Quantum computing and Nanoscale CAD

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Discussion Overview

The discussion revolves around the limitations of traditional computer-aided design (CAD) in modeling nanoscale systems and the potential advantages of quantum computing in addressing these challenges. Participants explore the computational intensity of quantum systems and the implications of Heisenberg's Uncertainty Principle on predictions in quantum mechanics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants reference Steve Jurvetson's claim that traditional CAD is insufficient for quantum-level designs, noting that supercomputers struggle with systems larger than a water molecule.
  • There is a question about the feasibility of making exact predictions in quantum systems, with some participants citing Heisenberg's Uncertainty Principle as a potential limitation.
  • Participants discuss the complexity of wave functions beyond simple systems like the hydrogen atom, emphasizing the challenges in solving the Schrödinger equation with traditional computers.
  • One participant suggests that brute-force simulation methods may not be effective due to the complexity of the systems involved.
  • Another participant draws a parallel between quantum systems and the Navier-Stokes equations in fluid dynamics, highlighting the computational intensity of numerical solutions.
  • It is noted that classical computers face challenges due to the exponentially large Hilbert spaces required for simulating multiple particles, which limits their capability to model realistic quantum systems.
  • Participants mention Feynman's original idea of quantum simulation and the concept of analog quantum computers as potential solutions to these computational challenges.

Areas of Agreement / Disagreement

Participants express differing views on the implications of Heisenberg's Uncertainty Principle for predictions in quantum mechanics, and there is no consensus on the effectiveness of traditional computers versus quantum computing for simulating complex systems.

Contextual Notes

The discussion highlights limitations related to the complexity of quantum systems, the assumptions underlying computational methods, and the unresolved nature of certain mathematical challenges in simulating these systems.

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Quantum computing and Nanoscale "CAD"

Reading a book on Nanotechnology and venture capitalist Steve Jurvetson makes the statement that traditional computer aided design, like one might use to test an airplane wing design, is not powerful enough to work at the quantum level in designing nanoscale systems. He writes:

"Although scientists have known for 100 years how to write down the equations an engineer needs to solve in order to understand any quantum system, no computer has ever been built powerful enough to solve them. Today's supercomputers choke on any system larger than a water molecule"

he goes on to say, without much elaboration that quantum computing can easily handle these sorts of problems resulting in "an exact prediction of how a system will behave in nature - something that is literally impossible for a traditional computer, no matter how powerful"

Question is what is he specifically referring to that is so computationally intensive and what is it about quantum computing that solves the problem so neatly?
 
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"an exact prediction of how a system will behave in nature - something that is literally impossible for a traditional computer, no matter how powerful"

Isn't this impossible regardless, according to Heisenberg's Uncertainty?
 


Isn't this impossible regardless, according to Heisenberg's Uncertainty?
Well, he means an accurate prediction of how a system will behave, to within the levels of statistical deviation mandated by the HUP.

Question is what is he specifically referring to that is so computationally intensive and what is it about quantum computing that solves the problem so neatly?
The wave functions becomes ginormously complex when you get beyond the hydrogen atom. You need to solve the Schrödinger equation for the system, and that requires advanced differential equations, which computers are not good at solving.

I'm not sure why the computers can't simulate the systems using brute-force though, i.e., dividing time into very small slices and then noting how it behaves over time.
 


peter0302 said:
Well, he means an accurate prediction of how a system will behave, to within the levels of statistical deviation mandated by the HUP.


The wave functions becomes ginormously complex when you get beyond the hydrogen atom. You need to solve the Schrödinger equation for the system, and that requires advanced differential equations, which computers are not good at solving.

I'm not sure why the computers can't simulate the systems using brute-force though, i.e., dividing time into very small slices and then noting how it behaves over time.


So is it like Navier Stokes equations in fluid dynamics - where there are not closed form solutions and the numerical solutions are computationally intensive?
 


Precisely.

Or even calculating the evolution of the solar system (which, at least as of 2000 when I was getting my CS degree) was a big problem for computers.
 


Well, the reason classical computers cannot deal with quantum systems is because, in order to simulate a given number of particles, you end up with exponentially large hilbert spaces (exponential in the number of particles).
This prevents anything realistic beyond very simple things to be simulated.

Which leads to the original Feynman idea. 10 atoms may be very hard to simulate, but nature actually known what to do with them, right? So nature is extremely powerful in computational power, otherwise it couldn't tell all these atoms how to interact, or their wave functions how to evolve.
Basically, the simplest idea is the quantum simulator original by Feynman and refined some years ago by Cirac, which basically amounts to engineer interactions among quantum systems such that the hamiltonian just looks like the system you want to simulate. That is today called "analog" quantum computer, and probably the first quantum computer that will be able to solve relevant problems.

Cheers,

Alex
 

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