Why Is Analog Quantum Computing Needed?

Quantum computing is motivated by a perception that simulating atomic physics described mathematically by the Schrödinger Equation SE of Quantum Mechanics QM, is exponentially hard and so is impossible. This is because SE for a system with $N$ electrons involves $3N$ spatial dimensions with computational work increasing exponentially with $N$.

In other words, digital simulation of QM is viewed to be so computationally demanding that the alternative of analog simulation must be explored. This is the idea analog quantum computing launched by Richard Feynman 50 years ago:

• Simulate a real quantum system by a controllable laboratory quantum system. 

This is the same idea as testing a physical model of a real airplane in a wind tunnel under controllable conditions. Or building a toy model of a bridge and testing its bearing capacity. No mathematics is needed, just craftsman skill.

The basic idea is thus to give up building mathematical models of realities in terms of Cartesian geometry based on numbers with digital representation, as the scientific method behind the evolution of the modern industrial/digital society. 

Such a step can be seen as a step back to a more primitive science based on analog modeling without mathematics. 

In any case, massive investment is now going into creating quantum computers as controllable analog quantum systems. The design work has to cope with the perceived impossibility to test different designs using mathematical digital modeling, and so has to rely on tricky experimental testing. The time frame for a useful analog quantum computer appears to be decades rather than years.

With this perspective it is natural to ask if the exponential computational complexity of the microscopics of quantum mechanics is written in stone. Macroscopics of continuum mechanics rarely comes with exponential complexity, because evolving a macroscopic system, like the weather, one time step involves only local connections in 3 space dimensions which has polynomial complexity. 

If macroscopics has polynomial complexity, then microscopics on smaller scales should have as well. RealQM offers a version of quantum mechanics of polynomial complexity. If nothing else, it can be used to test different designs of an analog quantum computer. Want to try RealQM?

Another mission of analog quantum computing put forward to motivate investors, is improved potential of factorisation of large natural numbers with promise to break cryptography codes. But analog computation about properties of numbers instead of digital appears far-fetched.

PS Recall that at each clock cycle

• a digital computer operates on $n$ factual states
• a quantum computer operates on $2^n$ possible states  

with simplistic promise of an enormous increase of capacity from linear to exponential. Is it too good to be true?