When will we have a quantum computer? Never, with that attitude

We are quantum drunks under the lamp post—we are only looking at stuff that we can shine photons on.

In a recently posted paper, M.I. Dyakonov outlines a simplistic argument for why quantum computing is impossible. It’s so far off the mark that it’s hard to believe that he’s even thought about math and physics before. I’ll explain why.

abstract

Find a coin. I know. Where, right? I actually had to steal one from my kid’s piggy bank. Flip it. I got heads. Flip it again. Heads. Again. Tails. Again, again, again… HHTHHTTTHHTHHTHHTTHT. Did you get the same thing? No, of course you didn’t. That feels obvious. But why?

Let’s do some math. Wait! Where are you going? Stay. It will be fun. Actually, it probably won’t. I’ll just tell you the answer then. There are about 1 million different combinations of heads and tails in a sequence of 20 coin flips. The chances that we would get the same string of H’s and T’s is 1 in a million. You might as well play the lottery if you feel that lucky. (You’re not that lucky, by the way, don’t waste your money.)

Now imagine 100 coin flips, or maybe a nice round number like 266. With just 266 coin flips, the number of possible sequences of heads and tails is just larger than the number of atoms in the entire universe. Written in plain English the number is 118 quinvigintillion 571 quattuorvigintillion 99 trevigintillion 379 duovigintillion 11 unvigintillion 784 vigintillion 113 novemdecillion 736 octodecillion 688 septendecillion 648 sexdecillion 896 quindecillion 417 quattuordecillion 641 tredecillion 748 duodecillion 464 undecillion 297 decillion 615 nonillion 937 octillion 576 septillion 404 sextillion 566 quintillion 24 quadrillion 103 trillion 44 billion 751 million 294 thousand 464. Holy fuck!

So obviously we can’t write them all down. What about if we just tried to count them one-by-one, one each second? We couldn’t do it alone, but what if all people on Earth helped us? Let’s round up and say there are 10 billion of us. That wouldn’t do it. What if each of those 10 billion people had a computer that could count 10 billion sequences per second instead? Still no. OK, let’s say, for the sake of argument, that there were 10 billion other planets like Earth in the Milky Way and we got all 10 billion people on each of the 10 billion planets to count 10 billion sequences per second. What? Still no? Alright, fine. What if there were 10 billion galaxies each with these 10 billion planets? Not yet? Oh, fuck off.

Even if there were 10 billion universes, each of which had 10 billion galaxies, which in turn had 10 billion habitable planets, which happened to have 10 billion people, all of which had 10 billion computers, which count count 10 billion sequences per second, it would still take 100 times the age of all those universes to count the number of possible sequences in just 266 coin flips. Mind. Fucking. Blown.

Why I am telling you all this? The point I want to get across is that humanity’s knack for pattern finding has given us the false impression that life, nature, the universe, or whatever, is simple. It’s not. It’s really fucking complicated. But like a drunk looking for their keys under the lamp post, we only see the simple things because that’s all we can process. The simple things, however, are the exception, not the rule.

Suppose I give you a problem: simulate the outcome of 266 coin tosses. Do you think you could solve it? Maybe you are thinking, well you just told me that I couldn’t even hope to write down all the possibilities—how the hell could I hope to choose from one of them. Fair. But, then again, you have the coin and 10 minutes to spare. As you solve the problem, you might realize that you are in fact a computer. You took an input, you are performing the steps in an algorithm, and will soon produce an output. You’ve solved the problem.

A problem you definitely could not solve is to simulate 266 coin tosses if the outcome of each toss depended on the outcome of the previous tosses in an arbitrary way, as if the coin had a memory. Now you have to keep track of the possibilities, which we just decided was impossible. Well, not impossible, just really really really time consuming. But all the ways that one toss could depend on previous tosses is yet even more difficult to count—in fact, it’s uncountable. One situation where it is not difficult is the one most familiar to us—when each coin toss is completely independent of all previous and future tosses. This seems like the only obvious situation because it is the only one we are familiar with. But we are only familiar with it because it is one we know how to solve.

Life’s complicated in general, but not so if we stay on the narrow paths of simplicity. Computers, deep down in their guts, are making sequences that look like those of coin-flips. Computers work by flipping transistors on and off. But your computer will never produce every possible sequence of bits. It stays on the simple path, or crashes. There is nothing innately special about your computer which forces it to do this. We never would have built computers that couldn’t solve problems quickly. So computers only work at solving problems that can we found can be solved because we are at the steering wheel forcing them to the problems which appear effortless.

In quantum computing it is no different. It can be in general very complicated. But we look for problems that are solvable, like flipping quantum coins. We are quantum drunks under the lamp post—we are only looking at stuff that we can shine photons on. A quantum computer will not be an all-powerful device that solves all possible problems by controlling more parameters than there are particles in the universe. It will only solve the problems we design it to solve, because those are the problems that can be solved with limited resources.

We don’t have to track (and “keep under control”) all the possibilities, as Dyakonov suggests, just as your digital computer does not need to track all its possible configurations. So next time someone tells you that quantum computing is complicated because there are so many possibilities involved, remind them that all of nature is complicated—the success of science is finding the patches of simplicity. In quantum computing, we know which path to take. It’s still full of debris and we are smelling flowers and picking the strawberries along the way, so it will take some time—but we’ll get there.

 

Just what does a postdoctoral theoretical physicist do all day?

Coffee… mostly, I drink coffee.

A kindergartener once asked me, “why don’t you wear science clothes?” I gathered that she meant a lab coat. Then there is the utter surprise my neighbors show when I tell them—yes—I am on my way to work wearing sandals, shorts and a t-shirt. Take a moment and do a google image search of “scientist”. You have to scroll through several pages before you see a person not wearing a lab coat. So if I don’t wear a lab coat while staring into a beaker as if the colorful liquid inside contained a part of my soul, what do I do all day?

Generally speaking, a postdoctoral researcher (postdoc) is someone at a stage in their academic career between a graduate student and a professor. This usually involves traveling around the world working on short-term contracts. In theoretical physics the typical situation is to move several times over a period of 5–10 years before landing a permanent position as a professor or leave academia for an industry job.

While that sounds kind of horrible, as far as responsibilities go, it’s the best job in the world. I have the freedom of a graduate student, but I don’t have to write exams or engage in any of the administrative duties of a professor. I get to focus on my passion: research.

Now, you might be thinking “wait, pictures of physicists still have lab equipment surrounding them. Presumably, instead of beakers, you still have to be doing something technical with your hands.” No. Let me explain. There are two types of physicists: experimental and theoretical. The distinction is easy to make. Experimental physicists (experimentalists) spend at least some of their time in a lab building devices to probe and test hypotheses about the world. Theoretical physicists (theorists) do not. I am one of the latter.

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OK, so I don’t wear a lab coat, I don’t use beakers, I don’t build anything, I don’t even step foot into a lab, what exactly do I do?

What does the internet say:

Theoretical physicists have a fascinating job that combines observation with mathematics in order to create complex formulas that describe the workings of the universe around us.

Not bad, but still not very illuminating in terms of my day-to-day life. In a business sense, I do create products: journal articles. These are usually 5–15 page papers which summarize a successful result, which can takes months to years to obtain. What they do not contain is any semblance of the blood, sweat and tears which make up the chaotic mess that went into them.

This mess can broken down into four tasks:

  1. Discuss problems with colleagues
  2. Perform mathematical calculations
  3. Read journal articles
  4. Write computer software

I don’t do every task every day, but on average my time is about equally spent on each.

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A day in the life of a postdoctoral theoretical physicist.

Much of every day is spent discussing problems with colleagues. Sometimes I seek advice on the problems I’m working from a co-worker; sometimes I am providing advice to others; and sometimes I am discussing a problem we are jointly working on. These are often brainstorming session which involve scribbling notes on a whiteboard and plenty of coffee.

Next, I perform mathematical calculations. This involves a lot of paper covered in the kinds of symbols pictured above. You’ll notice there is no arithmetic. These are abstract manipulations of symbols according to some rules. The fun part is that I sometimes get to make the rules! Most of the work done in this category gets trashed due to dead ends or errors and the rest gets heavily compressed if and when a journal article is written.

In order to find out what things others have tried and what techniques I can use to solve a problem, I read journal articles written by other scientists. Finding the right articles is a skill on its own given that over 2.5 million scientific journal articles are written each year. Often I find myself skimming over papers, picking out specific pieces. Occasionally, I am asked by a journal to evaluate the scientific merit of another article. This process is called peer review and could very well be the subject of a future post.

Lastly, there is coding. I write computer software that helps answer the scientific questions I have. For example, with my long-time friend and colleague Chris Granade I co-wrote Qinfer, which is statistical software for debugging small quantum computers. You’ll see examples of this and other software projects in future blog posts.

So there you have it. A day in the life of a postdoctoral theoretical physicist.