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We study weighted pseudorandom generators (WPRGs) and derandomizations for read-once branching programs (ROBPs). Denote $n$ and $w$ as the length and the width of a ROBP. We have the following results. For standard ROBPs, we give an…

Computational Complexity · Computer Science 2025-07-22 Kuan Cheng , Ruiyang Wu

We study the natural question of constructing pseudorandom generators (PRGs) for low-degree polynomial threshold functions (PTFs). We give a PRG with seed-length log n/eps^{O(d)} fooling degree d PTFs with error at most eps. Previously, no…

Computational Complexity · Computer Science 2015-03-13 Raghu Meka , David Zuckerman

A central question in derandomization is whether randomized logspace (RL) equals deterministic logspace (L). To show that RL=L, it suffices to construct explicit pseudorandom generators (PRGs) that fool polynomial-size read-once (oblivious)…

Computational Complexity · Computer Science 2018-08-21 Michael A. Forbes , Zander Kelley

We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for combinatorial rectangles and…

Computational Complexity · Computer Science 2012-10-02 Parikshit Gopalan , Raghu Meka , Omer Reingold , Luca Trevisan , Salil Vadhan

We construct pseudorandom generators of seed length $\tilde{O}(\log(n)\cdot \log(1/\epsilon))$ that $\epsilon$-fool ordered read-once branching programs (ROBPs) of width $3$ and length $n$. For unordered ROBPs, we construct pseudorandom…

Computational Complexity · Computer Science 2018-06-13 Raghu Meka , Omer Reingold , Avishay Tal

In a seminal work, Nisan (Combinatorica'92) constructed a pseudorandom generator for length $n$ and width $w$ read-once branching programs with seed length $O(\log n\cdot \log(nw)+\log n\cdot\log(1/\varepsilon))$ and error $\varepsilon$. It…

Computational Complexity · Computer Science 2020-06-02 Eshan Chattopadhyay , Jyun-Jie Liao

We establish new correlation bounds and pseudorandom generators for a collection of computation models. These models are all natural generalizations of structured low-degree $F_2$-polynomials that we did not have correlation bounds for…

Computational Complexity · Computer Science 2025-01-07 Vinayak M. Kumar

Halfspaces or linear threshold functions are widely studied in complexity theory, learning theory and algorithm design. In this work we study the natural problem of constructing pseudorandom generators (PRGs) for halfspaces over the sphere,…

Computational Complexity · Computer Science 2015-03-30 Pravesh Kothari , Raghu Meka

Developing explicit pseudorandom generators (PRGs) for prominent categories of Boolean functions is a key focus in computational complexity theory. In this paper, we investigate the PRGs against the functions of degree-$d$ polynomial…

Computational Complexity · Computer Science 2025-04-22 Penghui Yao , Mingnan Zhao

We show a new PRG construction fooling depth-$d$, size-$m$ $\mathsf{AC}^0$ circuits within error $\varepsilon$, which has seed length $O(\log^{d-1}(m)\log(m/\varepsilon)\log\log(m))$. Our PRG improves on previous work (Trevisan and Xue…

Computational Complexity · Computer Science 2023-01-25 Xin Lyu

We construct a pseudorandom generator which fools read-$k$ oblivious branching programs and, more generally, any linear length oblivious branching program, assuming that the sequence according to which the bits are read is known in advance.…

Computational Complexity · Computer Science 2017-08-08 Rohit Gurjar , Ben Lee Volk

Pseudorandom generators (PRGs) for low-degree polynomials are a central object in pseudorandomness, with applications to circuit lower bounds and derandomization. Viola's celebrated construction gives a PRG over the binary field, but with…

Computational Complexity · Computer Science 2026-02-11 Gil Cohen , Dean Doron , Noam Goldgraber

Pseudo-Random Numbers Generators (PRNGs) are algorithms produced to generate long sequences of statistically uncorrelated numbers, i.e. Pseudo-Random Numbers (PRNs). These numbers are widely employed in mid-level cryptography and in…

Cryptography and Security · Computer Science 2019-12-30 Luca Pasqualini , Maurizio Parton

We develop a pseudo-random generator to fool degree-$d$ polynomial threshold functions with respect to the Gaussian distribution. For $c>0$ any constant, we construct a pseudo-random generator that fools such functions to within $\epsilon$…

Computational Complexity · Computer Science 2011-04-08 Daniel M. Kane

High quality random numbers are necessary in the modern world. Ranging from encryption keys in cyber security to models and simulations for scientific use: it's important that these random numbers are of high quality and quickly attainable.…

Cryptography and Security · Computer Science 2024-05-16 Dmitriy Beznosko , Keith Driscoll , Fernando Guadarrama , Steven Mai , Nikolas Thornton

A sliding window algorithm receives a stream of symbols and has to output at each time instant a certain value which only depends on the last $n$ symbols. If the algorithm is randomized, then at each time instant it produces an incorrect…

Formal Languages and Automata Theory · Computer Science 2018-02-22 Moses Ganardi , Danny Hucke , Markus Lohrey

A Pseudo-Random Number Generator (PRNG) is any algorithm generating a sequence of numbers approximating properties of random numbers. These numbers are widely employed in mid-level cryptography and in software applications. Test suites are…

Cryptography and Security · Computer Science 2020-11-20 Luca Pasqualini , Maurizio Parton

Pseudo-random number generators (PRNGs) are essential in a wide range of applications, from cryptography to statistical simulations and optimization algorithms. While uniform randomness is crucial for security-critical areas like…

Cryptography and Security · Computer Science 2025-01-03 Jianan Wu , Ahmet Yusuf Salim , Eslam Elmitwalli , Selçuk Köse , Zeljko Ignjatovic

Pseudorandomness has played a central role in modern cryptography, finding theoretical and practical applications to various fields of computer science. A function that generates pseudorandom strings from shorter but truly random seeds is…

Formal Languages and Automata Theory · Computer Science 2016-10-25 Tomoyuki Yamakami

We present a new approach to constructing unconditional pseudorandom generators against classes of functions that involve computing a linear function of the inputs. We give an explicit construction of a pseudorandom generator that fools the…

Computational Complexity · Computer Science 2015-11-19 Parikshit Gopalan , Daniel Kane , Raghu Meka
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