[adamnemecek]

There really isn't. Some of the old stuff still applies. But my approach to understanding this is very all over the place and I wouldn't recommend it for anyone besides myself. But I've found trying to understand electromagnetism and basic quantum theory (photon-matter interactions) to be quite helpful.

As for classification, there's some work on this e.g. this http://www.cs.princeton.edu/~ken/MCS86.pdf

I believe it's not non-deterministic, as in some sense, if you can pose the problem in a differentiable way, it's better than non-determinism.

It's like being in a maze. An analog computer like robot can perceive the slight tilt of the floor that goes from the entrance to the exit and just follows that tilt. It takes the robot an optimal number of steps too.

A non-deterministic Turing would kind of split itself into N different robots and start exploring all the turns. It might find the answer eventually but e.g. it will consume that much more energy.

This analogy might be silly but I hope it conveys how very different analog machines are.

[jd007]

thanks for the info. for the maze example, a ND robot would be able to find the exit in the optimal number of steps since one of the decision trees will in fact be the optimal path and will terminate first. so i dont see how analog computing can be more efficient.

unless you are saying that in an analog case we can ignore the rules of the maze and can go through walls. but then are we still solving the same problem? seems like the time complexity comparison no longer makes sense if you redefine the constraints of the problem.

[adamnemecek]

> unless you are saying that in an analog case we can ignore the rules of the maze and can go through walls.

Not ignore, but you have a lot more information about the problem and you have a general direction of the solution.

ND turing can split and like explore multiple corridors at once. But in the end all those robots that don't end up finding exit just wasted energy. I guess you don't care about this in complexity theory but this is a huge gain in practice.

[techdragon]

The description makes me think of a loud sound echoing through the maze, each branch further divides the volume of the sound, but a loud enough sound will "exit" in the optimal "O(1)" time because the sound wave "explores" every branch of the maze in "parallel".

Is this a reasonable mental model of what your describing?

[adamnemecek]

In your description you are still expending extra energy to explore the branches. Also it's not O(1), it's just that every step you take is bound to be optimal. So in O(1), you are literally one step closer to the solution.

[quackdetector]

Did someone call my name?

[adamnemecek]

Please make your criticism more concrete. Is what I'm proposing a stretch given the current circumstances? Definitely. However I can provide you with research on just about any point that I'm making. You do sometimes have to read between the lines but please point out one thing that you need clarified and I'll provide some resources.