Abstract Geometrical Computation 10: An Intrinsically Universal Family of Signal Machines
Florent Becker, Tom Besson, J\'er\^ome Durand-Lose and, Aur\'elien Emmanuel, Mohammad-Hadi Foroughmand-Araabi, Sama Goliaei and, Shahrzad Heydarshahi

TL;DR
This paper constructs a universal family of signal machines capable of simulating any machine with speeds in a finite set, advancing the theoretical understanding of collision computing models.
Contribution
It introduces a method to simulate any signal machine with speeds in a finite set using macro-signals, establishing an intrinsically universal family of signal machines.
Findings
Constructed a universal signal machine for any finite set of speeds.
Developed a macro-signal simulation method for collision rules.
Proved the universality of the constructed family.
Abstract
Signal machines form an abstract and idealised model of collision computing. Based on dimensionless signals moving on the real line, they model particle/signal dynamics in Cellular Automata. Each particle, or signal, moves at constant speed in continuous time and space. When signals meet, they get replaced by other signals. A signal machine defines the types of available signals, their speeds and the rules for replacement in collision. A signal machine A simulates another one B if all the space-time diagrams of B can be generated from space-time diagrams of A by removing some signals and renaming other signals according to local information. Given any finite set of speeds S, we construct a signal machine that is able to simulate any signal machine whose speeds belong to S. Each signal is simulated by a macro-signal, a ray of parallel signals. Each macro-signal has a main signal located…
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Taxonomy
TopicsCellular Automata and Applications · DNA and Biological Computing · Computability, Logic, AI Algorithms
