A QUANTUM OF SOLACE?

 Dick Pountain/ Idealog304/ 3rd Nov 2019

When Google announced, on Oct 24th, that it has achieved 'quantum supremacy' -- that is, has performed a calculation on a quantum computer faster than any conventional computer could ever do -- I was forcefully reminded that quantum computing is a subject I've been avoiding in this column for 25 years. That prompted a further realisation that it's because I'm sceptical of the claims that have been made. I should hasten to add that I'm not sceptical about quantum mechanics per se (though I do veer closer to Einstein than to Bohr, am more impressed by Carver Mead's Collective Electrodynamics  than by Copenhagen, and find 'many worlds' frankly ludicrous). Nor am I sceptical of the theory of quantum computation itself, though the last time I wrote about it was in Byte in 1997.  No, what I'm sceptical of are the pragmatic engineering prospects for its timely implementation. 

The last 60 years saw our world transformed by a new industrial revolution in electronics, gifting us the internet, the smartphone, Google searches and Wikipedia, Alexa and Oyster cards. The pace of that revolution was never uniform but accelerated to a fantastic extent from the early 1960s thanks to the invention of CMOS, the Complementary Metal-Oxide-Semiconductor fabrication process. CMOS had a property shared by few other technologies, namely that it became much, much cheaper and faster the smaller you made it, resulting in 'Moore's Law', that doubling of power and halving of cost every two years that's only now showing any sign of levelling off.  That's how you got a smartphone as powerful as a '90s supercomputer in your pocket.  CMOS is a solid-state process where electrons whizz around metal tracks deposited on treated silicon, which makes it amenable to easy duplication by what amounts to a form of printing. 

You'll have seen pictures of Google's Sycamore quantum computer that may have achieved 'supremacy' (though IBM is disputing it). It looks more like a microbrewery than a computer. Its 56 quantum bits are indeed solid state, but they're superconductors that work at microwave frequencies and near absolute zero immersed in liquid helium. The quantum superpositions upon which computation depends collapse at higher temperatures and in the presence of radio noise, and there's no prospect that such an implementation could ever achieve the benign scaling properties of CMOS. Admittedly a single qubit can in theory do the work of millions of CMOS bits, but the algorithms that need to be devised to exploit that advantage are non-intuitive and opaque, the results of computation are difficult to extract correctly and will require novel error-correction techniques that are as yet unknown and may not exist. It's not years but decades, or more, from practicality.

Given this enormous difficulty, why is so much investment going into quantum computing right now? Thanks to two classes of problem that are provenly intractable on conventional computers, but of great interest to extremely wealthy sponsors. The first is the cracking of public-key encryption, a high priority for the world's intelligence agencies which therefore receives defence funds.  The second is the protein-folding problem in biochemistry. Chains of hundreds of amino-acids that constitute enzymes can fold and link to themselves in a myriad different ways, only one of which will produce the proper behaviour of that enzyme, and that behaviour is the target for synthetic drugs. Big Pharma would love a quantum computer that could simulate such folding in real time, like a CAD/CAM system for designing monoclonal antibodies. 

What worries me is that the hype surrounding quantum computing is of just the sort that's guaranteed to bewitch technologically-illerate politicians, and it may be resulting in poor allocation of computer science funding. The protein folding problem is an extreme example of the class of optimisation problems -- others are involved in banking, transport routing, storage allocation, product pricing and so on -- all of which are of enormous commercial importance and have been subject to much research effort. For example twenty years ago constraint solving was one very promising line of study. When faced with an intractably large number of possibilities, apply and propagate constraints to severely prune the tree of possibilities rather than trying to traverse it all. The promise of quantum computers is precisely that, assuming you could assemble enough qubits, they could indeed just test all the branches, thanks to superposition. In recent years the flow of constraint satisfaction papers seems to have dwindled: is this because the field has struck an actual impass, or because the chimera of imminent quantum computers is diverting effort? Perhaps a hybrid approach to these sorts of problem might be more productive, say hardware assistance for constraint solving, plus deep learning, plus analog architectures, and anticipating shared quantum servers as one, fairly distant, prospect rather than the only bet.