论文标题
详细的平衡化学反应网络作为广义玻尔兹曼机器
Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines
论文作者
论文摘要
一袋相互作用的分子可以理解并适应不断裂开的环境吗？蜂窝生活提供了肯定的存在，但是允许生命存在的原则尚未得到证明。工程和理解生化计算的一个挑战是由于化学波动引起的固有噪声。在本文中，我们从机器学习理论，化学反应网络理论和统计物理学中汲取了见解，以表明广泛且与生物学相关的详细平衡化学反应网络能够代表和调节复杂分布。这些结果说明了生化计算机如何使用固有的化学噪声来执行复杂的计算。此外，我们使用明确的物理模型来得出推理的热力学成本。
Can a micron sized sack of interacting molecules understand, and adapt to a constantly-fluctuating environment? Cellular life provides an existence proof in the affirmative, but the principles that allow for life's existence are far from being proven. One challenge in engineering and understanding biochemical computation is the intrinsic noise due to chemical fluctuations. In this paper, we draw insights from machine learning theory, chemical reaction network theory, and statistical physics to show that the broad and biologically relevant class of detailed balanced chemical reaction networks is capable of representing and conditioning complex distributions. These results illustrate how a biochemical computer can use intrinsic chemical noise to perform complex computations. Furthermore, we use our explicit physical model to derive thermodynamic costs of inference.
