STOC, 2016). An $(n,k,C)$-sumset source $\mathbf{X}$ is a distribution on $\{0,1\}^n$ of the…

Computational Complexity · Computer Science 2021-10-26 Eshan Chattopadhyay , Jyun-Jie Liao

Randomness extraction is a key problem in cryptography and theoretical computer science. With the recent rapid development of quantum cryptography, quantum-proof randomness extraction has also been widely studied, addressing the security…

Quantum Physics · Physics 2024-01-15 Qian Li , Xiaoming Sun , Xingjian Zhang , Hongyi Zhou

Quantum-proof randomness extraction is essential for handling quantum side information possessed by a quantum adversary, which is widely applied in various quantum cryptography tasks. In this study, we introduce a real-time two-source…

Quantum Physics · Physics 2024-02-23 Qian Li , Hongyi Zhou

We continue a line of work on extracting random bits from weak sources that are generated by simple processes. We focus on the model of locally samplable sources, where each bit in the source depends on a small number of (hidden) uniformly…

Computational Complexity · Computer Science 2022-05-30 Omar Alrabiah , Eshan Chattopadhyay , Jesse Goodman , Xin Li , João Ribeiro

We study the problem of extracting a prescribed number of random bits by reading the smallest possible number of symbols from non-ideal stochastic processes. The related interval algorithm proposed by Han and Hoshi has asymptotically…

Information Theory · Computer Science 2012-09-05 Hongchao Zhou , Jehoshua Bruck

In 2005 Bourgain gave the first explicit construction of a two-source extractor family with min-entropy rate less than $1/2$. His approach combined Fourier analysis with innovative but inefficient tools from arithmetic combinatorics and…

Combinatorics · Mathematics 2019-07-31 Mark Lewko

The known constructions of negligible error (non-malleable) two-source extractors can be broadly classified in three categories: (1) Constructions where one source has min-entropy rate about $1/2$, the other source can have small…

Information Theory · Computer Science 2023-06-13 Divesh Aggarwal , Eldon Chung , Maciej Obremski

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain…

Computational Complexity · Computer Science 2026-05-11 Farzan Byramji , Daniel M. Kane , Jackson Morris , Anthony Ostuni

Quantum random number generation is a technique to generate random numbers by extracting randomness from specific quantum processes. As for practical random number generators, they are required not only to have no information leakage but…

Information Theory · Computer Science 2020-11-10 Zehao Zhao , Xiongfeng Ma , Hongyi Zhou

In a recent breakthrough \cite{CZ15}, Chattopadhyay and Zuckerman gave an explicit two-source extractor for min-entropy $k \geq \log^C n$ for some large enough constant $C$. However, their extractor only outputs one bit. In this paper, we…

Computational Complexity · Computer Science 2015-08-06 Xin Li

How to generate provably true randomness with minimal assumptions? This question is important not only for the efficiency and the security of information processing, but also for understanding how extremely unpredictable events are possible…

Quantum Physics · Physics 2015-05-18 Kai-Min Chung , Yaoyun Shi , Xiaodi Wu

Non-malleable extractors are generalizations and strengthening of standard randomness extractors, that are resilient to adversarial tampering. Such extractors have wide applications in cryptography and explicit construction of extractors.…

Computational Complexity · Computer Science 2024-04-29 Xin Li , Yan Zhong

For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples from these distributions. The primary drawback to traditional…

Probability · Mathematics 2007-05-23 James Allen Fill , Mark L. Huber

We propose a new model of a weakly random source that admits randomness extraction. Our model of additive sources includes such natural sources as uniform distributions on arithmetic progressions (APs), generalized arithmetic progressions…

Computational Complexity · Computer Science 2014-10-28 Abhishek Bhowmick , Ariel Gabizon , Thái Hoàng Lê , David Zuckerman

The weak law of large numbers implies that, under mild assumptions on the source, the Renyi entropy per produced symbol converges (in probability) towards the Shannon entropy rate. This paper quantifies the speed of this convergence for…

Information Theory · Computer Science 2017-05-01 Maciej Skorski

Randomness extraction is indispensable for quantum random number generators, serving to eliminate bias and potential information leakage from raw measurement data. Conventional extractors operate in a block-wise fashion, requiring the…

Quantum Physics · Physics 2026-05-12 Chun-Yang Luan , Xiang-Jie Lie , Lin Cheng , Gang-Xi Wang , Cheng-Kang Pan , Xiang Zhang , Xingjian Zhang

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error $\epsilon$…

Computational Complexity · Computer Science 2016-08-02 Xin Li

Randomness extractors, which extract high quality (almost-uniform) random bits from biased random sources, are important objects both in theory and in practice. While there have been significant progress in obtaining near optimal…

Computational Complexity · Computer Science 2018-06-12 Kuan Cheng , Xin Li
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