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原文連結
論文資訊
- 類型：已發表論文
- 日期：2017-06-30
摘要
We analyze the 熱力學 costs of the three main approaches to generating random numbers via the recently introduced 資訊 Processing Second Law. Given access to a specified source of randomness, a random number generator (RNG) produces samples from a desired target probability distribution. This differs from pseudorandom number generators (PRNGs) that use wholly deterministic algorithms and from true random number generators (TRNGs) in which the randomness source is a physical system. For each class, we analyze the 熱力學s of generators based on algorithms implemented as finite-state machines, as these allow for direct bounds on the required physical resources. This establishes bounds on heat dissipation and work consumption during the operation of three main classes of RNG algorithms-including those
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