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We prove new results on the polarizing random walk framework introduced in recent works of Chattopadhyay {et al.} [CHHL19,CHLT19] that exploit $L_1$ Fourier tail bounds for classes of Boolean functions to construct pseudorandom generators…

Computational Complexity · Computer Science 2020-11-10 Eshan Chattopadhyay , Jason Gaitonde , Chin Ho Lee , Shachar Lovett , Abhishek Shetty

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

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 give the best known pseudorandom generators for two touchstone classes in unconditional derandomization: an $\varepsilon$-PRG for the class of size-$M$ depth-$d$ $\mathsf{AC}^0$ circuits with seed length $\log(M)^{d+O(1)}\cdot…

Computational Complexity · Computer Science 2018-01-12 Rocco A. Servedio , Li-Yang Tan

For Boolean functions computed by read-once, depth-$D$ circuits with unbounded fan-in over the de Morgan basis, we present an explicit pseudorandom generator with seed length $\tilde{O}(\log^{D+1} n)$. The previous best seed length known…

Computational Complexity · Computer Science 2015-09-21 Sitan Chen , Thomas Steinke , Salil Vadhan

We revisit Nisan's classical pseudorandom generator (PRG) for space-bounded computation (STOC 1990) and its applications in streaming algorithms. We describe a new generator, HashPRG, that can be thought of as a symmetric version of Nisan's…

Data Structures and Algorithms · Computer Science 2024-01-05 Praneeth Kacham , Rasmus Pagh , Mikkel Thorup , David P. Woodruff

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

We give improved pseudorandom generators (PRGs) for Lipschitz functions of low-degree polynomials over the hypercube. These are functions of the form psi(P(x)), where P is a low-degree polynomial and psi is a function with small Lipschitz…

Computational Complexity · Computer Science 2012-11-07 Daniel Kane , Raghu Meka

Introduced in [CG24], pseudorandom error-correcting codes (PRCs) are a new cryptographic primitive with applications in watermarking generative AI models. These are codes where a collection of polynomially many codewords is computationally…

Cryptography and Security · Computer Science 2025-07-14 Surendra Ghentiyala , Venkatesan Guruswami

In a recent work, Chen, Hoza, Lyu, Tal and Wu (FOCS 2023) showed an improved error reduction framework for the derandomization of regular read-once branching programs (ROBPs). Their result is based on a clever modification to the inverse…

Computational Complexity · Computer Science 2023-12-08 Eshan Chattopadhyay , Jyun-Jie Liao

We give deterministic black-box polynomial identity testing algorithms for multilinear read-once oblivious algebraic branching programs (ROABPs), in n^(lg^2 n) time. Further, our algorithm is oblivious to the order of the variables. This is…

Computational Complexity · Computer Science 2013-09-24 Michael A. Forbes , Ramprasad Saptharishi , Amir Shpilka

In a recent work, O'Donnell, Servedio and Tan (STOC 2019) gave explicit pseudorandom generators (PRGs) for arbitrary $m$-facet polytopes in $n$ variables with seed length poly-logarithmic in $m,n$, concluding a sequence of works in the last…

Computational Complexity · Computer Science 2021-06-03 Srinivasan Arunachalam , Penghui Yao

Differential Privacy (DP) relies on random numbers to preserve privacy, typically utilising Pseudorandom Number Generators (PRNGs) as a source of randomness. In order to allow for consistent reproducibility, testing and bug-fixing in DP…

Cryptography and Security · Computer Science 2023-07-10 Naoise Holohan

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

The paper develops techniques in order to construct computer programs, pseudorandom number generators (PRNG), that produce uniformly distributed sequences. The paper exploits an approach that treats standard processor instructions…

Dynamical Systems · Mathematics 2011-11-15 Vladimir Anashin

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 study pseudorandomness and pseudorandom generators from the perspective of logical definability. Building on results from ordinary derandomization and finite model theory, we show that it is possible to deterministically construct, in…

Logic in Computer Science · Computer Science 2023-04-25 Jan Dreier , Jamie Tucker-Foltz

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

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

We devise a new pseudorandom generator against degree 2 polynomial threshold functions in the Gaussian setting. We manage to achieve $\epsilon$ error with seed length polylogarithmic in $\epsilon$ and the dimension, and exponential…

Computational Complexity · Computer Science 2014-04-07 Daniel M. Kane