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We revisit the classical problem: given a memoryless source having a certain amount of Shannon Entropy, how many random bits can be extracted? This question appears in works studying random number generators built from physical entropy sources. Some authors proposed to use a heuristic estimate obtained from the Asymptotic Equipartition Property, which yields roughly n extractable bits, where n is the total Shannon entropy amount. However best precise results of this form give only $$n-O\\sqrt{\\log 1/\\epsilon n}$$ bits, where $$\\epsilon $$ is the distance of the extracted bits from uniform. In this paper we show a matching $$ n-\\varOmega \\sqrt{\\log 1/\\epsilon n}$$ upper bound. Therefore, the loss of $$\\varTheta \\sqrt{\\log 1/\\epsilon n}$$ bits is necessary. As we show, this theoretical bound is of practical relevance. Namely, applying the imprecise AEP heuristic to a mobile phone accelerometer one might overestimate extractable entropy even by $$100\\,\\%$$ , no matter what the extractor is. Thus, the \"AEP extracting heuristic\" should not be used without taking the precise error into account.

How Much Randomness Can Be Extracted from Memoryless Shannon Entropy Sources?