A single-celled amoeboid organism is known to maximize nutrient acquisition efficiently by deforming its body (Fig. 1(a)). This ability made it possible for the organism to survive in the harsh natural environment over a billion years. Its sophisticated search capability has been demonstrated by means of the amoeba-based computer in which the amoeboid organism is used to search for a solution of the optimization problem [1]. However, from engineering point of view, the deformation speed of the organism is too slow to compute compared to the modern computers. Here, our idea is to artificially represent the amoeba search capability by electronically mimicking the spatiotemporal dynamics of the organism, which is called “electronic amoeba” (Fig. 1(b)) [2]. We have demonstrated that our system can find a reliable and swift solution to the intractable combinatorial optimization problems including maximum cut problem, satisfiability problem (SAT), and traveling salesman problem (TSP) [3]. In this paper, we show the important features of the amoeba dynamics in terms of the solution search and their electronic representations. We also show how to map the problem to the system, which has a great advantage than the currently available optimization computers called Ising machine.

[1] e.g. L. Zhu, S.-J. Kim, M. Hara, and M. Aono, R. Soc. Open Sci. 5, 180396 (2018). [2] S. Kasai, M., Aono & M. Naurse, Appl. Phys. Lett. 103, 163703 (2013). [3] K. Saito, M. Aono & S. Kasai, Sci. Rep. 10, 20772 (2020).