Well, to one extent of course it will, since ion pumps and neurotransmitter-sensors run entirely on quantum mechanics, just like chlorophyll. The question for a simulation would seem to be whether we can model each and each instance of these things seperately, thus neatly cordoning off the quantum mechanics. Simulating a tree, for example, can be done quite well above the quantum level, because even though chlorophyll’s properties depend on QM, once you know the properties you can model it without further reference to quantum mechanics.
Are you saying roughly the same thing as Tegmark (2000)? (Louie pointed me to it.) Have you read the reply by Hagan et al. (2002)? A brief 2011 review is here. Unfortunately, my own training offers me limited ability to judge these matters.
I have never seen a coherent description of a situation in which we wouldn’t be able to model each instance separately; naively, it would require exceptionally careful engineering (to maintain quantum superpositions over large or spatially separated objects) which we have never witnessed in nature.
All of the examples I have seen support the obvious assertion “to one extent of course it will.” Is this also your impression?
Yeah, pretty much. It might be possible to have very brief entanglement between different neurons, but because the brain is so messy and not-a-microwave-transmitter there’s nothing to actually act on that entanglement, and forget having anything that looks like our quantum computing.
I can imagine situations which would make it impractical to not use a quantum computer for at least parts of the emulation. Shor’s alogorithm is an example of how quantum computers can fundamentally be more efficient then classical computers. If our brain uses quantum algorithms with fundamental advantages over the classical analog, then it could be impractical to use classical computers alone for emulation due to the exponential increase in computation time required.
I unable to assign a probability with confidence for this case. So I unconfidently assign a low probability for our brain using quantum algorithm that make it impractical to emulate with out quantum computers. A high probability to finding organisms that take advantage of quantum mechanics to a higher degree then a bird for navigation and plants for photosynthesis. This is due the ability to leverage quantum mechanics has evolved at least twice for very different purposes.
The question is not whether “quantum computers can fundamentally be more efficient then classical computers”, but if quantum mechanical entanglement can be used by the brain, which seems to be improbable.
I asked a professor of biophysics about this issues, he knew about the result concerning photosynthesis and was pretty sure that QM does not matter for simulating the brain.
I was trying to express in my post that the extra efficiency gained from a switch to quantum computers only matters when it makes the simulation practical rather impractical with the current resources. This transition would only happen if the brain used quantum algorithms with a fundamental advantage over classical computing, which I assigned a low probability to. Meaning that a QM computer would probably not be necessary.
It sounds like we agree in conclusion but are failing to comunicate some details or disagree on some details.
Well, to one extent of course it will, since ion pumps and neurotransmitter-sensors run entirely on quantum mechanics, just like chlorophyll. The question for a simulation would seem to be whether we can model each and each instance of these things seperately, thus neatly cordoning off the quantum mechanics. Simulating a tree, for example, can be done quite well above the quantum level, because even though chlorophyll’s properties depend on QM, once you know the properties you can model it without further reference to quantum mechanics.
Are you saying roughly the same thing as Tegmark (2000)? (Louie pointed me to it.) Have you read the reply by Hagan et al. (2002)? A brief 2011 review is here. Unfortunately, my own training offers me limited ability to judge these matters.
For others, useful links on quantum computation:
Quantum Computing: A General Introduction (2011)
A Quantum Information Science and Technology Roadmap (2004)
List of quantum algorithms that offer speed-up over classical algorithms (2011)
Recent progress in quantum algorithms (2010)
Practical Quantum Computers Creep Closer to Reality (2011)
I have never seen a coherent description of a situation in which we wouldn’t be able to model each instance separately; naively, it would require exceptionally careful engineering (to maintain quantum superpositions over large or spatially separated objects) which we have never witnessed in nature.
All of the examples I have seen support the obvious assertion “to one extent of course it will.” Is this also your impression?
Yeah, pretty much. It might be possible to have very brief entanglement between different neurons, but because the brain is so messy and not-a-microwave-transmitter there’s nothing to actually act on that entanglement, and forget having anything that looks like our quantum computing.
exactly.
I can imagine situations which would make it impractical to not use a quantum computer for at least parts of the emulation. Shor’s alogorithm is an example of how quantum computers can fundamentally be more efficient then classical computers. If our brain uses quantum algorithms with fundamental advantages over the classical analog, then it could be impractical to use classical computers alone for emulation due to the exponential increase in computation time required.
I unable to assign a probability with confidence for this case. So I unconfidently assign a low probability for our brain using quantum algorithm that make it impractical to emulate with out quantum computers. A high probability to finding organisms that take advantage of quantum mechanics to a higher degree then a bird for navigation and plants for photosynthesis. This is due the ability to leverage quantum mechanics has evolved at least twice for very different purposes.
The question is not whether “quantum computers can fundamentally be more efficient then classical computers”, but if quantum mechanical entanglement can be used by the brain, which seems to be improbable. I asked a professor of biophysics about this issues, he knew about the result concerning photosynthesis and was pretty sure that QM does not matter for simulating the brain.
I was trying to express in my post that the extra efficiency gained from a switch to quantum computers only matters when it makes the simulation practical rather impractical with the current resources. This transition would only happen if the brain used quantum algorithms with a fundamental advantage over classical computing, which I assigned a low probability to. Meaning that a QM computer would probably not be necessary.
It sounds like we agree in conclusion but are failing to comunicate some details or disagree on some details.