The analog way for quantum computing

January 25, 2016 // By Peter Clarke
Blaine Bateman looks at the parallels between quantum and analog computing.

I'm sure nearly everyone has by now heard that Google "proved" the D-Wave 2 they operate jointly with NASA (mainly paid for by Google) can operate "up to 108 times faster".

If not, you might want to have a quick read of their paper, titled "What is the Computational Value of Finite Range Tunneling?" Even if you don't read the paper, you can be excused for wondering if "the race to a real quantum computer" is over. There is enough press around every such announcement from Google, IBM, and others that you easily can get the impression it is just down to the details now.
 

In fact, there are still major, fundamental challenges to be overcome and building blocks to be created. You might have heard earlier last year how IBM had solved the problem of quantum error correction. Although there was a lot of buzz about that, it is interesting to note that a month earlier, Google reported on their own blog that they had already done more or less the same thing. And so it goes. But the near-term reality could be even more interesting, especially if you are old or lucky enough to have played with analog computing.

Back in 2013, I wrote a series of posts on the possible role of quantum computing in analog design. (see: Will Quantum Computing Enhance Analog Design? Part 1 Parts 1-3) In the introduction to that series, I provided the following diagram:

 

 

An analog problem