Particle Computation: Complexity, Algorithms, and Logic
Aaron T. Becker, Erik D. Demaine, S\'andor P. Fekete, Jarrett, Lonsforda, Rose Morris-Wright

TL;DR
This paper explores the algorithmic control of particle swarms in 2D environments, demonstrating how obstacles enable complex computations, and introduces methods for implementing logical operations and circuit replication within such systems.
Contribution
It provides new complexity results for particle configuration transformations and designs universal logic gates using particle interactions, advancing the understanding of computation in particle swarms.
Findings
Deciding configuration transformations is NP-hard.
Minimum control sequence length is PSPACE-complete.
Constructive algorithms for workspace design and logic gate implementation.
Abstract
We investigate algorithmic control of a large swarm of mobile particles (such as robots, sensors, or building material) that move in a 2D workspace using a global input signal (such as gravity or a magnetic field). We show that a maze of obstacles to the environment can be used to create complex systems. We provide a wide range of results for a wide range of questions. These can be subdivided into external algorithmic problems, in which particle configurations serve as input for computations that are performed elsewhere, and internal logic problems, in which the particle configurations themselves are used for carrying out computations. For external algorithms, we give both negative and positive results. If we are given a set of stationary obstacles, we prove that it is NP-hard to decide whether a given initial configuration of unit-sized particles can be transformed into a desired…
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