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Quantum mechanics can reduce the complexity of classical models

机译:量子力学可以降低经典模型的复杂性

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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.. ? 2012 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.
机译:数学模型是定量科学的重要组成部分。他们根据当前可用的信息生成有关未来的预测。本着简单的精神更好;如果两个模型做出相同的预测,则首选需要较少输入的模型。但是,对于几乎所有的随机过程,即使是可证明的最佳经典模型也会浪费信息。他们需要的输入信息量超过了他们输出的预测信息量。在这里,我们展示了如何系统地构建打破这一经典界限的量子模型,并且模拟这种过程的最小熵系统必须具有量子动力学特征。这表明如果涉及量子效应,许多观察到的现象可能比传统上可能的简单得多。 2012自然出版集团,麦克米伦出版社有限公司的一个部门。版权所有。

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