English
Related papers

Related papers: Deterministic Extractors for Additive Sources

200 papers

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

We construct explicit deterministic extractors for polynomial images of varieties, that is, distributions sampled by applying a low-degree polynomial map $f : \mathbb{F}_q^r \to \mathbb{F}_q^n$ to an element sampled uniformly at random from…

Computational Complexity · Computer Science 2023-01-18 Zeyu Guo , Ben Lee Volk , Akhil Jalan , David Zuckerman

In a recent work, Gryaznov, Pudl\'{a}k, and Talebanfard (CCC' 22) introduced a stronger version of affine extractors known as directional affine extractors, together with a generalization of $\mathsf{ROBP}$s where each node can make linear…

Computational Complexity · Computer Science 2024-07-04 Xin Li , Yan Zhong

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 explicitly construct the first nontrivial extractors for degree $d \ge 2$ polynomial sources over $\mathbb{F}_2^n$. Our extractor requires min-entropy $k\geq n - \tilde{\Omega}(\sqrt{\log n})$. Previously, no constructions were known,…

Computational Complexity · Computer Science 2024-02-02 Eshan Chattopadhyay , Jesse Goodman , Mohit Gurumukhani

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

A long line of work in the past two decades or so established close connections between several different pseudorandom objects and applications. These connections essentially show that an asymptotically optimal construction of one central…

Computational Complexity · Computer Science 2023-05-31 Xin Li

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

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

Randomness extractors are algorithms that distill weak random sources into near-perfect random numbers. Two-source extractors enable this distillation process by combining two independent weak random sources. Raz's extractor (STOC '05) was…

Cryptography and Security · Computer Science 2025-06-19 Cameron Foreman , Lewis Wooltorton , Kevin Milner , Florian J. Curchod

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

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

Addition chains are a classical construction for fast exponentiation and related computation problems. In this paper, we study a chain for a fixed integer $n$ by decomposing each generator into a \emph{determiner} and a \emph{regulator}…

Number Theory · Mathematics 2026-04-23 Theophilus Agama

This work is based on the proposal of a deterministic randomness extractor of a random Diffie-Hellman element defined over two prime order multiplicative subgroups of a finite fields $\mathbb{F}_{p^n}$, $G_1$ and $G_2$. We show that the…

Cryptography and Security · Computer Science 2015-02-03 Hortense Boudjou Tchapgnouo , Abdoul Aziz Ciss

We consider an additive partially linear framework for modelling massive heterogeneous data. The major goal is to extract multiple common features simultaneously across all sub-populations while exploring heterogeneity of each…

Methodology · Statistics 2019-01-01 Binhuan Wang , Yixin Fang , Heng Lian , Hua Liang

A natural model of read-once linear branching programs is a branching program where queries are $\mathbb{F}_2$ linear forms, and along each path, the queries are linearly independent. We consider two restrictions of this model, which we…

Computational Complexity · Computer Science 2022-07-19 Svyatoslav Gryaznov , Pavel Pudlák , Navid Talebanfard

We identify a new notion of pseudorandomness for randomness sources, which we call the average bias. Given a distribution $Z$ over $\{0,1\}^n$, its average bias is: $b_{\text{av}}(Z) =2^{-n} \sum_{c \in \{0,1\}^n} |\mathbb{E}_{z \sim…

Computational Complexity · Computer Science 2019-05-31 Arnab Bhattacharyya , Philips George John , Suprovat Ghoshal , Raghu Meka

We describe a construction of explicit affine extractors over large finite fields with exponentially small error and linear output length. Our construction relies on a deep theorem of Deligne giving tight estimates for exponential sums over…

Computational Complexity · Computer Science 2014-01-27 Jean Bourgain , Zeev Dvir , Ethan Leeman
‹ Prev 1 2 3 10 Next ›