This is an important observation, and is one of the reasons we included an energy-time tradeoff analysis in the paper. To our knowledge, this is the first result where the product energy * time has been shown to scale with dimension for solving linear systems of equations (in any computational paradigm).
The time-energy trade off is of particular interest to me. I’m a roboticist, but I’ve been looking at adapting similar thermodynamic results to research problems in my field (Crooks’ work has been quite inspirational). I’m looking forward to reading this paper in greater detail in a few days when I have time (I’m in the middle of a move) and might want to get in touch about research ideas if that’s of interest.
Here there are N cells with N^2 couplings. So as you say, a normal computer with this many processors could also solve a linear system in O(N sqrt(kappa)) time. (Using conjugate gradient, since matrix-vector-mult on the system would be O(N) time.)
However, (1) these thermodynamic cells are much simpler than processors, and (2) it seems the overall energy required to simulate the SDE, once the couplings are initialized, only scales with O(N), not O(N^2) as in your digital case.