Extractors for Polynomial Sources over $\mathbb{F}_2$
Eshan Chattopadhyay, Jesse Goodman, Mohit Gurumukhani

TL;DR
This paper presents the first explicit construction of extractors for polynomial sources over _2 with high min-entropy, introduces a novel input reduction lemma, and demonstrates inherent limitations of sumset extractors for such sources.
Contribution
It provides the first nontrivial extractor for polynomial sources over _2 and introduces polynomial NOBF sources, highlighting fundamental challenges in seedless extraction.
Findings
Constructed explicit extractors for degree 2 polynomial sources
Established limitations of sumset extractors for low min-entropy polynomial sources
Introduced polynomial NOBF sources as a new algebraic source family
Abstract
We explicitly construct the first nontrivial extractors for degree polynomial sources over . Our extractor requires min-entropy . Previously, no constructions were known, even for min-entropy . A key ingredient in our construction is an input reduction lemma, which allows us to assume that any polynomial source with min-entropy can be generated by uniformly random bits. We also provide strong formal evidence that polynomial sources are unusually challenging to extract from, by showing that even our most powerful general purpose extractors cannot handle polynomial sources with min-entropy below . In more detail, we show that sumset extractors cannot even disperse from degree polynomial sources with min-entropy . In fact, this impossibility result even…
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Taxonomy
TopicsQuantum chaos and dynamical systems
