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Wow, that short story was awesome. It's great that there's still so much Greg Egan I haven't encountered.

You're right that this idea feels like a deus ex machina. When I first read "Permutation City" I walked around for a few days in a euphoric haze, imagining simulations running without their substrates. But then reality hit. I was running huge microprocessor simulations in those days, and I remembered that you can't simulate their instructions out of order. There are dependencies that have to be respected[1]. And Egan had glossed past that in a single page, so slickly that I never noticed. This feels similar. It's dangerous to introduce too much fiction into one's worldview.

[1] Though it's possible you can sidestep dependency constraints, using something like maximum entropy to simulate a set of particles at far enough time steps without simulating the intervening steps, simply by estimating the probabilities of different kinds of interactions. It might work better if you have a goal in mind to train for using reinforcement learning. Then you could leave the fundamental laws of the simulated universe open and part of the weights to train, and select the simulation that gives you what you want. But all this is probably like Borges's library[2], or at least way beyond our computational capacity. Or maybe you need to imagine your goal to such depth that.. what's the point of finding a simulation that yields it? The world has never been easy, so better to assume it never will be until one is proven wrong.

[2] When I first read Carl Sagan's "Contact", the final chapter left me in a similar euphoric haze for a few days. Inside the infinite digits of pi in all bases you could find all possible patterns, all truths. Then I discovered the insight of Borges's library for myself.

I wonder what the author would think of some of the cellular automata in A New Kind of Science.