Multiplicative and Additive Extractors for Low Entropy Samplable Sources Under Reduced Assumptions
Trevisan and Vadhan [TV, FOCS'00] constructed (seedless) extractors for distributions samplable by poly-size circuits that have very high min-entropy, under the very strong complexity theoretic hardness assumption that $\mathsf{E}=\mathsf{DTIME}(2^{O(n)})$ requires size $2^{Ω(n)}$ circuits that have oracle access to $Σ_6^{\text{P}}$. In this paper we give three new explicit constructions of extractors for samplable distributions. First, we construct an extractor that extracts one bit, with constant error, for min-entropy $k=O(\log n)$, which matches the non-constructive probabilistic argument. This result uses hardness for nondeterministic circuits, and achieves the same parameters as the recent extractor of Oh and Shaltiel [OS, STOC'26] under an incomparable hardness assumption. In contrast to the extractor of [OS26], our extractor (and, similarly, the constructions below) also works for the more general class of distributions samplable with postselection (a model introduced by [BGDM, FOCS'23] that generalizes samplable and recognizable sources). Second, we construct an extractor that extracts almost all the entropy, with polynomially small error, for min-entropy $k=n^α$, where $α>0$ is an arbitrary constant. This result also uses hardness for nondeterministic circuits, and significantly improves upon the recent extractor of [Shaltiel, FOCS'25] which required a much stronger assumption. This extractor is also \textit{multiplicative}: a stronger notion suggested in [AASY, Comp. Complexity'16; Shaltiel, CCC'25] to make extractors for samplable distributions suitable for selecting keys for cryptographic protocols. Third, we construct an extractor that extracts almost all the entropy, with polynomially small error, for min-entropy $k=\mathrm{polylog}(n)$. This result uses hardness for circuits that have oracle access to $Σ_2^{\text{P}}$.