Gorecki Jerzy, Bose Ashmita
Department of Complex Systems and Chemical Processing of Information, Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland.
Front Chem. 2020 Nov 9;8:580703. doi: 10.3389/fchem.2020.580703. eCollection 2020.
Chemical computing is something we use every day (e.g., in the brain), but we can still not explore and master its potential in human-made experiments. It is expected that the maximum computational efficiency of a chemical medium can be achieved if information is processed in parallel by different parts of the medium. In this paper, we use computer simulations to explore the efficiency of chemical computing performed by a small network of three coupled chemical oscillators. We optimize the network to recognize the white and red regions of the Japanese flag. The input information is introduced as the inhibition times of individual oscillators, and the output information is coded in the number of activator maxima observed on a selected oscillator. We have used the Oregonator model to simulate the network time evolution and the evolutionary optimization to find the best network for the considered task. We have found that even a network of three interacting oscillators can recognize the color of a randomly selected point with 95% accuracy.
化学计算是我们每天都会用到的(例如在大脑中),但我们仍然无法在人造实验中探索和掌握其潜力。如果信息由化学介质的不同部分并行处理,预计可以实现化学介质的最大计算效率。在本文中,我们使用计算机模拟来探索由三个耦合化学振荡器组成的小型网络执行化学计算的效率。我们对网络进行优化,以识别日本国旗的白色和红色区域。输入信息作为各个振荡器的抑制时间引入,输出信息则编码为在选定振荡器上观察到的激活剂最大值的数量。我们使用俄勒冈振子模型来模拟网络的时间演化,并通过进化优化来找到适合该任务的最佳网络。我们发现,即使是由三个相互作用的振荡器组成的网络,也能以95%的准确率识别随机选择点的颜色。