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Academia

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The Viewpoint Skeptics of Quantum Computers Don’t Want You To Hear

Quantum computers are fascinating devices.  Our current understanding of these devices is that they can do something that classical computers cannot: they can factor numbers in polynomial time (thank you Peter Shor!)  Interestingly, however, we can’t prove that these devices outperform classical computers on any class of problems.  What this means is something very particularly: we can’t show that the model of a quantum Turing machine can solve problems more efficiently than the classical model of a Turing machine.  Complexity theorists say that we can’t show that BPP does not equal BQP.  Complexity theorists remind me of my son learning new letters.  Sorry I can’t help it.  S. T. O. P. spells….stop!

A dark secret (okay it’s not really secret, but this is a blog) of classical computing is that we (or rather, they, since I’m as much a complexity theorist as I am handsomely good looking) also can’t say a lot along the same lines about classical computers.  The most famous example of this, currently (2012), is that classically we don’t know whether there are computations which take polynomial (in the size of the problem) space and unlimited time, but can’t be done with just a polynomial (in the size of the problem) limit in time.  In jargon this is the fact that we don’t know whether P (or BPP) equals PSPACE.  That’s a huge gap, because PSPACE includes nearly everything in the sun, including computers which use time machines.  That’s right.  Classical complexity theory has yet to show that computers that use frickin’ time machines aren’t more powerful than the laptop I’m typing this on.

A reasonable person, I would think, given this state of affairs, would admit that we just don’t know and try to figure out more about the model of quantum computation.  Interesting, however, academia attracts an interesting class of hyper smart person who try to get places in life by being contrarian.  That’s great when it leads to results, and often it does.  Being skeptical is an important part of the scientific process.  But when it doesn’t lead to results, which I think is the current state of arguments about quantum computers, it leads to senior professors acting very unprofessionally, and stifling a field.  Quantum computing is in exactly this state of existence.  I can count the number of jobs given to theorists in quantum computing over the last decade on my hands.  It’s far greater than the number of senior folks I’ve talked to who are credulously skeptical of quantum computers and show know better (i.e. they’ve at least read the relevant papers.)  The number who are skeptical but who haven’t actually read the papers?  My registers don’t count that high.

For an example of this phenomenon, hop on over at to the awesome and widely read blog Godel’s Lost Letter and P=NP where one of the coauthors of the blog Ken Regan has a post describing some work on trying to understanding the limits of quantum computers.  That’s great!  But in this post, Ken, who is an associate professor, can’t help but in a dig at quantum computers along the lines of “we can’t prove that it can’t do anything”:

But there is no proof today—let me repeat, no proof—that quantum circuits in BQP are not easy to simulate classically

Because I like poking tigers, and am no longer beholden to the whims of an academic community that strongly rejects quantum computing, I posted a comment (okay I’d post this even when I was a psuedo-professor) which included the last line

Oh, and, p.s. there is also no proof that classical circuits can’t solve NP-complete problems efficiently, but for some reason I don’t see that in all of your posts on classical computers ;)

to which Ken responded

As for “no proof”, Dick provided some thoughts which I merged into my intro; I pondered upgrading that line to add “…, nor even a convincing hardness argument”—but thought that better left-alone in the post

So you can see the kind of thoughts that go through many theoretical computer scientists which confronted with quantum computing.  Instead of “lets figure this out” the response is “I want to remind you that we haven’t proved anything, even though we also haven’t proved the same thing about likely even more powerful models of computation.”  If you don’t think this isn’t a case of bias in academia, then you’re reading a different novel than I am.  And if you don’t think this has an impact on junior academics, please see the correlation evidence of past hiring in academia (Or if you don’t like that: do an experiment.  Give the damn people the jobs to hang themselves by.  Or at least don’t give them advice to avoid quantum computing because of your own biases, I’m looking at you, you know who you are.  Pffst!)

Like I said, however, I think focusing on making actual progress in understanding quantum computers is the important path to take (and to the credit of Ken, who I’m picking on simply because he’s at the top of the temporal queue of a long line of guys who like to pontificate about the power of quantum computers without having any arguments that go beyond “I think…”, he has tried to answer this question.  But not without throwing in a backhand that he seems to find utterly professionally appropriate.)  And of course the previous two paragraphs are enough of the same ad slander’n reasoning, but exactly from my own completely biased perspective.  But toward being *ahem* productive, I’m completely convinced that quantum computers offer significant, proven, reasons to be built.  This is a controversial statement, because I know all complexity theorists will disagree with this point of view.  So this is aimed at the group of people with minds open enough to think not about complexity classes, but about real world experiments (we might call them, physicists.). 😉

The argument is almost as old as quantum computing itself.  These are the so called “black-box” query complexity results in quantum computing, albeit as seen through a physicist’s measuring device.  What these models do is as follows.  They consider a set of black box functions (say functions from n bits to 1 bit, so-called binary functions) and ask one to identify something about this set of black box functions.  For example, the set of functions could be all binary functions that are either constant (on all inputs they output 0 or on all inputs they output 1) or balanced (on half of inputs they output 0 and on the other half they output 1). Then the problem would be to distinguish whether, if I give you a machine that implements one of these functions, whether the function is constant or whether it is balanced.  Then one “measures” the effectiveness of an algorithm for solving this by the number of times that you have to use the black box in order to figure out which set the function belongs to.

So what is the state of query complexity differences between classical and quantum computers?  It can be proven that there are black box problems that can be solved by quantum computers using a polynomial number of queries in the size of the problem, but that require an exponential number of queries classical.  That’s right.  There is a proven exponential separation.  (For those who would like to argue that the comparison is not fair because a quantum device that computes a function implements a different physics than that which gives you a classical computation, I would only note that our world is quantum mechanical, and we can compare a quantum querying of the quantum device to a classical one.  A classical query of this quantum device is exponentially less efficient.)

At this point you may then wonder why all of the fuss about quantum computers not being proven to be more powerful than classical computers.  The answer is interesting and starts with the way we set up the problem.  We were given a black box that computes a classical function.  We can think about this literally as a machine that we can’t probe any deeper into how it actually works.  In this respect it is a sort of a-physical device, one that isn’t connected to the normal context of what a computation is (as modeled by, say a parallel Turing machine.)  Suppose that this were a real physical device, then you could take it apart and look at how it worked.  This means that you could get more information about the computation being performed.  And when you allow this, well, it is then not clear that you couldn’t solve the problems for which quantum computers offer speedups just as fast on a classical computer.  Thus while we know that with respect to these black box problems, quantum computers are exponentially faster than their classical brethren, we can’t carry this over to statements about models of computation.

But take a step back.  Suppose you are an experimental physicist and I give you a black box and ask you to figure out whether the box implements one or another sets of functions.  Well then, if you use this experimental device without peering into its innards, then you really really want to use a quantum computer for your experiment.  The difference between exponential graduate students and polynomial graduate students is most certainly something that will get your grant funded by the NSF.  Because the universe is quantum mechanical, damnit, and if you want to perform experiments that more quickly reveal how that universe operates, you’ve got to query it quantum mechanically to be most efficient.

Okay, you may not be convinced.  You may argue that at its heart you can’t ever have a box that one can’t take apart and probe its innards (can you?)  Fine.  So I’ll modify the game a bit.  I’ll give you a quantum system that is the output of the standard way this device if queried in these computeres $sum_x |x> |f(x)>$.  Now you either get to query this using only classical measurements on this device in the computational basis, or you get to use the full power of quantum computers, querying with a measurement you can build in your quantum laboratory.  In that case, you can show that a quantum experimentalist will exponentially outperform characterizing this state, i.e. solving the given promise problem.  Think about this as a game, a game in which you can win by being quantum mechanical exponentially faster than you could being classical.

Of course this won’t convince anyone, especially not classical theoretical computer scientists (who once were at the vanguard of a totally new field, but now find themselves defending their own legacy code.) Does it at least pass the test of trying to present evidence in either direction for the power of quantum computers?  Not really, for those who refuse to believe that quantum theory isn’t actually the right theory of nature.  But it does seem to tell us something is fundamentally very very different about the ability to use quantum theory in a setting where you’re trying to extract information about an unknown quantum system.  And it’s proven.  And it’s not a way of thinking that the old guys would like you to think 🙂

dabacon July 16, 2012 9 Comments Permalink

IDE Tools for Reading Research Papers?

It’s been over six months I made the jump from quantum computing theory professor at the University of Washington to software engineer at Google. When I hear from my friends back in quantum computing, the second question they ask is, “what’s it like?” (the first question is whether Google wants to build a quantum computer.)  There are lots of answers to this question, but what I think is really interesting is not how I feel about the ins and outs of this new career, but what I found the most surprising about the similarities between my new jobs and my old job.  And, for me, hands down, the most surprising similarity is between reading papers and reading other peoples code.

Reading a a paper in a new subject area was definitely one of the favorite parts of my old job (and a central skill to being a good researcher.)  You’d start out, often, with only a small clue about the subject of the paper.  Often you were led to the paper by a search that hit a few keywords, and an abstract that seemed interesting.  But after a few pages it often becomes clear that there are all sorts of terms and ideas that you just haven’t seen before.  And so you often have to spend some time doing some reading of other papers that contain the terms you don’t understand and see if they help.  Mostly they don’t, but sometimes they do and then you can backtrack and figure out some of what the first paper said.  This sort of jumping around, at least for me, occurred quite a bit as I’d try to parse a paper, interspread with periods of logical thought and pen and paper verification of calculations.

Reading other peoples code is very similar.  At first you start looking at some class, say, and you have some vague idea what it does.  Documentation and implicit documentation through naming gives  you some idea of what is going on, but quickly you often see the code start calling code that you don’t know how it works or what it exactly does, and so you have to go track down that other class, and then figure it out, and then backtrack.  Of course this is often interspread with bits of following the logic of the code.  Today, with modern IDE tools, this sort of jumping back and forth becomes a quick habit and makes the process of figuring out someone else’s code significantly easier.

Which got me thinking.  Why aren’t there modern tools for reading research documents that provide some of the functionality that is found in IDEs such as Eclipse?  Certainly some authors are gracious enough to compile their LaTeX such that their citation data is a link, but this is a long way from having PDFs where you can click on citations in the text and then you get immediately transported to the other paper, maybe even to the particular location in the paper that is relevant.  I think the technical challenge here is providing hooks between the documents: how do I make a citation that is more than just citing the full paper (wouldn’t it be nice if you specified the set of ranges of relevant lines in the paper?)  There are certainly very cool tools out there now for storing and parsing your scientific papers, but while the implicit linking between these papers is complex, most of this complexity is buried in the [12] citation pater.  But maybe solutions for this are already out there?  Thoughts?

dabacon January 15, 2012 7 Comments Permalink

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