Centre for Quantum Technologies, National University of Singapore, Singapore 117543, Singapore.
Nat Commun. 2012 Mar 27;3:762. doi: 10.1038/ncomms1761.
Mathematical models are an essential component of quantitative science. They generate predictions about the future, based on information available in the present. In the spirit of simpler is better; should two models make identical predictions, the one that requires less input is preferred. Yet, for almost all stochastic processes, even the provably optimal classical models waste information. The amount of input information they demand exceeds the amount of predictive information they output. Here we show how to systematically construct quantum models that break this classical bound, and that the system of minimal entropy that simulates such processes must necessarily feature quantum dynamics. This indicates that many observed phenomena could be significantly simpler than classically possible should quantum effects be involved.
数学模型是定量科学的重要组成部分。它们根据当前可用的信息对未来进行预测。本着越简单越好的精神，如果两个模型做出相同的预测，那么需要较少输入的模型是首选。然而，对于几乎所有的随机过程来说，即使是可证明的最优经典模型也会浪费信息。它们所要求的输入信息量超过了它们所输出的预测信息量。在这里，我们展示了如何系统地构建量子模型来打破这种经典限制，以及模拟这些过程的最小熵系统必然具有量子动力学。这表明，如果涉及量子效应，许多观察到的现象可能比经典情况下简单得多。
