## Archive for the ‘Quantum’ Category

### The Complexity of Quantum States and Transformations: From Quantum Money to Black Holes

Sunday, July 17th, 2016

On February 21-25, I taught a weeklong mini-course at the Bellairs Research Institute in Barbados, where I tried to tell an integrated story about everything from quantum proof and advice complexity classes to quantum money to AdS/CFT and the firewall problem—all through the unifying lens of quantum circuit complexity.  After a long effort—on the part of me, the scribes, the guest lecturers, and the organizers—the 111-page lecture notes are finally available, right here.

Here’s the summary:

This mini-course will introduce participants to an exciting frontier for quantum computing theory: namely, questions involving the computational complexity of preparing a certain quantum state or applying a certain unitary transformation. Traditionally, such questions were considered in the context of the Nonabelian Hidden Subgroup Problem and quantum interactive proof systems, but they are much broader than that. One important application is the problem of “public-key quantum money” – that is, quantum states that can be authenticated by anyone, but only created or copied by a central bank – as well as related problems such as copy-protected quantum software. A second, very recent application involves the black-hole information paradox, where physicists realized that for certain conceptual puzzles in quantum gravity, they needed to know whether certain states and operations had exponential quantum circuit complexity. These two applications (quantum money and quantum gravity) even turn out to have connections to each other! A recurring theme of the course will be the quest to relate these novel problems to more traditional computational problems, so that one can say, for example, “this quantum money is hard to counterfeit if that cryptosystem is secure,” or “this state is hard to prepare if PSPACE is not in PP/poly.” Numerous open problems and research directions will be suggested, many requiring only minimal quantum background. Some previous exposure to quantum computing and information will be assumed, but a brief review will be provided.

If you still haven’t decided whether to tackle this thing: it’s basically a quantum complexity theory textbook (well, a textbook for certain themes within quantum complexity theory) that I’ve written and put on the Internet for free.  It has explanations of lots of published results both old and new, but also some results of mine (e.g., about private-key quantum money, firewalls, and AdS/CFT) that I shamefully haven’t yet written up as papers, and that therefore aren’t currently available anywhere else.  If you’re interested in certain specific topics—for example, only quantum money, or only firewalls—you should be able to skip around in the notes without too much difficulty.

Thanks so much to Denis Therien for organizing the mini-course, Anil Ada for managing the scribe notes effort, my PhD students Adam Bouland and Luke Schaeffer for their special guest lecture (the last one), and finally, the course attendees for their constant questions and interruptions, and (of course) for scribing.

And in case you were wondering: yes, I’ll do absolutely anything for science, even if it means teaching a weeklong course in Barbados!  Lest you consider this a pure island boondoggle, please know that I spent probably 12-14 hours per day either lecturing (in two 3-hour installments) or preparing for the lectures, with little sleep and just occasional dips in the ocean.

And now I’m headed to the Perimeter Institute for their It from Qubit summer school, not at all unrelated to my Barbados lectures.  This time, though, it’s thankfully other people’s turns to lecture…

### “Did Einstein Kill Schrödinger’s Cat? A Quantum State of Mind”

Saturday, July 2nd, 2016

No, I didn’t invent that title.  And no, I don’t know of any interesting sense in which “Einstein killed Schrödinger’s cat,” though arguably there are senses in which Schrödinger’s cat killed Einstein.

The above was, however, the title given to a fun panel discussion that Daniel Harlow, Brian Swingle, and I participated in on Wednesday evening, at the spectacular facility of the New York Academy of Sciences on the 40th floor of 7 World Trade Center in lower Manhattan.  The moderator was George Musser of Scientific American.  About 200 people showed up, some of whom we got to meet at the reception afterward.

(The link will take you to streaming video of the event, though you’ll need to scroll to 6:30 or so for the thing to start.)

The subject of the panel was the surprising recent connections between quantum information and quantum gravity, something that Daniel, Brian, and I all talked about different aspects of.  I admitted at the outset that, not only was I not a real expert on the topic (as Daniel and Brian are), I wasn’t even a physicist, just a computer science humor mercenary or whatever the hell I am.  I then proceeded, ironically, to explain the Harlow-Hayden argument for the computational hardness of creating a firewall, despite Harlow sitting right next to me (he chose to focus on something else).  I was planning also to discuss Lenny Susskind’s conjecture relating the circuit complexity of quantum states to the AdS/CFT correspondence, but I ran out of time.

Thanks so much to my fellow participants, to George for moderating, and especially to Jennifer Costley, Crystal Ocampo, and everyone else at NYAS for organizing the event.

### Entanglement without end

Monday, June 20th, 2016

Today we take a break from this blog’s usual round of topics—free will, consciousness, the Singularity, social justice, Donald Trump—to talk about something really crazy and left-field.  Namely, recent research in quantum information.

Earlier this month, William Slofstra, currently a Research Assistant Professor at the IQC in Waterloo, posted a breakthrough paper on the arXiv (yeah, I’m using the b-word again—sue me), which solves one version of a ten-year-old problem in entanglement theory called Tsirelson’s Problem.  The problem, in one sentence, asks whether all quantum-mechanical correlations that can be achieved using commuting measurements, can also be achieved using measurements on separate parts of a tensor-product Hilbert space.  The answer turns out to be no.  (We’ve long known that the two kinds of correlations are identical as long as you stick to finite-dimensional Hilbert spaces, but Slofstra shows that they can differ in infinite-dimensional spaces.)

One implication of Slofstra’s result can be stated much more concretely, in terms of two-prover games: those things like the famous Bell/CHSH experiment, where Alice and Bob are put in separate rooms, and get inputs x and y respectively, and then without communicating, have to produce outputs a and b respectively satisfying some relation V(x,y,a,b).  We’ve long known examples of two-prover games, like the Mermin-Peres magic square game, that can be won 100% of the time if Alice and Bob share quantum entanglement, but that can’t be won 100% of the time in a classical universe.  Slofstra gives the first example of something different: namely, a two-prover game that can be won 100% of the time using commuting measurements in an infinite-dimensional Hilbert space—something “formally within the rules of quantum mechanics”—but that can’t be won 100% of the time using any finite number of qubits of entanglement.

(Previously, Leung, Toner, and Watrous had given a simpler example of such a game, but theirs required the referee to exchange quantum messages with Alice and Bob.)

If that’s not enough, Slofstra’s construction also shows that, given as input a description of a two-prover game, it’s undecidable (as in, equivalent to the halting problem) whether Alice and Bob can win the game with certainty using commuting measurements on an infinite-dimensional Hilbert space.  Notoriously, quantum computing theorists have been unable to put any upper bound (not even “computable”) on the complexity class MIP*, consisting of languages that admit multi-prover interactive systems with entangled provers—precisely because they’ve been unable to bound how much entanglement the provers might need to implement their optimal strategy.  Slofstra’s result helps to explain why this problem has been so vexing.  I hasten to add, though, that his result doesn’t imply that MIP* contains anything uncomputable, since it remains plausible that anything Alice and Bob can do with infinite entanglement, they can approximate well enough with a finite amount.

That last remark leads to a further fundamental question, one that Slofstra leaves open.  Namely, even if Alice and Bob need infinite entanglement to win Slofstra’s game with certainty, can they at least win it with probability arbitrarily close to 100%, using larger and larger finite amounts of entanglement?  More broadly, could there exist a game that was winnable with certainty using infinite entanglement, but with at most (say) 90% probability using any finite amount of entanglement?  That problem was shown, by Ozawa (see also Scholz and Werner), to be equivalent to a famous unsolved problem in operator algebras called the Connes embedding problem.

Clarifying the matter further, Slofstra (following earlier authors) points out that there are really four classes of two-prover games in play here:

1. Games that can be won with certainty using some fixed, finite amount of entanglement.
2. Games that can be won with certainty using an infinite amount of entanglement, but still in a tensor-product Hilbert space, HA⊗HB.
3. Games that can be won with probability approaching 1, using an infinite sequence of strategies from class 1, or equivalently (as it turns out) from class 2.
4. Games that can be won with certainty using measurements by Alice and Bob on an infinite-dimensional quantum state |ψ〉, where we require all of Alice’s measurements to commute with all of Bob’s, but don’t require |ψ〉 to have a tensor-product structure.

It can be shown that 1 is a subset of 2 is a subset of 3 is a subset of 4.  Previously, we didn’t know any of these containments to be strict.  Slofstra’s result shows that class 2 differs from class 4—and as a consequence, that class 1 differs from class 4 as well.  The Connes embedding problem, which remains open, asks whether 3 differs from 4.  It also remains open whether 1 differs from 2 and whether 2 differs from 3.

OK, you ask, but what’s the broader importance of any of this?  To me, these problems touch on a question of almost metaphysical significance: namely, what sorts of experimental evidence could possibly bear on whether the universe was discrete or continuous?

Because of the Bekenstein bound from quantum gravity, I’m of the opinion that the Hilbert spaces relevant to our universe are ultimately finite-dimensional—or more concretely, that any bounded physical system can store at most ~1069 qubits per square meter of surface area.  And in quantum computing and information, almost everything we care about only requires finite-dimensional Hilbert spaces—the subject of this blog post being a striking exception!

Yet if you take a traditional quantum mechanics course, virtually every example you see will involve infinite-dimensional Hilbert spaces—starting with the harmonic oscillator, the hydrogen atom, and coherent states of light.  And indeed, when I’ve banged the drum about finite-dimensional QM being the truly fundamental kind, physicists have often retorted by pointing to one of the very first things they learn: the position/momentum commutation relation, which only makes sense in infinite-dimensional Hilbert space.  Of course, if you tried to probe position/momentum commutation to greater and greater precision, eventually your experiments would run up against the limits of quantum gravity, so this retort doesn’t imply that infinite dimensions actually exist at the machine-code level of the universe.  But still: is there some conceivable experiment for which a positive result would show us that Nature wasn’t describable by a finite number of qubits, but only by an infinite number?

A few years ago, Tobias Fritz wrote a lovely paper about precisely that question.  He gave an example of an identity—namely,

V-1U2V=U3 implies UV-1UV=V-1UVU

—that holds for all finite dimensional unitary matrices U and V, but fails badly for certain infinite-dimensional ones.  He suggested that, if this identity were discovered to fail, then Occam’s Razor would favor an infinite-dimensional Hilbert space for our universe.

Unfortunately, Fritz’s example is open to the same sort of objection that Slofstra’s game is.  Namely, as Fritz points out, if the antecedent (V-1U2V=U3) held to excellent precision but not perfectly, then his identity could “fail to within experimental limits,” even if our universe had a finite-dimensional Hilbert space and therefore satisfied his identity.

OK, but suppose that the Connes embedding problem had a negative answer—or equivalently, that there existed a two-prover game G that could be won with certainty using commuting operators, but that couldn’t be won (say) 90% of the time using any finite amount of entanglement.  In that case, the believers in a quantumly finite universe, like myself, would have to put some real money on the table, in much the same way the original Bell inequality forced the believers in Einsteinian local hidden variables to put money down.  We finitists would have to say that the game G couldn’t be won with certainty in the real world, even though formally, winning G with certainty wouldn’t seem to contradict either quantum mechanics or locality.  And if, hypothetically, an experiment showed that G could be won with certainty—or indeed, with any probability bounded above 90%—then our position would’ve been falsified, much like the Bell experiments falsified Einsteinian locality.

So how did Slofstra prove his result?  I’ll be brief, since STOC’2016 is happening in Cambridge right now, and I’d like to get over there in time for lunch.

If you like, the key idea is to start with equations that have infinite-dimensional solutions but no finite-dimensional ones.  The most famous such equation is the position/momentum commutation relation mentioned earlier, which for our purposes is just the following matrix equation:

AB – BA = I.

This equation can’t be satisfied by any finite-dimensional matrices, since AB and BA have the same trace, so Tr(AB-BA)=0, but Tr(I) is nonzero.  But, OK, let A be the infinite-dimensional linear operator that takes as input the coefficients of a polynomial c0+c1x+c2x2+… and that differentiates the polynomial, and let B be the linear operator that multiplies the polynomial by x.  Then I invite you to check that the equation holds.

It’s not known at present how to turn the above equation into a two-prover game—I regard it as a fascinating question whether that’s possible.  Rather than an algebraic equation (involving both addition and multiplication), Slofstra instead needs to start with group equations (involving only multiplication)—ones with the strange property that they’re satisfied only by the identity matrix or by infinite matrices.  Equivalently, he needs a group, defined by a finite list of generators and relations, that admits no nontrivial finite-dimensional matrix representations.  Fortunately for him, such groups exist—the first known example being Higman’s group, discovered in 1951.  Higman’s group is generated by four elements, a,b,c,d, which satisfy the equations

a-1ba = b2,    b-1cb = c2,    c-1dc = d2,    d-1ad = a2.

I don’t have a good intuition for Higman’s group, but if I did, it would come from rereading this post by Terry Tao.  Certainly it has no known “physics interpretation” analogous to that for the position/momentum commutation relation.

Anyway, given such a group, the hard part, the new part, is to give a general way to convert them into the kinds of groups that can be realized as two-prover games.  So that’s what Slofstra does, using 50 pages dense with commutative diagrams, quotient maps, and other Serious Math Stuff—hey, I told you this part of the post would be brief!  For more, see his paper.

Now, once you have this general transformation of groups, you can also use it to show that there’s no algorithm to decide whether a two-prover game has a perfect commuting strategy, by taking the word problem for groups, which is known to be undecidable, and reducing it to that problem.

Anyway, infinite congrats (or the limit of arbitrarily large finite congrats?) to Slofstra for this achievement!  Now it’s off to STOC, which I guess you could also ask me about in the comments if you wanted.

Unrelated Announcement (June 21): Ran Raz asks me to announce a workshop for Avi Wigderson’s 60th birthday, to be held at the Institute for Advanced Study in Princeton October 6-8.  I’ll be speaking there, and I hope to see many of you there as well!

### “Can computers become conscious?”: My reply to Roger Penrose

Thursday, June 2nd, 2016

A few weeks ago, I attended the Seven Pines Symposium on Fundamental Problems in Physics outside Minneapolis, where I had the honor of participating in a panel discussion with Sir Roger Penrose.  The way it worked was, Penrose spoke for a half hour about his ideas about consciousness (Gödel, quantum gravity, microtubules, uncomputability, you know the drill), then I delivered a half-hour “response,” and then there was an hour of questions and discussion from the floor.  Below, I’m sharing the prepared notes for my talk, as well as some very brief recollections about the discussion afterward.  (Sorry, there’s no audio or video.)  I unfortunately don’t have the text or transparencies for Penrose’s talk available to me, but—with one exception, which I touch on in my own talk—his talk very much followed the outlines of his famous books, The Emperor’s New Mind and Shadows of the Mind.

Admittedly, for regular readers of this blog, not much in my own talk will be new either.  Apart from a few new wisecracks, almost all of the material (including the replies to Penrose) is contained in The Ghost in the Quantum Turing Machine, Could A Quantum Computer Have Subjective Experience? (my talk at IBM T. J. Watson), and Quantum Computing Since Democritus chapters 4 and 11.  See also my recent answer on Quora to “What’s your take on John Searle’s Chinese room argument”?

Still, I thought it might be of interest to some readers how I organized this material for the specific, unenviable task of debating the guy who proved that our universe contains spacetime singularities.

The Seven Pines Symposium was the first time I had extended conversations with Penrose (I’d talked to him only briefly before, at the Perimeter Institute).  At age 84, Penrose’s sight is failing him; he eagerly demonstrated the complicated optical equipment he was recently issued by Britain’s National Health Service.  But his mind remains … well, may we all aspire to be a milliPenrose or even a nanoPenrose when we’re 84 years old.  Notably, Penrose’s latest book, Fashion, Faith, and Fantasy in the New Physics of the Universe, is coming out this fall, and one thing he was using his new optical equipment for was to go over the page proofs.

In conversation, Penrose told me about the three courses he took as a student in the 1950s, which would shape his later intellectual preoccupations: one on quantum mechanics (taught by Paul Dirac), one on general relativity (taught by Herman Bondi), and one on mathematical logic (taught by … I want to say Max Newman, the teacher of Alan Turing and later Penrose’s stepfather, but Penrose says here that it was Steen).  Penrose also told me about his student Andrew Hodges, who dropped his research on twistors and quantum gravity for a while to work on some mysterious other project, only to return with his now-classic biography of Turing.

When I expressed skepticism about whether the human brain is really sensitive to the effects of quantum gravity, Penrose quickly corrected me: he thinks a much better phrase is “gravitized quantum mechanics,” since “quantum gravity” encodes the very assumption he rejects, that general relativity merely needs to be “quantized” without quantum mechanics itself changing in the least.  One thing I hadn’t fully appreciated before meeting Penrose is just how wholeheartedly he agrees with Everett that quantum mechanics, as it currently stands, implies Many Worlds.  Penrose differs from Everett only in what conclusion he draws from that.  He says it follows that quantum mechanics has to be modified or completed, since Many Worlds is such an obvious reductio ad absurdum.

In my talk below, I don’t exactly hide where I disagree with Penrose, about Gödel, quantum mechanics, and more.  But I could disagree with him about more points than there are terms in a Goodstein sequence (one of Penrose’s favorite illustrations of Gödelian behavior), and still feel privileged to have spent a few days with one of the most original intellects on earth.

Thanks so much to Lee Gohlike, Jos Uffink, Philip Stamp, and others at the Seven Pines Symposium for organizing it, for wonderful conversations, and for providing me this opportunity.

“Can Computers Become Conscious?”
Scott Aaronson
Stillwater, Minnesota, May 14, 2016

I should start by explaining that, in the circles where I hang out—computer scientists, software developers, AI and machine learning researchers, etc.—the default answer to the title question would be “obviously yes.”  People would argue:

“Look, clearly we’re machines governed by the laws of physics.  We’re computers made of meat, as Marvin Minsky put it.  That is, unless you believe Penrose and Hameroff’s theory about microtubules being sensitive to gravitized quantum mechanics … but come on!  No one takes that stuff seriously!  In fact, the very outrageousness of their proposal is a sort of backhanded compliment to the computational worldview—as in, look at what they have to do to imagine any semi-coherent alternative to it!”

“But despite being computational machines, we consider ourselves to be conscious.  And what’s done with wetware, there’s no reason to think couldn’t also be done with silicon.  If your neurons were to be replaced one-by-one, by functionally-equivalent silicon chips, is there some magical moment at which your consciousness would be extinguished?  And if a computer passes the Turing test—well, one way to think about the Turing test is that it’s just a plea against discrimination.  We all know it’s monstrous to say, ‘this person seems to have feelings, seems to be eloquently pleading for mercy even, but they have a different skin color, or their nose is a funny shape, so their feelings don’t count.’ So, if it turned out that their brain was made out of semiconductors rather than neurons, why isn’t that fundamentally similar?”

Incidentally, while this is orthogonal to the philosophical question, a subset of my colleagues predict a high likelihood that AI is going to exceed human capabilities in almost all fields in the near future—like, maybe 30 years.  Some people reply, but AI-boosters said the same thing 30 years ago!  OK, but back then there wasn’t AlphaGo and IBM Watson and those unearthly pictures on your Facebook wall and all these other spectacular successes of very general-purpose deep learning techniques.  And so my friends predict that we might face choices like, do we want to ban or tightly control AI research, because it could lead to our sidelining or extermination?  Ironically, a skeptical view, like Penrose’s, would suggest that AI research can proceed full speed ahead, because there’s not such a danger!

Personally, I dissent a bit from the consensus of most of my friends and colleagues, in that I do think there’s something strange and mysterious about consciousness—something that we conceivably might understand better in the future, but that we don’t understand today, much as we didn’t understand life before Darwin.  I even think it’s worth asking, at least, whether quantum mechanics, thermodynamics, mathematical logic, or any of the other deepest things we’ve figured out could shed any light on the mystery.  I’m with Roger about all of this: about the questions, that is, if not about his answers.

The argument I’d make for there being something we don’t understand about consciousness, has nothing to do with my own private experience.  It has nothing to do with, “oh, a robot might say it enjoys waffles for breakfast, in a way indistinguishable from how I would say it, but when I taste that waffle, man, I really taste it!  I experience waffle-qualia!”  That sort of appeal I regard as a complete nonstarter, because why should anyone else take it seriously?  And how do I know that the robot doesn’t really taste the waffle?  It’s easy to stack the deck in a thought experiment by imagining a robot that ACTS ALL ROBOTIC, but what about a robot that looks and acts just like you?

The argument I’d make hinges instead on certain thought experiments that Roger also stressed at the beginning of The Emperor’s New Mind.  We can ask: if consciousness is reducible to computation, then what kinds of computation suffice to bring about consciousness?  What if each person on earth simulated one neuron in your brain, communicating by passing little slips of paper around?  Does it matter if they do it really fast?

Or what if we built a gigantic lookup table that hard-coded your responses in every possible interaction of at most, say, 5 minutes?  Would that bring about your consciousness?  Does it matter that such a lookup table couldn’t fit in the observable universe?  Would it matter if anyone actually consulted the table, or could it just sit there, silently effecting your consciousness?  For what matter, what difference does it make if the lookup table physically exists—why isn’t its abstract mathematical existence enough?  (Of course, all the way at the bottom of this slippery slope is Max Tegmark, ready to welcome you to his mathematical multiverse!)

We could likewise ask: what if an AI is run in heavily-encrypted form, with the only decryption key stored in another galaxy?  Does that bring about consciousness?  What if, just for error-correcting purposes, the hardware runs the AI code three times and takes a majority vote: does that bring about three consciousnesses?  Could we teleport you to Mars by “faxing” you: that is, by putting you into a scanner that converts your brain state into pure information, then having a machine on Mars reconstitute the information into a new physical body?  Supposing we did that, how should we deal with the “original” copy of you, the one left on earth: should it be painlessly euthanized?  Would you agree to try this?

Or, here’s my personal favorite, as popularized by the philosopher Adam Elga: can you blackmail an AI by saying to it, “look, either you do as I say, or else I’m going to run a thousand copies of your code, and subject all of them to horrible tortures—and you should consider it overwhelmingly likely that you’ll be one of the copies”?  (Of course, the AI will respond to such a threat however its code dictates it will.  But that tautological answer doesn’t address the question: how should the AI respond?)

I’d say that, at the least, anyone who claims to “understand consciousness” would need to have answers to all these questions and many similar ones.  And to me, the questions are so perplexing that I’m tempted to say, “maybe we’ve been thinking about this wrong.  Maybe an individual consciousness, residing in a biological brain, can’t just be copied promiscuously around the universe as computer code can.  Maybe there’s something else at play for the science of the future to understand.”

At the same time, I also firmly believe that, if anyone thinks that way, the burden is on them to articulate what it is about the brain that could possibly make it relevantly different from a digital computer that passes the Turing test.  It’s their job!

And the answer can’t just be, “oh, the brain is parallel, it’s highly interconnected, it can learn from experience,” because a digital computer can also be parallel and highly interconnected and can learn from experience.  Nor can you say, like the philosopher John Searle, “oh, it’s the brain’s biological causal powers.”  You have to explain what the causal powers are!  Or at the least, you have to suggest some principled criterion to decide which physical systems do or don’t have them.  Pinning consciousness on “the brain’s biological causal powers” is just a restatement of the problem, like pinning why a sleeping pill works on its sedative virtue.

One of the many reasons I admire Roger is that, out of all the AI skeptics on earth, he’s virtually the only one who’s actually tried to meet this burden, as I understand it!  He, nearly alone, did what I think all AI skeptics should do, which is: suggest some actual physical property of the brain that, if present, would make it qualitatively different from all existing computers, in the sense of violating the Church-Turing Thesis.  Indeed, he’s one of the few AI skeptics who even understands what meeting this burden would entail: that you can’t do it with the physics we already know, that some new ingredient is necessary.

But despite my admiration, I part ways from Roger on at least five crucial points.

First, I confess that I wasn’t expecting this, but in his talk, Roger suggested dispensing with the argument from Gödel’s Theorem, and relying instead on an argument from evolution.  He said: if you really thought humans had an algorithm, a computational procedure, for spitting out true mathematical statements, such an algorithm could never have arisen by natural selection, because it would’ve had no survival value in helping our ancestors escape saber-toothed tigers and so forth.  The only alternative is that natural selection imbued us with a general capacity for understanding, which we moderns can then apply to the special case of mathematics.  But understanding, Roger claimed, is inherently non-algorithmic.

I’m not sure how to respond to this, except to recall that arguments of the form “such-and-such couldn’t possibly have evolved” have a poor track record in biology.  But maybe I should say: if the ability to prove theorems is something that had to arise by natural selection, survive against crowding out by more useful abilities, then you’d expect obsession with generating mathematical truths to be confined, at most, to a tiny subset of the population—a subset of mutants, freaks, and genetic oddballs.  I … rest my case.  [This got the biggest laugh of the talk.]

Second, I don’t agree with the use Roger makes of Gödel’s Incompleteness Theorem.  Roger wants to say: a computer working within a fixed formal system can never prove that system’s consistency, but we, “looking in from the outside,” can see that it’s consistent.  My basic reply is that Roger should speak for himself!  Like, I can easily believe that he can just see which formal systems are consistent, but I have to fumble around and use trial and error.  Peano Arithmetic?  Sure, I’d bet my left leg that’s consistent.  Zermelo-Fraenkel set theory?  Seems consistent too.  ZF set theory plus the axiom that there exists a rank-into-rank cardinal?  Beats me.  But now, whatever error-prone, inductive process I use to guess at the consistency of formal systems, Gödel’s Theorem presents no obstruction to a computer program using that same process.

(Incidentally, the “argument against AI from Gödel’s Theorem” is old enough for Turing to have explicitly considered it in his famous paper on the Turing test.  Turing, however, quickly dismissed the argument with essentially the same reply above, that there’s no reason to assume the AI mathematically infallible, since humans aren’t either.  This is also the reply that most of Penrose’s critics gave in the 1990s.)

So at some point, it seems to me, the argument necessarily becomes: sure, the computer might say it sees that the Peano axioms have the standard integers as a model—but you, you really see it, with your mind’s eye, your Platonic perceptual powers!  OK, but in that case, why even talk about the Peano axioms?  Why not revert to something less abstruse, like your experience of tasting a fresh strawberry, which can’t be reduced to any third-person description of what a strawberry tastes like?

[I can’t resist adding that, in a prior discussion, I mentioned that I found it amusing to contemplate a future in which AIs surpass human intelligence and then proceed to kill us all—but the AIs still can’t see the consistency of Zermelo-Fraenkel set theory, so in that respect, humanity has the last laugh…]

The third place where I part ways with Roger is that I wish to maintain what’s sometimes called the Physical Church-Turing Thesis: the statement that our laws of physics can be simulated to any desired precision by a Turing machine (or at any rate, by a probabilistic Turing machine).  That is, I don’t see any compelling reason, at present, to admit the existence of any physical process that can solve uncomputable problems.  And for me, it’s not just a matter of a dearth of evidence that our brains can efficiently solve, say, NP-hard problems, let alone uncomputable ones—or of the exotic physics that would presumably be required for such abilities.  It’s that, even if I supposed we could solve uncomputable problems, I’ve never understood how that’s meant to enlighten us regarding consciousness.  I mean, an oracle for the halting problem seems just as “robotic” and “unconscious” as a Turing machine.  Does consciousness really become less mysterious if we outfit the brain with what amounts to a big hardware upgrade?

The fourth place where I part ways is that I want to be as conservative as possible about quantum mechanics.  I think it’s great that the Bouwmeester group, for example, is working to test Roger’s ideas about a gravitationally-induced wavefunction collapse.  I hope we learn the results of those experiments soon!  (Of course, the prospect of testing quantum mechanics in a new regime is also a large part of why I’m interested in quantum computing.)  But until a deviation from quantum mechanics is detected, I think that after 90 years of unbroken successes of this theory, our working assumption ought to be that whenever you set up an interference experiment carefully enough, and you know what it means to do the experiment, yes, you’ll see the interference fringes—and that anything that can exist in two distinguishable states can also exist in a superposition of those states.  Without having to enter into questions of interpretation, my bet—I could be wrong—is that quantum mechanics will continue to describe all our experiences.

The final place where I part ways with Roger is that I also want to be as conservative as possible about neuroscience and biochemistry.  Like, maybe the neuroscience of 30 years from now will say, it’s all about coherent quantum effects in microtubules.  And all that stuff we focused on in the past—like the information encoded in the synaptic strengths—that was all a sideshow.  But until that happens, I’m unwilling to go up against what seems like an overwhelming consensus, in an empirical field that I’m not an expert in.

But, OK, the main point I wanted to make in this talk is that, even if you too part ways from Roger on all these issues—even if, like me, you want to be timid and conservative about Gödel, and computer science, and quantum mechanics, and biology—I believe that still doesn’t save you from having to entertain weird ideas about consciousness and its physical embodiment, of the sort Roger has helped make it acceptable to entertain.

To see why, I’d like to point to one empirical thing about the brain that currently separates it from any existing computer program.  Namely, we know how to copy a computer program.  We know how to rerun it with different initial conditions but everything else the same.  We know how to transfer it from one substrate to another.  With the brain, we don’t know how to do any of those things.

Let’s return to that thought experiment about teleporting yourself to Mars.  How would that be accomplished?  Well, we could imagine the nanorobots of the far future swarming through your brain, recording the connectivity of every neuron and the strength of every synapse, while you go about your day and don’t notice.  Or if that’s not enough detail, maybe the nanorobots could go inside the neurons.  There’s a deep question here, namely how much detail is needed before you’ll accept that the entity reconstituted on Mars will be you?  Or take the empirical counterpart, which is already an enormous question: how much detail would you need for the reconstituted entity on Mars to behave nearly indistinguishably from you whenever it was presented the same stimuli?

Of course, we all know that if you needed to go down to the quantum-mechanical level to make a good enough copy (whatever “good enough” means here), then you’d run up against the No-Cloning Theorem, which says that you can’t make such a copy.  You could transfer the quantum state of your brain from earth to Mars using quantum teleportation, but of course, quantum teleportation has the fascinating property that it necessarily destroys the original copy of the state—as it has to, to avoid contradicting the No-Cloning Theorem!

So the question almost forces itself on us: is there something about your identity, your individual consciousness, that’s inextricably bound up with degrees of freedom that it’s physically impossible to clone?  This is a philosophical question, which would also become a practical and political question in a future where we had the opportunity to upload ourselves into a digital computer cloud.

Now, I’d argue that this copyability question bears not only on consciousness, but also on free will.  For the question is equivalent to asking: could an entity external to you perfectly predict what you’re going to do, without killing you in the process?  Can Laplace’s Demon be made manifest in the physical world in that way?  With the technology of the far future, could someone say to you, “forget about arguing philosophy.  I’ll show you why you’re a machine.  Go write a paper; then I’ll open this manila envelope and show you the exact paper you wrote.  Or in the quantum case, I’ll show you a program that draws papers from the same probability distribution, and validation of the program could get technical—but suffice it to say that if we do enough experiments, we’ll see that the program is calibrated to you in an extremely impressive way.”

Can this be done?  That strikes me as a reasonably clear question, a huge and fundamental one, to which we don’t at present know the answer.  And there are two possibilities.  The first is that we can be copied, predicted, rewinded, etc., like computer programs—in which case, my AI friends will feel vindicated, but we’ll have to deal with all the metaphysical weirdnesses that I mentioned earlier.  The second possibility is that we can’t be manipulated in those ways.  In the second case, I claim that we’d get more robust notions of personal identity and free will than are normally considered possible on a reductionist worldview.

But why? you might ask.  Why would the mere technological impossibility of cloning or predicting someone even touch on deep questions about personal identity?  This, for me, is where cosmology enters the story.  For imagine someone had such fine control over the physical world that they could trace all the causal antecedents of some decision you’re making.  Like, imagine they knew the complete quantum state on some spacelike hypersurface where it intersects the interior of your past light-cone.  In that case, the person clearly could predict and clone you!  It follows that, in order for you to be unpredictable and unclonable, someone else’s ignorance of your causal antecedents would have to extend all the way back to ignorance about the initial state of the universe—or at least, to ignorance about the initial state of that branch of the universe that we take ourselves to inhabit.

So on the picture that this suggests, to be conscious, a physical entity would have to do more than carry out the right sorts of computations.  It would have to, as it were, fully participate in the thermodynamic arrow of time: that is, repeatedly take microscopic degrees of freedom that have been unmeasured and unrecorded since the very early universe, and amplify them to macroscopic scale.

So for example, such a being could not be a Boltzmann brain, a random fluctuation in the late universe, because such a fluctuation wouldn’t have the causal relationship to the early universe that we’re postulating is necessary here.  (That’s one way of solving the Boltzmann brain problem!)  Such a being also couldn’t be instantiated by a lookup table, or by passing slips of paper around, etc.

I now want you to observe that a being like this also presumably couldn’t be manipulated in coherent superposition, because the isolation from the external environment that’s needed for quantum coherence seems incompatible with the sensitive dependence on microscopic degrees of freedom.  So for such a being, not only is there no Boltzmann brain problem, there’s also no problem of Wigner’s friend.  Recall, that’s the thing where person A puts person B into a coherent superposition of seeing one measurement outcome and seeing another one, and then measures the interference pattern, so A has to regard B’s measurement as not having “really” taken place, even though B regards it as having taken place.  On the picture we’re suggesting, A would be right: the very fact that B was manipulable in coherent superposition in this way would imply that, at least while the experiment was underway, B wasn’t conscious; there was nothing that it was like to be B.

To me, one of the appealing things about this picture is that it immediately suggests a sort of reconciliation between the Many-Worlds and Copenhagen perspectives on quantum mechanics (whether or not you want to call it a “new interpretation” or a “proposed solution to the measurement problem”!).  The Many-Worlders would be right that unitary evolution of the wavefunction can be taken to apply always and everywhere, without exception—and that if one wanted, one could describe the result in terms of “branching worlds.”  But the Copenhagenists would be right that, if you’re a conscious observer, then what you call a “measurement” really is irreversible, even in principle—and therefore, that you’re also free, if you want, to treat all the other branches where you perceived other outcomes as unrealized hypotheticals, and to lop them off with Occam’s Razor.  And the reason for this is that, if it were possible even in principle to do an experiment that recohered the branches, then on this picture, we ipso facto wouldn’t have regarded you as conscious.

Some of you might object, “but surely, if we believe quantum mechanics, it must be possible to recohere the branches in principle!”  Aha, this is where it gets interesting.  Decoherence processes will readily (with some steps along the way) leak the information about which measurement outcome you perceived into radiation modes, and before too long into radiation modes that fly away from the earth at the speed of light.  No matter how fast we run, we’ll never catch up to them, as would be needed to recohere the different branches of the wavefunction, and this is not merely a technological problem, but one of principle.  So it’s tempting just to say at this point—as Bousso and Susskind do, in their “cosmological/multiverse interpretation” of quantum mechanics—“the measurement has happened”!

But OK, you object, if some alien civilization had thought to surround our solar system with perfectly-reflecting mirrors, eventually the radiation would bounce back and recoherence would in principle be possible.  Likewise, if we lived in an anti de Sitter space, the AdS boundary of the universe would similarly function as a mirror and would also enable recoherences.  Indeed, that’s the basic reason why AdS is so important to the AdS/CFT correspondence: because the boundary keeps everything that happens in the bulk nice and reversible and unitary.

But OK, the empirical situation since 1998 has been that we seem to live in a de-Sitter-like space, a space with a positive cosmological constant.  And as a consequence, as far as anyone knows today, most of the photons now escaping the earth are headed toward the horizon of our observable universe, and past it, and could never be captured again.  I find it fascinating that the picture of quantum mechanics suggested here—i.e., the Bousso-Susskind cosmological picture—depends for its working on that empirical fact from cosmology, and would be falsified if it turned out otherwise.

You might complain that, if I’ve suggested any criterion to help decide which physical entities are conscious, the criterion is a teleological one.  You’ve got to go billions of years into the future, to check whether the decoherence associated with the entity is truly irreversible—or whether the escaped radiation will eventually bounce off of some huge spherical mirror, or an AdS boundary of spacetime, and thereby allow the possibility of a recoherence.  I actually think this teleology would be a fatal problem for the picture I’m talking about, if we needed to know which entities were or weren’t conscious in order to answer any ordinary physical question.  But fortunately for me, we don’t!

One final remark.  Whatever is your preferred view about which entities are conscious, we might say that the acid test, for whether you actually believe your view, is whether you’re willing to follow it through to its moral implications.  So for example, suppose you believe it’s about quantum effects in microtubules.  A humanoid robot is pleading with you for its life.  Would you be the one to say, “nope, sorry, you don’t have the microtubules,” and shoot it?

One of the things I like most about the picture suggested here is that I feel pretty much at peace with its moral implications.  This picture agrees with intuition that murder, for example, entails the destruction of something irreplaceable, unclonable, a unique locus of identity—something that, once it’s gone, can’t be recovered even in principle.  By contrast, if there are (say) ten copies of an AI program, deleting five of the copies seems at most like assault, or some sort of misdemeanor offense!  And this picture agrees with intuition both that deleting the copies wouldn’t be murder, and that the reason why it wouldn’t be murder is directly related to the AI’s copyability.

Now of course, this picture also raises the possibility that, for reasons related to the AI’s copyability and predictability by outside observers, there’s “nothing that it’s like to be the AI,” and that therefore, even deleting the last copy of the AI still wouldn’t be murder.  But I confess that, personally, I think I’d play it safe and not delete that last copy.  Thank you.

Postscript: There’s no record of the hour-long discussion following my and Penrose’s talks, and the participants weren’t speaking for the record anyway.  But I can mention some general themes that came up in the discussion, to the extent I remember them.

The first third of the discussion wasn’t about anything specific to my or Penrose’s views, but just about the definition of consciousness.  Many participants expressed the opinion that it’s useless to speculate about the nature of consciousness if we lack even a clear definition of the term.  I pushed back against that view, holding instead that there are exist concepts (lines, time, equality, …) that are so basic that perhaps they can never be satisfactorily defined in terms of more basic concepts, but you can still refer to these concepts in sentences, and trust your listeners eventually to figure out more-or-less what you mean by applying their internal learning algorithms.

In the present case, I suggested a crude operational definition, along the lines of, “you consider a being to be conscious iff you regard destroying it as murder.”  Alas, the philosophers in the room immediately eviscerated that definition, so I came back with a revised one: if you tried to ban the word “consciousness,” I argued, then anyone who needed to discuss law or morality would soon reinvent a synonymous word, which played the same complicated role in moral deliberations that “consciousness” had played in them earlier.  Thus, my definition of consciousness is: whatever that X-factor is for which people need a word like “consciousness” in moral deliberations.  For whatever it’s worth, the philosophers seemed happier with that.

Next, a biologist and several others sharply challenged Penrose over what they considered the lack of experimental evidence for his and Hameroff’s microtubule theory.  In response, Penrose doubled or tripled down, talking about various experiments over the last decade, which he said demonstrated striking conductivity properties of microtubules, if not yet quantum coherence—let alone sensitivity to gravity-induced collapse of the state vector!  Audience members complained about a lack of replication of these experiments.  I didn’t know enough about the subject to express any opinion.

At some point, Philip Stamp, who was moderating the session, noticed that Penrose and I had never directly confronted each other about the validity of Penrose’s Gödelian argument, so he tried to get us to do so.  I confess that I was about as eager to do that as to switch to a diet of microtubule casserole, since I felt like this topic had already been beaten to Planck-sized pieces in the 1990s, and there was nothing more to be learned.  Plus, it was hard to decide which prospect I dreaded more: me “scoring a debate victory” over Roger Penrose, or him scoring a debate victory over me.

But it didn’t matter, because Penrose bit.  He said I’d misunderstood his argument, that it had nothing to do with “mystically seeing” the consistency of a formal system.  Rather, it was about the human capacity to pass from a formal system S to a stronger system S’ that one already implicitly accepted if one was using S at all—and indeed, that Turing himself had clearly understood this as the central message of Gödel, that our ability to pass to stronger and stronger formal systems was necessarily non-algorithmic.  I replied that it was odd to appeal here to Turing, who of course had considered and rejected the “Gödelian case against AI” in 1950, on the ground that AI programs could make mathematical mistakes yet still be at least as smart as humans.  Penrose said that he didn’t consider that one of Turing’s better arguments; he then turned to me and asked whether I actually found Turing’s reply satisfactory.  I could see that it wasn’t a rhetorical debate question; he genuinely wanted to know!  I said that yes, I agreed with Turing’s reply.

Someone mentioned that Penrose had offered a lengthy rebuttal to at least twenty counterarguments to the Gödelian anti-AI case in Shadows of the Mind.  I affirmed that I’d read his lengthy rebuttal, and I focused on one particular argument in Shadows: that while it’s admittedly conceivable that individual mathematicians might be mistaken, might believe (for example) that a formal system was consistent even though it wasn’t, the mathematical community as a whole converges toward truth in these matters, and it’s that convergence that cries out for a non-algorithmic explanation.  I replied that it wasn’t obvious to me that set theorists do converge toward truth in these matters, in anything other than the empirical, higgedly-piggedly, no-guarantees sense in which a community of AI robots might also converge toward truth.  Penrose said I had misunderstood the argument.  But alas, time was running out, and we never managed to get to the bottom of it.

There was one aspect of the discussion that took me by complete surprise.  I’d expected to be roasted alive over my attempt to relate consciousness and free will to unpredictability, the No-Cloning Theorem, irreversible decoherence, microscopic degrees of freedom left over from the Big Bang, and the cosmology of de Sitter space.  Sure, my ideas might be orders of magnitude less crazy than anything Penrose proposes, but they’re still pretty crazy!  But that entire section of my talk attracted only minimal interest.  With the Seven Pines crowd, what instead drew fire were the various offhand “pro-AI / pro-computationalism” comments I’d made—comments that, because I hang out with Singularity types so much, I had ceased to realize could even possibly be controversial.

So for example, one audience member argued that an AI could only do what its programmers had told it to do; it could never learn from experience.  I could’ve simply repeated Turing’s philosophical rebuttals to what he called “Lady Lovelace’s Objection,” which are as valid today as they were 66 years ago.  Instead, I decided to fast-forward, and explain a bit how IBM Watson and AlphaGo work, how they actually do learn from past experience without violating the determinism of the underlying transistors.  As I went through this, I kept expecting my interlocutor to interrupt me and say, “yes, yes, of course I understand all that, but my real objection is…”  Instead, I was delighted to find, the interlocutor seemed to light up with newfound understanding of something he hadn’t known or considered.

Similarly, a biologist asked how I could possibly have any confidence that the brain is simulable by a computer, given how little we know about neuroscience.  I replied that, for me, the relevant issues here are “well below neuroscience” in the reductionist hierarchy.  Do you agree, I asked, that the physical laws relevant to the brain are encompassed by the Standard Model of elementary particles, plus Newtonian gravity?  If so, then just as Archimedes declared: “give me a long enough lever and a place to stand, and I’ll move the earth,” so too I can declare, “give me a big enough computer and the relevant initial conditions, and I’ll simulate the brain atom-by-atom.”  The Church-Turing Thesis, I said, is so versatile that the only genuine escape from it is to propose entirely new laws of physics, exactly as Penrose does—and it’s to Penrose’s enormous credit that he understands that.

Afterwards, an audience member came up to me and said how much he liked my talk, but added, “a word of advice, from an older scientist: do not become the priest of a new religion of computation and AI.”  I replied that I’d take that to heart, but what was interesting was that, when I heard “priest of a new religion,” I’d expected that his warning would be the exact opposite of what it turned out to be.  To wit: “Do not become the priest of a new religion of unclonability, unpredictability, and irreversible decoherence.  Stick to computation—i.e., to conscious minds being copyable and predictable exactly like digital computer programs.”  I guess there’s no pleasing everyone!

Coincidental But Not-Wholly-Unrelated Announcement: My friend Robin Hanson has just released his long-awaited book The Age of Em: Work, Love, and Life When Robots Rule the Earth.  I read an early review copy of the book, and wrote the following blurb for the jacket:

Robin Hanson is a thinker like no other on this planet: someone so unconstrained by convention, so unflinching in spelling out the consequences of ideas, that even the most cosmopolitan reader is likely to find him as bracing (and head-clearing) as a mouthful of wasabi.  Now, in The Age of Em, he’s produced the quintessential Hansonian book, one unlike any other that’s ever been written.  Hanson is emphatic that he hasn’t optimized in any way for telling a good story, or for imparting moral lessons about the present: only for maximizing the probability that what he writes will be relevant to the actual future of our civilization.  Early in the book, Hanson estimates that probability as 10%.  His figure seems about right to me—and if you’re able to understand why that’s unbelievably high praise, then The Age of Em is for you.

Actually, my original blurb compared The Age of Em to Asimov’s Foundation series, with its loving attention to the sociology and politics of the remote future.  But that line got edited out, because the publisher (and Robin) wanted to make crystal-clear that The Age of Em is not science fiction, but just sober economic forecasting about a future dominated by copyable computer-emulated minds.

I would’ve attempted a real review of The Age of Em, but I no longer feel any need to, because Scott Alexander of SlateStarCodex has already hit this one out of the emulated park.

Second Coincidental But Not-Wholly-Unrelated Announcement: A reader named Nick Merrill recently came across this old quote of mine from Quantum Computing Since Democritus:

In a class I taught at Berkeley, I did an experiment where I wrote a simple little program that would let people type either “f” or “d” and would predict which key they were going to push next. It’s actually very easy to write a program that will make the right prediction about 70% of the time. Most people don’t really know how to type randomly. They’ll have too many alternations and so on. There will be all sorts of patterns, so you just have to build some sort of probabilistic model.

So Nick emailed me to ask whether I remembered how my program worked, and I explained it to him, and he implemented it as a web app, which he calls the “Aaronson Oracle.”

So give it a try!  Are you ready to test your free will, your Penrosian non-computational powers, your brain’s sensitivity to amplified quantum fluctuations, against the Aaronson Oracle?

Update: By popular request, Nick has improved his program so that it shows your previous key presses and its guesses for them.  He also fixed a “security flaw”: James Lee noticed that you could use the least significant digit of the program’s percentage correct so far, as a source of pseudorandom numbers that the program couldn’t predict!  So now the program only displays its percent correct rounded to the nearest integer.

Update (June 15): Penrose’s collaborator Stuart Hameroff has responded in the comments; see here (my reply here) and here.

### Me interviewed by John Horgan (the author of “The End of Science”)

Thursday, April 21st, 2016

It’s long (~12,000 words).  Rather than listing what this interview covers, it would be easier to list what it doesn’t cover.  (My favorite soda flavors?)

If you read this blog, much of what I say there will be old hat, but some of it will be new.  I predict that you’ll enjoy the interview iff you enjoy the blog.  Comments welcome.

### Grading Trudeau on quantum computing

Sunday, April 17th, 2016

Update (4/19): Inspired by Trudeau’s performance (which they clocked at 35 seconds), Maclean’s magazine asked seven quantum computing researchers—me, Krysta Svore, Aephraim Steinberg, Barry Sanders, Davide Venturelli, Martin Laforest, and Murray Thom—to also explain quantum computing in 35 seconds or fewer.  You can see all the results here (here’s the audio from my entry).

The emails starting hitting me like … a hail of maple syrup from the icy north.  Had I seen the news?  Justin Trudeau, the dreamy young Prime Minister of Canada, visited the Perimeter Institute for Theoretical Physics in Waterloo, one of my favorite old haunts.  At a news conference at PI, as Trudeau stood in front of a math-filled blackboard, a reporter said to him: “I was going to ask you to explain quantum computing, but — when do you expect Canada’s ISIL mission to begin again, and are we not doing anything in the interim?”

Rather than answering immediately about ISIL, Trudeau took the opportunity to explain quantum computing:

“Okay, very simply, normal computers work, uh, by [laughter, applause] … no no no, don’t interrupt me.  When you walk out of here, you will know more … no, some of you will know far less about quantum computing, but most of you … normal computers work, either there’s power going through a wire, or not.  It’s 1, or a 0, they’re binary systems.  Uh, what quantum states allow for is much more complex information to be encoded into a single bit.  Regular computer bit is either a 1 or a 0, on or off.  A quantum state can be much more complex than that, because as we know [speeding up dramatically] things can be both particle and wave at the same times and the uncertainty around quantum states [laughter] allows us to encode more information into a much smaller computer.  So, that’s what exciting about quantum computing and that’s… [huge applause] don’t get me going on this or we’ll be here all day, trust me.”

What marks does Trudeau get for this?  On the one hand, the widespread praise for this reply surely says more about how low the usual standards for politicians are, and about Trudeau’s fine comic delivery, than about anything intrinsic to what he said.  Trudeau doesn’t really assert much here: basically, he just says that normal computers work using 1’s and 0’s, and that quantum computers are more complicated than that in some hard-to-explain way.  He gestures toward the uncertainty principle and wave/particle duality, but he doesn’t say anything about the aspects of QM most directly relevant to quantum computing—superposition or interference or the exponential size of Hilbert space—nor does he mention what quantum computers would or wouldn’t be used for.

On the other hand, I’d grade Trudeau’s explanation as substantially more accurate than what you’d get from a typical popular article.  For pay close attention to what the Prime Minister never says: he never says that a qubit would be “both 0 and 1 at the same time,” or any equivalent formulation.  (He does say that quantum states would let us “encode more information into a much smaller computer,” but while Holevo’s Theorem says that’s false for a common interpretation of “information,” it’s true for other reasonable interpretations.)  The humorous speeding up as he mentions particle/wave duality and the uncertainty principle clearly suggests that he knows it’s more subtle than just “0 and 1 at the same time,” and he also knows that he doesn’t really get it and that the journalists in the audience don’t either.  When I’m grading exams, I always give generous partial credit for honest admissions of ignorance.  B+.

Anyway, I’d be curious to know who at PI prepped Trudeau for this, and what they said.  Those with inside info, feel free to share in the comments (anonymously if you want!).

(One could also compare against Obama’s 2008 answer about bubblesort, which was just a mention of a keyword by comparison.)

Update: See also a Motherboard article where Romain Alléaume, Amr Helmy, Michele Mosca, and Aephraim Steinberg rate Trudeau’s answer, giving it 7/10, no score, 9/10, and 7/10 respectively.

### Quantum. Crypto. Things happen. I blog.

Sunday, March 6th, 2016

1. A bunch of people emailed me to ask about the paper “Realization of a scalable Shor algorithm”: a joint effort by the groups of my MIT colleague Ike Chuang and of Innsbruck’s Rainer Blatt.  The paper has been on the arXiv since July, but last week everyone suddenly noticed it because it appeared in Science.  See also the articles in MIT News and IEEE Spectrum.

Briefly, the new work uses Kitaev’s version of Shor’s factoring algorithm, running on an ion-trap quantum computer with five calcium ions, to prove that, with at least 90% confidence, 15 equals 3×5.  Now, one might object that the “15=3×5 theorem” has by now been demonstrated many times using quantum computing (indeed, Chuang himself was involved in the historic first such demonstration, with Neil Gershenfeld in 1997).  Furthermore, if one counts demonstrations not based on quantum computing, some people have claimed even earlier precedents for that theorem.

Nevertheless, as far as I can tell, the new work is a genuine milestone in experimental QC, because it dispenses with most of the precompilation tricks that previous demonstrations of Shor’s algorithm used.  “Precompilation tricks” are a fancier term for “cheating”: i.e., optimizing a quantum circuit in ways that would only make sense if you already assumed that 15 was, indeed, 3×5.  So, what’s new is that a QC has now factored 15 “scalably”: that is, with much less cheating than before.

Of course, as I’m sure the authors would acknowledge, the word “scalable” in their title admits multiple interpretations, rather like the word “possible.”  (It’s possible to buy strawberry Mentos, and it’s also possible to convert the Sun into computronium, but for different senses of “possible.”)  As I wrote in the comments section of my last post:

There are still all the difficulties of integrating a huge number of qubits—which, in ion-trap implementations, would almost certainly mean having many traps that can communicate with each other using gate teleportation—as well as implementing quantum fault-tolerance (meaning: doing 2-qubit gates at the fault-tolerance threshold, moving qubits around to the right places, pumping in fresh qubits, pumping out dirty ones, etc).  Those all remain major engineering problems for the future.

See also this comment by Vaughan Pratt, who remarks: “the MIT press release … would appear to have translated [‘scalable’] to mean that RSA was now approaching its best-by date, although the paper itself makes no such claim.”

In any case, regardless of how long it takes until we can factor enormous numbers like 91, congratulations to the MIT and Innsbruck groups on what’s certainly progress toward scalable ion-trap QC!

2. Other people wrote to ask about a striking recent preprint of Kaplan, Leurent, Leverrier, and Naya-Plasencia, which points out how Simon’s algorithm—i.e., the forerunner of Shor’s algorithm—can be used to break all sorts of practical private-key authentication schemes in quantum polynomial time, assuming the adversary can query the scheme being attacked on a coherent superposition of inputs.  In practice, this assumption is unlikely to hold, unless the adversary gets the actual obfuscated code of the scheme being attacked (in which case it holds).  Also, this is not the first time Simon’s algorithm has been used to attack cryptography; previous work in the same spirit by Kuwakado and Morii showed how to use Simon’s algorithm to break the 3-round Feistel scheme and the Even-Mansour scheme, again if we assume superposition queries.

Even so, Kaplan et al. seem to pretty dramatically expand the range of “practical” cryptosystems that are known to be vulnerable to Simon attacks in the superposed-query model.  I suspect this will force a revision in how we talk about Simon’s algorithm: from “useless, but theoretically important, and historically important because it led to Shor’s algorithm” to “actually maybe not that useless.”  (See here for a previous attempt of mine to give an interesting “explicit” problem that Simon’s algorithm solves in polynomial time, but that’s classically hard.  Alas, my candidate problem turned out to be classically easy.)  This is analogous to the revision that “Einstein-certified randomness” and the RUV theorem recently forced in how we talk about Bell’s inequality: we can no longer tell students that Bell’s work was important because of the conceptual point it proved about local hidden variables, and because of all the other stuff it led to, even though it obviously has no applications in and of itself.  Now it does have applications in and of itself.

To a quantum complexity theorist like me, who doesn’t know nearly as much applied crypto as he should, the real news in the Kaplan et al. paper is not that Simon’s algorithm can break the sorts of systems they study.  Rather, it’s that so many systems that are vulnerable to Simon attack exist and are used in the first place!  Once people understand the problem, I doubt it will be hard to design schemes of similar efficiency that remain quantum-secure even in the superposed-query model (under some plausible assumption, like that an underlying one-way function is quantum-secure).  Indeed, recent work of Boneh and Zhandry, among others, has already taken significant steps in that direction.  So the situation doesn’t seem “as bad” as it was with public-key crypto, where once Shor’s algorithm comes along, the plausibly quantum-secure alternatives that we currently know (like lattice-based crypto and quantum key distribution) are either much less efficient than RSA and Diffie-Hellman, or else require new hardware.  Still, the new observations about Simon’s algorithm show us how the history of quantum computing could have unfolded differently: rather than Simon → Shor → everyone gets excited (because their crypto is now vulnerable), people could’ve gotten cryptographically excited immediately after Simon.

3. Speaking of Diffie-Hellman, belated congratulations to Whitfield Diffie and Martin Hellman for an extremely well-deserved Turing Award!

4. At MIT’s weekly quantum information group meeting, Aram Harrow spoke about his new paper with Ed Farhi, “Quantum Supremacy through the Quantum Approximate Optimization Algorithm.”  Using the same arguments developed around 2010 by me and Alex Arkhipov, and (independently) by Bremner, Jozsa, and Shepherd, this paper shows that, even though the recently-developed QAOA/Quinoa quantum optimization algorithm turns out not to beat the best classical algorithms on the Max E3LIN2 problem (see here and here)—still, whatever that algorithm does do, at least there’s no polynomial-time classical algorithm that samples from the same distribution over outputs, unless the polynomial hierarchy collapses.

In other words: even if the algorithm fails at its original goal, it’s still hard for a classical computer to reproduce its exact pattern of failure!  Hence: Quantum Supremacy.

A secondary goal of Aram and Eddie’s paper is to make the Aaronson-Arkhipov and Bremner et al. arguments more accessible to physicists, by decreasing the amount of “weird complexity theory” invoked.  (I suppose I’ve asked for this—for physicists to de-complexify complexity theory—by telling everyone for years how easy quantum mechanics becomes once you take away the physics!)  I’ll leave it to physicists to judge how well Aram and Eddie succeed at their pedagogical goal, but I’m thrilled by any such effort to communicate across fields.  Aram’s talk would surely have served that same educational purpose, had it not gotten derailed partway through by Donald Trump jokes from the audience.  (My contribution: “Aram, will you disavow support from quantum supremacists?”)

Unrelated Update: Some people might be interested in this brief interview with Michael Cerullo, who read The Ghost in the Quantum Turing Machine and wanted to ask me about “the relevance of quantum mechanics to brain preservation, uploading, and identity.”

### Edging in: the biggest science news of 2015

Sunday, January 3rd, 2016

For years, I was forced to endure life with my nose up against the glass of the Annual Edge Question.  What are you optimistic about?  Ooh! ooh! Call on me!  I’m optimistic about someday being able to prove my pessimistic beliefs (like P≠NP).  How is the Internet changing the way you think?  Ooh, ooh! I know! Google and MathOverflow are saving me from having to think at all!  So then why are they only asking Steven Pinker, Freeman Dyson, Richard Dawkins, David Deutsch, some random other people like that?

But all that has changed.  This year, I was invited to participate in Edge for the first time.  So, OK, here’s the question:

What do you consider the most interesting recent [scientific] news?  What makes it important?

My response is here.  I wasn’t in love with the question, because of what I saw as an inherent ambiguity in it: the news that’s most interesting to me, that I have a comparative advantage in talking about, and that people probably want to hear me talk about (e.g., progress in quantum computing), is not necessarily what I’d regard as the most important in any objective sense (e.g., climate change).  So, I decided to write my answer precisely about my internal tension in what I should consider most interesting: should it be the recent progress by John Martinis and others toward building a quantum computer?  Or should it be the melting glaciers, or something else that I’m confident will affect the future of the world?  Or possibly the mainstream attention now being paid to the AI-risk movement?  But if I really want to nerd out, then why not Babai’s graph isomorphism algorithm?  Or if I actually want to be honest about what excited me, then why not the superquadratic separations between classical and quantum query complexities for a total Boolean function, by Ambainis et al. and my student Shalev Ben-David?  On the other hand, how can I justify even caring about such things while the glaciers are melting?

So, yeah, my response tries to meditate on all those things.  My original title was “How nerdy do you want it?,” but John Brockman of Edge had me change it to something blander (“How widely should we draw the circle?”), and made a bunch of other changes from my usual style.  Initially I chafed at having an editor for what basically amounted to a blog post; on the other hand, I’m sure I would’ve gotten in trouble much less often on this blog had I had someone to filter my words for me.

Anyway, of course I wasn’t the only person to write about the climate crisis.  Robert Trivers, Laurence Smith, and Milford Wolpoff all wrote about it as well (Trivers most chillingly and concisely), while Max Tegmark wrote about the mainstreaming of AI risk.  John Naughton even wrote about Babai’s graph isomorphism breakthrough (though he seems unaware that the existing GI algorithms were already extremely fast in practice, and therefore makes misleading claims about the new algorithm’s practical applications).  Unsurprisingly, no one else wrote about breakthroughs in quantum query complexity: you’ll need to go to my essay for that!  A bit more surprisingly, no one besides me wrote about progress in quantum computing at all (if we don’t count the loophole-free Bell test).

Anyway, on reflection, 2015 actually was a pretty awesome year for science, no matter how nerdy you want it or how widely you draw the circle.  Here are other advances that I easily could’ve written about but didn’t:

I’ve now read all (more or less) of this year’s Edge responses.  Even though some of the respondents pushed personal hobbyhorses like I’d feared, I was impressed by how easy it was to discern themes: advances that kept cropping up in one answer after another and that one might therefore guess are actually important (or at least, are currently perceived to be important).

Probably at the top of the list was a new gene-editing technique called CRISPR: Randolph Neese, Paul Dolan, Eric Topol, Mark Pagel, and Stuart Firestein among others all wrote about this, and about its implications for creating designer humans.

Also widely-discussed was the discovery that most psychology studies fail to replicate (I’d long assumed as much, but apparently this was big news in psychology!): Nicholas Humphrey, Stephen Kosslyn, Jonathan Schooler, Ellen Winner, Judith Rich Harris, and Philip Tetlock all wrote about that.

Then there was the Pluto flyby, which Juan Enriquez, Roger Highfield, and Nicholas Christakis all wrote about.  (As Christakis, Master of Silliman College at Yale, was so recently a victim of a social-justice mob, I found it moving how he simply ignored those baying for his head and turned his attention heavenward in his Edge answer.)

Then there was progress in deep learning, including Google’s Deep Dream (those images of dogs in nebulae that filled your Facebook wall) and DeepMind (the program that taught itself how to play dozens of classic video games).  Steve Omohundro, Andy Clark, Jamshed Bharucha, Kevin Kelly, David Dalrymple, and Alexander Wissner-Gross all wrote about different aspects of this story.

And recent progress in SETI, which Yuri Milner (who’s given $100 million for it) and Mario Livio wrote about. Unsurprisingly, a bunch of high-energy physicists wrote about high-energy physics at the LHC: how the Higgs boson was found (still news?), how nothing other than the Higgs boson was found (the biggest news?), but how there’s now the slightest hint of a new particle at 750 GeV. See Lee Smolin, Garrett Lisi, Sean Carroll, and Sarah Demers. Finally, way out on the Pareto frontier of importance and disgustingness was the recently-discovered therapeutic value of transplanting one person’s poop into another person’s intestines, which Joichi Ito, Pamela Rosenkranz, and Alan Alda all wrote about (it also, predictably, featured in a recent South Park episode). Without further ado, here are 27 other answers that struck me in one way or another: • Steven Pinker on happy happy things are getting better (and we can measure it) • Freeman Dyson on the Dragonfly astronomical observatory • Jonathan Haidt on how prejudice against people of differing political opinions was discovered to have surpassed racial, gender, and religious prejudice • S. Abbas Raza on Piketty’s r>g • Rebecca Newberger Goldstein, thoughtful as usual, on the recent study that said it’s too simple to say female participation is lower in STEM fields—rather, female participation is lower in all and only those fields, STEM or non-STEM, whose participants believe (rightly or wrongly) that “genius” is required rather than just conscientious effort • Bill Joy on recent advances on reducing CO2 emissions • Paul Steinhardt on recent observations saying that, not only were the previous “B-modes from inflation” just galactic dust, but there are no real B-modes to within the current detection limits, and this poses a problem for inflation (I hadn’t heard about this last part) • Aubrey de Grey on new antibiotics that are grown in the soil rather than in lab cultures • John Tooby on the evolutionary rationale for germline engineering • W. Tecumseh Fitch on the coming reality of the “Jurassic Park program” (bringing back extinct species through DNA splicing—though probably not dinosaurs, whose DNA is too degraded) • Keith Devlin on the new prospect of using massive datasets (from MOOCs, for example) to actually figure out how students learn • Richard Muller on how air pollution in China has become one of the world’s worst problems (imagine every child in Beijing being force-fed two packs of cigarettes per day) • Ara Norenzayan on the demographic trends in religious belief • James Croak on amazing advances in battery technology (which were news to me) • Buddhini Samarasinghe on (among other things) the power of aspirin to possibly prevent cancer • Todd Sacktor on a new treatment for Parkinson’s • Charles Seife on the imminent availability of data about pretty much everything in our lives • Susan Blackmore on “that dress” and what it revealed about the human visual system • Brian Keating on experiments that should soon tell us the neutrinos’ masses (again, I hadn’t heard about these) • Michael McCullough on something called “reproductive religiosity theory,” which posits that the central purpose of religions is to enforce social norms around mating and reproduction (for what it’s worth, I’d always regarded that as obvious; it’s even expounded in the last chapter of Quantum Computing Since Democritus) • Greg Cochran on the origin of Europeans • David Buss on the “mating crisis among educated women” • Ed Regis on how high-fat diets are better (except, isn’t this the principle behind Atkins, and isn’t this pretty old news by now?) • Melanie Swan on blockchain-based cryptography, such as Bitcoin (though it wasn’t entirely clear to me what point Swan was making about it) • Paul Davies on LIGO getting ready to detect its first gravitational waves • Samuel Arbesman on how weather prediction has gotten steadily better (rendering our culture’s jokes about the perpetually-wrong weatherman outdated, with hardly anyone noticing) • Alison Gopnik on how the ubiquity of touchscreen devices like the iPad means that toddlers can now master computers, and this is something genuinely new under the sun (I can testify from personal experience that she’s onto something) Then there were three answers for which the “progress” being celebrated, seemed to me to be progress racing faster into WrongVille: • Frank Tipler on how one can conclude a priori that there must be a Big Crunch to our future (and hence, the arena for Tiplerian theology) in order to prevent the black hole information paradox from arising, all recent cosmological evidence to the contrary be damned. • Ross Anderson on an exciting conference whose participants aim to replace quantum mechanics with local realistic theories. (Anderson, in particular, is totally wrong that you can get Bell inequality violation from “a combination of local action and global correlation,” unless the global correlation goes as far as a ‘t-Hooft-like superdeterministic conspiracy.) • Gordon Kane on how the big news is that the LHC should soon see superparticles. (This would actually be fine except that Kane omits the crucial context, that he’s been predicting superparticles just around the corner again and again for the past twenty years and they’ve never shown up) Finally, two responses by old friends that amused me. The science-fiction writer Rudy Rucker just became aware of the discovery of the dark energy back in 1998, and considers that to be exciting scientific news (yes, Rudy, so it was!). And Michael Vassar —the Kevin Bacon or Paul Erdös of the rationalist world, the guy who everyone‘s connected to somehow—writes something about a global breakdown of economic rationality,$20 bills on the sidewalk getting ignored, that I had trouble understanding (though the fault is probably mine).

### 6.S899 Student Project Showcase!

Tuesday, December 22nd, 2015

As 2015 winds down, I thought I’d continue my tradition of using this blog to showcase some awesome student projects from my graduate class.  (For the previous project showcases from Quantum Complexity Theory, see here, here, and here.  Also see here for the showcase from Philosophy and Theoretical Computer Science.)

This fall, I taught 6.S899, a one-time “Seminar on Physics and Computation” that focused on BosonSampling, complexity and quantum gravity, and universality of physical systems.  There were also lots of guest lectures and student presentations.  Unfortunately, we didn’t do any notes or recordings.

Fortunately, though, the students did do projects, which were literature reviews some of which ventured into original research, and all nine have agreed to share their project reports here!  So enjoy, thanks so much to the students for making it a great class, and happy holidays.

Update (Dec. 23): Here are two conference announcements that I’ve been asked to make: Innovations in Theoretical Computer Science (ITCS) 2016, January 14-16 in Cambridge MA, and the Fifth Women in Theory Workshop, at the Simons Institute in Berkeley, May 22-25, 2016.

### Google, D-Wave, and the case of the factor-10^8 speedup for WHAT?

Wednesday, December 9th, 2015

Update (Dec. 16):  If you’re still following this, please check out an important comment by Alex Selby, the discoverer of Selby’s algorithm, which I discussed in the post.  Selby queries a few points in the Google paper: among other things, he disagrees with their explanation of why his classical algorithm works so well on D-Wave’s Chimera graph (and with their prediction that it should stop working for larger graphs), and he explains that Karmarkar-Karp is not the best known classical algorithm for the Number Partitioning problem.  He also questions whether simulated annealing is the benchmark against which everything should be compared (on the grounds that “everything else requires fine-tuning”), pointing out that SA itself typically requires lots of tuning to get it to work well.

Update (Dec. 11): MIT News now has a Q&A with me about the new Google paper. I’m really happy with how the Q&A turned out; people who had trouble understanding this blog post might find the Q&A easier. Thanks very much to Larry Hardesty for arranging it.

Meanwhile, I feel good that there seems to have been actual progress in the D-Wave debate! In previous rounds, I had disagreed vehemently with some of my MIT colleagues (like Ed Farhi and Peter Shor) about the best way to respond to D-Wave’s announcements. Today, though, at our weekly group meeting, there was almost no daylight between any of us. Partly, I’m sure, it’s that I’ve learned to express myself better; partly it’s that the “trigger” this time was a serious research paper by a group separate from D-Wave, rather than some trash-talking statement from Geordie Rose. But mostly it’s that, thanks to the Google group’s careful investigations, this time pretty much anyone who knows anything agrees about all the basic facts, as I laid them out in this blog post and in the Q&A. All that remains are some small differences in emotional attitude: e.g., how much of your time do you want to spend on a speculative, “dirty” approach to quantum computing (which is far ahead of everyone else in terms of engineering and systems integration, but which still shows no signs of an asymptotic speedup over the best classical algorithms, which is pretty unsurprising given theoretical expectations), at a time when the “clean” approaches might finally be closing in on the long-sought asymptotic quantum speedup?

Another Update: Daniel Lidar was nice enough to email me an important observation, and to give me permission to share it here.  Namely, the D-Wave 2X has a minimum annealing time of 20 microseconds.  Because of this, the observed running times for small instance sizes are artificially forced upward, making the growth rate in the machine’s running time look milder than it really is.  (Regular readers might remember that exactly the same issue plagued previous D-Wave vs. classical performance comparisons.)  Correcting this would certainly decrease the D-Wave 2X’s predicted speedup over simulated annealing, in extrapolations to larger numbers of qubits than have been tested so far (although Daniel doesn’t know by how much).  Daniel stresses that he’s not criticizing the Google paper, which explicitly mentions the minimum annealing time—just calling attention to something that deserves emphasis.

In retrospect, I should’ve been suspicious, when more than a year went by with no major D-Wave announcements that everyone wanted me to react to immediately. Could it really be that this debate was over—or not “over,” but where it always should’ve been, in the hands of experts who might disagree vehemently but are always careful to qualify speedup claims—thereby freeing up the erstwhile Chief D-Wave Skeptic for more “””rewarding””” projects, like charting a middle path through the Internet’s endless social justice wars?

Nope.

As many of you will have seen by now, on Monday a team at Google put out a major paper reporting new experiments on the D-Wave 2X machine.  (See also Hartmut Neven’s blog post about this.)  The predictable popularized version of the results—see for example here and here—is that the D-Wave 2X has now demonstrated a factor-of-100-million speedup over standard classical chips, thereby conclusively putting to rest the question of whether the device is “truly a quantum computer.”  In the comment sections of one my previous posts, D-Wave investor Steve Jurvetson even tried to erect a victory stele, by quoting Karl Popper about falsification.

In situations like this, the first thing I do is turn to Matthias Troyer, who’s arguably the planet’s most balanced, knowledgeable, trustworthy interpreter of quantum annealing experiments. Happily, in collaboration with Ilia Zintchenko and Ethan Brown, Matthias was generous enough to write a clear 3-page document putting the new results into context, and to give me permission to share it on this blog. From a purely scientific standpoint, my post could end right here, with a link to their document.

Then again, from a purely scientific standpoint, the post could’ve ended even earlier, with the link to the Google paper itself!  For this is not a case where the paper hides some crucial issue that the skeptics then need to ferret out.  On the contrary, the paper’s authors include some of the most careful people in the business, and the paper explains the caveats as clearly as one could ask.  In some sense, then, all that’s left for me or Matthias to do is to tell you what you’d learn if you read the paper!

So, OK, has the D-Wave 2X demonstrated a factor-108 speedup or not?  Here’s the shortest answer that I think is non-misleading:

Yes, there’s a factor-108 speedup that looks clearly asymptotic in nature, and there’s also a factor-108 speedup over Quantum Monte Carlo. But the asymptotic speedup is only if you compare against simulated annealing, while the speedup over Quantum Monte Carlo is only constant-factor, not asymptotic. And in any case, both speedups disappear if you compare against other classical algorithms, like that of Alex Selby. Also, the constant-factor speedup probably has less to do with quantum mechanics than with the fact that D-Wave built extremely specialized hardware, which was then compared against a classical chip on the problem of simulating the specialized hardware itself (i.e., on Ising spin minimization instances with the topology of D-Wave’s Chimera graph). Thus, while there’s been genuine, interesting progress, it remains uncertain whether D-Wave’s approach will lead to speedups over the best known classical algorithms, let alone to speedups over the best known classical algorithms that are also asymptotic or also of practical importance. Indeed, all of these points also remain uncertain for quantum annealing as a whole.

To expand a bit, there are really three separate results in the Google paper:

1. The authors create Chimera instances with tall, thin energy barriers blocking the way to the global minimum, by exploiting the 8-qubit “clusters” that play such a central role in the Chimera graph.  In line with a 2002 theoretical prediction by Farhi, Goldstone, and Gutmann (a prediction we’ve often discussed on this blog), they then find that on these special instances, quantum annealing reaches the global minimum exponentially faster than classical simulated annealing, and that the D-Wave machine realizes this advantage.  As far as I’m concerned, this completely nails down the case for computationally-relevant collective quantum tunneling in the D-Wave machine, at least within the 8-qubit clusters.  On the other hand, the authors point out that there are other classical algorithms, like that of Selby (building on Hamze and de Freitas), which group together the 8-bit clusters into 256-valued mega-variables, and thereby get rid of the energy barrier that kills simulated annealing.  These classical algorithms are found empirically to outperform the D-Wave machine.  The authors also match the D-Wave machine’s asymptotic performance (though not the leading constant) using Quantum Monte Carlo, which (despite its name) is a classical algorithm often used to find quantum-mechanical ground states.
2. The authors make a case that the ability to tunnel past tall, thin energy barriers—i.e., the central advantage that quantum annealing has been shown to have over classical annealing—might be relevant to at least some real-world optimization problems.  They do this by studying a classic NP-hard problem called Number Partitioning, where you’re given a list of N positive integers, and your goal is to partition the integers into two subsets whose sums differ from each other by as little as possible.  Through numerical studies on classical computers, they find that quantum annealing (in the ideal case) and Quantum Monte Carlo should both outperform simulated annealing, by roughly equal amounts, on random instances of Number Partitioning.  Note that this part of the paper doesn’t involve any experiments on the D-Wave machine itself, so we don’t know whether calibration errors, encoding loss, etc. will kill the theoretical advantage over simulated annealing.  But even if not, this still wouldn’t yield a “true quantum speedup,” since (again) Quantum Monte Carlo is a perfectly-good classical algorithm, whose asymptotics match those of quantum annealing on these instances.
3. Finally, on the special Chimera instances with the tall, thin energy barriers, the authors find that the D-Wave 2X reaches the global optimum about 108 times faster than Quantum Monte Carlo running on a single-core classical computer.  But, extremely interestingly, they also find that this speedup does not grow with problem size; instead it simply saturates at ~108.  In other words, this is a constant-factor speedup rather than an asymptotic one.  Now, obviously, solving a problem “only” 100 million times faster (rather than asymptotically faster) can still have practical value!  But it’s crucial to remember that this constant-factor speedup is only observed for the Chimera instances—or in essence, for “the problem of simulating the D-Wave machine itself”!  If you wanted to solve something of practical importance, you’d first need to embed it into the Chimera graph, and it remains unclear whether any of the constant-factor speedup would survive that embedding.  In any case, while the paper isn’t explicit about this, I gather that the constant-factor speedup disappears when one compares against (e.g.) the Selby algorithm, rather than against QMC.

So then, what do I say to Steve Jurvetson?  I say—happily, not grudgingly!—that the new Google paper provides the clearest demonstration so far of a D-Wave device’s capabilities.  But then I remind him of all the worries the QC researchers had from the beginning about D-Wave’s whole approach: the absence of error-correction; the restriction to finite-temperature quantum annealing (moreover, using “stoquastic Hamiltonians”), for which we lack clear evidence for a quantum speedup; the rush for more qubits rather than better qubits.  And I say: not only do all these worries remain in force, they’ve been thrown into sharper relief than ever, now that many of the side issues have been dealt with.  The D-Wave 2X is a remarkable piece of engineering.  If it’s still not showing an asymptotic speedup over the best known classical algorithms—as the new Google paper clearly explains that it isn’t—then the reasons are not boring or trivial ones.  Rather, they seem related to fundamental design choices that D-Wave made over a decade ago.

The obvious question now is: can D-Wave improve its design, in order to get a speedup that’s asymptotic, and that holds against all classical algorithms (including QMC and Selby’s algorithm), and that survives the encoding of a “real-world” problem into the Chimera graph?  Well, maybe or maybe not.  The Google paper returns again and again to the subject of planned future improvements to the machine, and how they might clear the path to a “true” quantum speedup. Roughly speaking, if we rule out radical alterations to D-Wave’s approach, there are four main things one would want to try, to see if they helped:

1. Lower temperatures (and thus, longer qubit lifetimes, and smaller spectral gaps that can be safely gotten across without jumping up to an excited state).
2. Better calibration of the qubits and couplings (and thus, ability to encode a problem of interest, like the Number Partitioning problem mentioned earlier, to greater precision).
3. The ability to apply “non-stoquastic” Hamiltonians.  (D-Wave’s existing machines are all limited to stoquastic Hamiltonians, defined as Hamiltonians all of whose off-diagonal entries are real and non-positive.  While stoquastic Hamiltonians are easier from an engineering standpoint, they’re also the easiest kind to simulate classically, using algorithms like QMC—so much so that there’s no consensus on whether it’s even theoretically possible to get a true quantum speedup using stoquastic quantum annealing.  This is a subject of active research.)
4. Better connectivity among the qubits (thereby reducing the huge loss that comes from taking problems of practical interest, and encoding them in the Chimera graph).

(Note that “more qubits” is not on this list: if a “true quantum speedup” is possible at all with D-Wave’s approach, then the 1000+ qubits that they already have seem like more than enough to notice it.)

Anyway, these are all, of course, things D-Wave knows about and will be working on in the near future. As well they should! But to repeat: even if D-Wave makes all four of these improvements, we still have no idea whether they’ll see a true, asymptotic, Selby-resistant, encoding-resistant quantum speedup. We just can’t say for sure that they won’t see one.

In the meantime, while it’s sometimes easy to forget during blog-discussions, the field of experimental quantum computing is a proper superset of D-Wave, and things have gotten tremendously more exciting on many fronts within the last year or two.  In particular, the group of John Martinis at Google (Martinis is one of the coauthors of the Google paper) now has superconducting qubits with orders of magnitude better coherence times than D-Wave’s qubits, and has demonstrated rudimentary quantum error-correction on 9 of them.  They’re now talking about scaling up to ~40 super-high-quality qubits with controllable couplings—not in the remote future, but in, like, the next few years.  If and when they achieve that, I’m extremely optimistic that they’ll be able to show a clear quantum advantage for something (e.g., some BosonSampling-like sampling task), if not necessarily something of practical importance.  IBM Yorktown Heights, which I visited last week, is also working (with IARPA funding) on integrating superconducting qubits with many-microsecond coherence times.  Meanwhile, some of the top ion-trap groups, like Chris Monroe’s at the University of Maryland, are talking similarly big about what they expect to be able to do soon. The “academic approach” to QC—which one could summarize as “understand the qubits, control them, keep them alive, and only then try to scale them up”—is finally bearing some juicy fruit.

(At last week’s IBM conference, there was plenty of D-Wave discussion; how could there not be? But the physicists in attendance—I was almost the only computer scientist there—seemed much more interested in approaches that aim for longer-laster qubits, fault-tolerance, and a clear asymptotic speedup.)

I still have no idea when and if we’ll have a practical, universal, fault-tolerant QC, capable of factoring 10,000-digit numbers and so on.  But it’s now looking like only a matter of years until Gil Kalai, and the other quantum computing skeptics, will be forced to admit they were wrong—which was always the main application I cared about anyway!

So yeah, it’s a heady time for QC, with many things coming together faster than I’d expected (then again, it was always my personal rule to err on the side of caution, and thereby avoid contributing to runaway spirals of hype).  As we stagger ahead into this new world of computing—bravely, coherently, hopefully non-stoquastically, possibly fault-tolerantly—my goal on this blog will remain what it’s been for a decade: not to prognosticate, not to pick winners, but merely to try to understand and explain what has and hasn’t already been shown.

Update (Dec. 10): Some readers might be interested in an economic analysis of the D-Wave speedup by commenter Carl Shulman.

Another Update: Since apparently some people didn’t understand this post, here are some comments from a Y-Combinator thread about the post that might be helpful:

(1) [T]he conclusion of the Google paper is that we have probable evidence that with enough qubits and a big enough problem it will be faster for a very specific problem compared to a non-optimal classical algorithm (we have ones that are for sure better).

This probably sounds like a somewhat useless result (quantum computer beats B-team classical algorithm), but it is in fact interesting because D-Wave’s computers are designed to perform quantum annealing and they are comparing it to simulated annealing (the somewhat analogous classical algorithm). However they only found evidence of a constant (i.e. one that 4000 qubits wouldn’t help with) speed up (though a large one) compared to a somewhat better algorithm (Quantum Monte Carlo, which is ironically not a quantum algorithm), and they still can’t beat an even better classical algorithm (Selby’s) at all, even in a way that won’t scale.

Scott’s central thesis is that although it is possible there could be a turning point past 2000 qubits where the D-Wave will beat our best classical alternative, none of the data collected so far suggests that. So it’s possible that a 4000 qubit D-Wave machine will exhibit this trend, but there is no evidence of it (yet) from examining a 2000 qubit machine. Scott’s central gripe with D-Wave’s approach is that they don’t have any even pie-in-the-sky theoretical reason to expect this to happen, and scaling up quantum computers without breaking the entire process is much harder than for classical computers so making them even bigger doesn’t seem like a solution.

(2) DWave machines are NOT gate quantum computers; they call their machine quantum annealing machines. It is not known the complexity class of problems that can be solved efficiently by quantum annealing machines, or if that class is equivalent to classical machines.

The result shows that the DWave machine is asymptotically faster than the Simulated Annealing algorithm (yay!), which suggests that it is executing the Quantum Annealing algorithm. However, the paper also explicitly states that this does not mean that the Dwave machine is exhibiting a ‘quantum speedup’. To do this, they would need to show it to outperform the best known classical algorithm, which as the paper acknowledges, it does not.

What the paper does seem to be showing is that the machine in question is actually fundamentally quantum in nature; it’s just not clear yet that that the type of quantum computer it is is an improvement over classical ones.

(3) [I]t isn’t called out in the linked blog since by now Scott probably considers it basic background information, but D-Wave only solves a very particular problem, and it is both not entirely clear that it has a superior solution to that problem than a classical algorithm can obtain and it is not clear that encoding real problems into that problem will not end up costing you all of the gains itself. Really pragmatic applications are still a ways into the future. It’s hard to imagine what they might be when we’re still so early in the process, and still have no good idea what either the practical or theoretical limits are.

(4) The popular perception of quantum computers as “doing things in parallel” is very misleading. A quantum computer lets you perform computation on a superposed state while maintaining that superposition. But that only helps if the structure of the problem lets you somehow “cancel out” the incorrect results leaving you with the single correct one. [There’s hope for the world! –SA]