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A Pseudorandom Generator for Functions of Low-Degree Polynomial Threshold Functions

Computational Complexity 2025-04-22 v2

Abstract

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-dd polynomial threshold functions (PTFs) over Gaussian space. Our main result is an explicit construction of PRG with seed length poly(k,d,1/ϵ)logn\mathrm{poly}(k,d,1/\epsilon)\cdot\log n that can fool any function of kk degree-dd PTFs with probability at least 1ε1-\varepsilon. More specifically, we show that the summation of LL independent RR-moment-matching Gaussian vectors ϵ\epsilon-fools functions of kk degree-dd PTFs, where L=poly(k,d,1ϵ)L=\mathrm{poly}( k, d, \frac{1}{\epsilon}) and R=O(logkdϵ)R = O({\log \frac{kd}{\epsilon}}). The PRG is then obtained by applying an appropriate discretization to Gaussian vectors with bounded independence.

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Cite

@article{arxiv.2504.10904,
  title  = {A Pseudorandom Generator for Functions of Low-Degree Polynomial Threshold Functions},
  author = {Penghui Yao and Mingnan Zhao},
  journal= {arXiv preprint arXiv:2504.10904},
  year   = {2025}
}

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R2 v1 2026-06-28T22:58:41.591Z