LOTOS-like composition of boolean nets and causal set construction

Bolognesi T.

LOTOS  discrete spacetime  parallel composition  causal set 

In the context of research efforts on causal sets as discrete models of physical spacetime, and on their derivation from simple, deterministic, sequential models of computation, we consider boolean nets, a transition system that generalises cellular automata, and investigate the family of causal sets that derive from their computations, in search for interesting emergent properties. The choice of boolean nets is motivated by the fact that they naturally support compositions via a LOTOS-inspired parametric parallel operator, with possible interesting effects on the emergent structure of the derived causal sets. More generally, we critically reconsider the whole issue of algorithmic causet construction and expose the limitations suffered by these structures w.r.t. to the requirements of Lorentz invariance that even discrete models of physical spacetime, as recently shown, can and should satisfy. We conclude by hinting at novel ways to add momentum to the bold research programme that attempts to identify the natural with the computational universe.

Source: ModelEd, TestEd, TrustEd, edited by Joost-Pieter Katoen, Rom Langerak, Arend Rensink, pp. 27–47. Switzerland: Springer International Publishing, 2017

Publisher: Springer International Publishing, Switzerland, CHE

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