Why do you think nature can’t solve NP-hard problems? When you dip a twisted wire with 3D structure into a dish of liquid soap and water, and pull it out and get a soap film, didn’t it just solve an NP problem?
All of the bonds and atoms in a protein are “computing” simultaneously, so the fact that the problem is NP in terms of number of molecules isn’t a problem. I don’t understand BQP & so can’t comment on that.
Incidentally, your observation about consistent folding is often right, but some proteins have functions that depending on them folding to different shapes under different conditions. Usually these shapes are similar. I don’t know if any proteins routinely fold into 2 very-different shapes.
Why do you think nature can’t solve NP-hard problems? When you dip a twisted wire with 3D structure into a dish of liquid soap and water, and pull it out and get a soap film, didn’t it just solve an NP problem?
Oh no. Ohhhhh no. Not somebody trying to claim that nature solves problems in NP in polynomial time because of bubble shape minimization again!
Like Cyan just said, nature does not solve the NP problem of a global optimal configuration. It just finds a local optimum, which is already known to be computationally easy! Here’s a reference list.
All of the bonds and atoms in a protein are “computing” simultaneously,
And there are at most N^2 of them, so that doesn’t transform exponential into tractable. It’s not even a Grover speedup (2^N → 2^(N/2)), which we do know how to get out of a quantum computer.
Why do you think nature can’t solve NP-hard problems? When you dip a twisted wire with 3D structure into a dish of liquid soap and water, and pull it out and get a soap film, didn’t it just solve an NP problem?
All of the bonds and atoms in a protein are “computing” simultaneously, so the fact that the problem is NP in terms of number of molecules isn’t a problem. I don’t understand BQP & so can’t comment on that.
Incidentally, your observation about consistent folding is often right, but some proteins have functions that depending on them folding to different shapes under different conditions. Usually these shapes are similar. I don’t know if any proteins routinely fold into 2 very-different shapes.
Oh no. Ohhhhh no. Not somebody trying to claim that nature solves problems in NP in polynomial time because of bubble shape minimization again!
Like Cyan just said, nature does not solve the NP problem of a global optimal configuration. It just finds a local optimum, which is already known to be computationally easy! Here’s a reference list.
The more convoluted the wire structure, the more likely the soap film is to be in a stable sub-optimal configuration.
And there are at most N^2 of them, so that doesn’t transform exponential into tractable. It’s not even a Grover speedup (2^N → 2^(N/2)), which we do know how to get out of a quantum computer.