Extend no-signalling results to objective collapse models

Determine whether the equivalence between no-signalling and the inability to solve NP-hard problems efficiently extends to non-invertible nonlinear maps arising in objective collapse models.

Background

The thesis explains that the Bao--Bouland--Jordan argument applies to differentiable, invertible nonlinear maps, whereas objective collapse models are stochastic and non-invertible. Thus, the presented argument does not directly establish that such models violate the Physical Extended Church--Turing Thesis.

The unresolved question is whether no-signalling constraints can nevertheless be used to rule out efficient NP-hard computation in these non-invertible collapse theories.