## Archive for the ‘Quantum’ Category

### Turn down the quantum volume

Thursday, March 5th, 2020

Several people asked me to comment on the recent announcement by Honeywell that they’ll soon have what they call “the most powerful” quantum computer (see here for press release, here for Forbes article, here for paper).

I’m glad that Honeywell, which many people might know as an air-conditioner manufacturer, has entered the race for trapped-ion QC. I wish them success. I’ve known about what they were doing in part because Drew Potter, my friend and colleague in UT Austin’s physics department, took a one-year leave from UT to contribute to their effort.

Here I wanted to comment about one detail in Honeywell’s announcement: namely, the huge emphasis on “quantum volume” as the central metric for judging quantum computing progress, and the basis for calling their own planned device the “most powerful.” One journalist asked me to explain why quantum volume is such an important measure. I had to give her an honest answer: I don’t know whether it is.

Quantum volume was invented a few years ago by a group at IBM. According to one of their papers, it can be defined roughly as 2k, where k is the largest number such that you can run a k-qubit random quantum circuit, with depth k and with any-to-any connectivity, and have at least (say) 2/3 probability of measuring an answer that passes some statistical test. (In the paper, they use what Lijie Chen and I named Heavy Output Generation, though Google’s Linear Cross-Entropy Benchmark is similar.)

I don’t know why IBM takes the “volume” to be 2k rather than k itself. Leaving that aside, though, the idea was to invent a single “goodness measure” for quantum computers that can’t be gamed either by building a huge number of qubits that don’t maintain nearly enough coherence (what one might call “the D-Wave approach”), or by building just one perfect qubit, or by building qubits that behave well in isolation but don’t interact easily. Note that the any-to-any connectivity requirement makes things harder for architectures with nearest-neighbor interactions only, like the 2D superconducting chips being built by Google, Rigetti, or IBM itself.

You know the notion of a researcher’s h-index—defined as the largest h such that she’s published h papers that garnered h citations each? Quantum volume is basically an h-index for quantum computers. It’s an attempt to take several different yardsticks of experimental progress, none terribly useful in isolation, and combine them into one “consumer index.”

Certainly I sympathize with the goal of broadening people’s focus beyond the “but how many qubits does it have?” question—since the answer to that question is meaningless without further information about what the qubits can do. From that standpoint, quantum volume seems like a clear step in the right direction.

Alas, Goodhart’s Law states that “as soon as a measure becomes a target, it ceases to be a good measure.” That happened years ago with the h-index, which now regularly pollutes academic hiring and promotion decisions, to the point where its inventor expressed regrets. Quantum volume is now looking to me like another example of Goodhart’s Law at work.

The position of Honeywell’s PR seems to be that, if they can build a device that can apply 6 layers of gates to 6 qubits, with full connectivity and good fidelity, that will then count as “the world’s most powerful quantum computer,” since it will have the largest volume. One problem here is that such a device could be simulated by maintaining a vector of only 26=64 amplitudes. This is nowhere near quantum supremacy (i.e., beating classical computers at some well-defined task), which is a necessary though not sufficient condition for doing anything useful.

Think of a university that achieves an average faculty-to-student ratio of infinity by holding one class with zero students. It gets the “best score” only by exploiting an obvious defect in the scoring system.

So what’s the alternative? The policy I prefer is simply to tell the world all your system specs, as clearly as you can, with no attempts made to bury the lede. How many qubits do you have? With what coherence times? With what connectivity? What are the 1- and 2-qubit gate fidelities? What depth of circuit can you do? What resources do the standard classical algorithms need to simulate your system? Most importantly: what’s the main drawback of your system, the spec that’s the worst, the one you most need to improve? What prevents you from having a scalable quantum computer right now? And are you going to tell me, or will you make me scour Appendix III.B in your paper, or worse yet, ask one of your competitors?

I confess that the answers to the above questions are hard to summarize in a single number (unless you, like, concatenated binary encodings of them or something). But they can be ineffably combined, to produce a progress metric that one of my postdocs suggested calling “quantum scottness,” and which roughly equals the number of expressions of wide-eyed surprise minus the number of groans.

### Paperz

Tuesday, March 3rd, 2020

Soon, all anyone will want to talk about is quarantines, food shortages, N95 masks, the suspension of universities and of scientific conferences. (As many others have pointed out, this last might actually be a boon to scientific productivity—as it was for a young Isaac Newton when Cambridge was closed for the bubonic plague, so Newton went home and invented calculus and mechanics.)

Anyway, before that all happens, I figured I’d get in a last post about quantum information and complexity theory progress.

Hsin-Yuan Huang, Richard Kueng, and John Preskill have a nice preprint entitled Predicting Many Properties of a Quantum System from Very Few Measurements. In it they take shadow tomography, which I proposed a couple years ago, and try to bring it closer to practicality on near-term devices, by restricting to the special case of non-adaptive, one-shot measurements, on separate copies of the state ρ that you’re trying to learn about. They show that this is possible using a number of copies that depends logarithmically on the number of properties you’re trying to learn (the optimal dependence), not at all on the Hilbert space dimension, and linearly on a new “shadow norm” quantity that they introduce.

Rahul Ilango, Bruno Loff, and Igor Oliveira announced the pretty spectacular-sounding result that the Minimum Circuit Size Problem (MCSP) is NP-complete for multi-output functions—that is, for Boolean functions f with not only many input bits but many outputs. Given the 2n-sized truth table of a Boolean function f:{0,1}n→{0,1}, the original MCSP simply asks for the size of the smallest Boolean circuit that computes f. This problem was studied in the USSR as early as the 1950s; whether it’s NP-complete has stood for decades as one of the big open problems of complexity theory. We’ve known that if you could quickly solve MCSP then you could also invert any one-way function, but we’ve also known technical barriers to going beyond that to a flat-out NP-hardness result, at least via known routes. Before seeing this paper, I’d never thought about whether MCSP for many-output functions might somehow be easier to classify, but apparently it is!

Hamoon Mousavi, Seyed Nezhadi, and Henry Yuen have now taken the MIP*=RE breakthrough even a tiny step further, by showing that “zero-gap MIP*” (that is, quantum multi-prover interactive proofs with an arbitrarily small gap between the completeness and soundness probabilities) takes you even beyond the halting problem (i.e., beyond Recursively Enumerable or RE), and up to the second level of the arithmetical hierarchy (i.e., to the halting problem for Turing machines with oracles for the original halting problem). This answers a question that someone asked in the comments section of this blog.

Several people asked me for comment on the paper What limits the simulation of quantum computers?, by Yiqing Zhou, Miles Stoudenmire, and Xavier Waintal. In particular, does this paper refute or weaken Google’s quantum supremacy claim, as the paper does not claim to do (but, rather coyly, also does not claim not to do)? Short answer: No, it doesn’t, or not now anyway.

Longer, more technical answer: The quoted simulation times, just a few minutes for quantum circuits with 54 qubits and depth 20, assume Controlled-Z gates rather than iSWAP-like gates. Using tensor network methods, the classical simulation cost with the former is roughly the square root of the simulation cost with the latter (~2k versus ~4k for some parameter k related to the depth). As it happens, Google switched its hardware from Controlled-Z to iSWAP-like gates a couple years ago precisely because they realized this—I had a conversation about it with Sergio Boixo at the time. Once this issue is accounted for, the quoted simulation times in the new paper seem to be roughly in line with what was previously reported by, e.g., Johnnie Gray and Google itself.

Oh yeah, I enjoyed Quantum Homeopathy Works. Cool result, and the title is actually a pretty accurate description of the contents.

To end with a community announcement: as many of you might know, the American Physical Society’s March Meeting, which was planned for this week in Denver, was abruptly cancelled due to the coronavirus (leaving thousands of physicists out their flights and hotel rooms—many had even already arrived there). However, my colleague Michael Biercuk kindly alerted me to a “virtual March Meeting” that’s been set up online, with recorded talks and live webinars. Even after the pandemic passes, is this a model that we should increasingly move to? I wouldn’t have thought so ten or fifteen years ago, but today every schlep across the continent brings me a step closer to shouting “yes”…

### Freeman Dyson and Boris Tsirelson

Saturday, February 29th, 2020

Today, as the world braces for the possibility of losing millions of lives to the new coronavirus—to the hunger for pangolin meat, of all things (combined with the evisceration of competent public health agencies like the CDC)—we also mourn the loss of two incredibly special lives, those of Freeman Dyson (age 96) and Boris Tsirelson (age 69).

Freeman Dyson was sufficiently legendary, both within and beyond the worlds of math and physics, that there’s very little I can add to what’s been said. It seemed like he was immortal, although I’d heard from mutual friends that his health was failing over the past year. When I spent a year as a postdoc at the Institute for Advanced Study, in 2004-5, I often sat across from Dyson in the common room, while he drank tea and read the news. That I never once struck up a conversation with him is a regret that I’ll now carry with me forever.

My only exchange with Dyson came when he gave a lecture at UC Berkeley, about how life might persist infinitely far into the future, even after the last stars had burnt out, by feeding off steadily dimishing negentropy flows in the nearly-thermal radiation. During the Q&A, I challenged Dyson that his proposal seemed to assume an analog model of computation. But, I asked, once we took on board the quantum-gravity insights of Jacob Bekenstein and others, suggesting that nature behaves like a (quantum) digital computer at the Planck scale, with at most ~1043 operations per second and ~1069 qubits per square meter and so forth, wasn’t this sort of proposal ruled out? “I’m not going to argue with you,” was Dyson’s response. Yes, he’d assumed an analog computational model; if computation was digital then that surely changed the picture.

Sometimes—and not just with his climate skepticism, but also (e.g.) with his idea that general relativity and quantum mechanics didn’t need to be reconciled, that it was totally fine for the deepest layer of reality to be a patchwork of inconsistent theories—Dyson’s views struck me as not merely contrarian but as a high-level form of trolling. Even so, Dyson’s book Disturbing the Universe had had a major impact on me as a teenager, for the sparkling prose as much as for the ideas.

With Dyson’s passing, the scientific world has lost one of its last direct links to a heroic era, of Einstein and Oppenheimer and von Neumann and a young Richard Feynman, when theoretical physics stood at the helm of civilization like never before or since. Dyson, who apparently remained not only lucid but mathematically powerful (!) well into his last year, clearly remembered when the Golden Age of science fiction looked like simply sober forecasting; when the smartest young people, rather than denouncing each other on Twitter, dreamed of scouting the solar system in thermonuclear-explosion-powered spacecraft and seriously worked to make that happen.

Boris Tsirelson (homepage, Wikipedia), who emigrated from the Soviet Union and then worked at Tel Aviv University (where my wife Dana attended his math lectures), wasn’t nearly as well known as Dyson to the wider world, but was equally beloved within the quantum computing and information community. Tsirelson’s bound, which he proved in the 1980s, showed that even quantum mechanics could only violate the Bell inequality by so much and by no more, could only let Alice and Bob win the CHSH game with probability cos2(π/8). This seminal result anticipated many of the questions that would only be asked decades later with the rise of quantum information. Tsirelson’s investigations of quantum nonlocality also led him to pose the famous Tsirelson’s problem: loosely speaking, can all sets of quantum correlations that can arise from an infinite amount of entanglement, be arbitrarily well approximated using finite amounts of entanglement? The spectacular answer—no—was only announced one month ago, as a corollary of the MIP*=RE breakthrough, something that Tsirelson happily lived to see although I don’t know what his reaction was (update: I’m told that he indeed learned of it in his final weeks, and was happy about it). Sadly, for some reason, I never met Tsirelson in person, although I did have lively email exchanges with him 10-15 years ago about his problem and other topics. This amusing interview with Tsirelson gives some sense for his personality (hat tip to Gil Kalai, who knew Tsirelson well).

Please share any memories of Dyson or Tsirelson in the comments section.

### My video interview with Lex Fridman at MIT about philosophy and quantum computing

Monday, February 17th, 2020

Here it is (about 90 minutes; I recommend the 1.5x speed)

I had buried this as an addendum to my previous post on the quantum supremacy lecture tour, but then decided that a steely-eyed assessment of what’s likely to have more or less interest for this blog’s readers probably militated in favor of a separate post.

Thanks so much to Lex for arranging the interview and for his questions!

### My “Quantum Supremacy: Skeptics Were Wrong” 2020 World Speaking Tour

Monday, February 17th, 2020

(At a few people’s request, I’ve changed the title so that it no longer refers to a specific person. I try always to be accurate, amusing, and appropriate, but sometimes I only hit 1 or 2 of the 3.)

As part of my speaking tour, in the last month I’ve already given talks at the following fine places:

World Economic Forum at Davos
University of Waterloo
Perimeter Institute
UC Berkeley
Harvard
MIT
Princeton
University of Houston

And I’ll be giving talks at the following places over the next couple of months:

Louisiana State University
Pittsburgh Quantum Institute
Fermilab
Yale

For anyone who’s interested, I’ll add links and dates to this post later (if you want that to happen any faster, feel free to hunt them down for me!).

In the meantime, there are also interviews! See, for example, this 5-minute one on Texas Standard (an NPR affiliate), where I’m asked about the current state of quantum computing in the US, in light of the Trump administration’s recent proposal to give a big boost to quantum computing and AI research, even while slashing and burning basic science more broadly. I made some critical comments—for example, about the need to support the whole basic research ecosystem (I pointed out that “quantum computing can’t thrive in isolation”), and also about the urgent need to make it feasible for the best researchers from around the world to get US visas and green cards. Unfortunately, those parts seem to have been edited out, in favor of my explanations of basic points about quantum computing.

There was a discussion on Twitter of the ethics of the “Quantum Bullshit Detector” Twitter feed—which dishes out vigilante justice, like some dark and troubled comic-book hero, by rendering anonymous, unexplained, unaccountable, very often correct albeit not infallible verdicts of “Bullshit” or “Not Bullshit” on claimed quantum information advances. As part of that discussion, Christopher Savoie wrote:

[Criticizing] is what we do in science. [But not calling] “bullshit” anonymously and without any accountability. Look at Scott Aaronson’s blog. He takes strong positions. But as Scott. I respect that.

What do people think: should “He takes strong positions. But as Scott.” be added onto the Shtetl-Optimized header bar?

In other news, I was amused by the following headline, for a Vice story about the MIP*=RE breakthrough: Mathematicians Are Studying Planet-Sized Supercomputers With God-Like Powers. (If I’m going to quibble about accuracy: only planet-sized???)

### MIP*=RE

Tuesday, January 14th, 2020

Another Update (Jan. 16): Yet another reason to be excited about this result—one that somehow hadn’t occurred to me—is that, as far as I know, it’s the first-ever fully convincing example of a non-relativizing computability result. See this comment for more.

Update: If you’re interested in the above topic, then you should probably stop reading this post right now, and switch to this better post by Thomas Vidick, one of the authors of the new breakthrough. (Or this by Boaz Barak or this by Lance Fortnow or this by Ken Regan.) (For background, also see Thomas Vidick’s excellent piece for the AMS Notices.)

Still here? Alright, alright…

Here’s the paper, which weighs in at 165 pages. The authors are Zhengfeng Ji, Anand Natarajan, my former postdoc Thomas Vidick, John Wright (who will be joining the CS faculty here at UT Austin this fall), and my wife Dana’s former student Henry Yuen. Rather than pretending that I can provide intelligent commentary on this opus in the space of a day, I’ll basically just open my comment section to discussion and quote the abstract:

We show that the class MIP* of languages that can be decided by a classical verifier interacting with multiple all-powerful quantum provers sharing entanglement is equal to the class RE of recursively enumerable languages. Our proof builds upon the quantum low-degree test of (Natarajan and Vidick, FOCS 2018) by integrating recent developments from (Natarajan and Wright, FOCS 2019) and combining them with the recursive compression framework of (Fitzsimons et al., STOC 2019).
An immediate byproduct of our result is that there is an efficient reduction from the Halting Problem to the problem of deciding whether a two-player nonlocal game has entangled value 1 or at most 1/2. Using a known connection, undecidability of the entangled value implies a negative answer to Tsirelson’s problem: we show, by providing an explicit example, that the closure Cqa of the set of quantum tensor product correlations is strictly included in the set Cqc of quantum commuting correlations. Following work of (Fritz, Rev. Math. Phys. 2012) and (Junge et al., J. Math. Phys. 2011) our results provide a refutation of Connes’ embedding conjecture from the theory of von Neumann algebras.

To say it differently (in response to a commenter’s request), some of the major implications are as follows.

(1) There is a protocol by which two entangled provers can convince a polynomial-time verifier of the answer to any computable problem whatsoever (!!), or indeed that a given Turing machine halts.

(2) There is a two-prover game, analogous to the Bell/CHSH game, for which Alice and Bob can do markedly better with a literally infinite amount of entanglement than they can with any finite amount of entanglement.

(3) There is no algorithm even to approximate the entangled value of a two-prover game (i.e., the probability that Alice and Bob win the game, if they use the best possible strategy and as much entanglement as they like). Instead, this problem is equivalent to the halting problem.

(4) There are types of correlations between Alice and Bob that can be produced using infinite entanglement, but that can’t even be approximated using any finite amount of entanglement.

(5) The Connes embedding conjecture, a central conjecture from the theory of operator algebras dating back to the 1970s, is false.

Note that all of these implications—including the ones for pure math and the foundations of quantum physics—were obtained using tools that originated in theoretical computer science, specifically the study of interactive proof systems.

I can remember when the class MIP* was first defined and studied, back around 2003, and people made the point that we didn’t know any reasonable upper bound on the class’s power—not NEXP, not NEEEEXP, not even the set of all computable languages. Back then, the joke was how far our proof techniques were from what was self-evidently the truth. I don’t remember a single person who seriously contemplated that two entangled provers could convince a polynomial-time verifier than an arbitrary Turing machine halts.

Still, ever since Natarajan and Wright’s NEEXP in MIP* breakthrough last year, all of us in quantum computing theory knew that MIP*=RE was a live possibility—and all through the summer and fall, I heard many hints that such a breakthrough was imminent.

It’s worth pointing out that, with only classical correlations between the provers, MIP gives “merely” the power of NEXP (Nondeterministic Exponential Time), while with arbitrary non-signalling correlations between the provers, the so-called MIPns gives the power of EXP (Deterministic Exponential Time). So it’s particularly striking that quantum entanglement, which is “intermediate” between classical correlations and arbitrary non-signalling correlations, yields such wildly greater computational power than either of those two.

The usual proviso applies: when I’ve blogged excitedly about preprints with amazing new results, most have stood, but at least two ended up being retracted. Still, assuming this one stands (as I’m guessing it will), I regard it as easily one of the biggest complexity-theoretic (and indeed computability-theoretic!) surprises so far in this century. Huge congratulations to the authors on what looks to be a historic achievement.

In unrelated news, for anyone for whom the 165-page MIP* paper is too heavy going (really??), please enjoy this CNBC video on quantum computing, which features several clips of yours truly speaking in front of a fake UT tower.

In other unrelated news, I’m also excited about this preprint by Avishay Tal, which sets a new record for the largest known separation between quantum query complexity and classical randomized query complexity, making substantial progress toward proving a conjecture by me and Andris Ambainis from 2015. (Not the “Aaronson-Ambainis Conjecture,” a different conjecture.)

### Quantum computing motte-and-baileys

Saturday, December 28th, 2019

In the wake of two culture-war posts—the first on the term “quantum supremacy,” the second on the acronym “NIPS”—it’s clear that we all need to cool off with something anodyne and uncontroversial. Fortunately, this holiday season, I know just the thing to bring everyone together: groaning about quantum computing hype!

When I was at the Q2B conference in San Jose, I learned about lots of cool stuff that’s happening in the wake of Google’s quantum supremacy announcement. I heard about the 57-qubit superconducting chip that the Google group is now building, following up on its 53-qubit one; and also about their first small-scale experimental demonstration of my certified randomness protocol. I learned about recent progress on costing out the numbers of qubits and gates needed to do fault-tolerant quantum simulations of useful chemical reactions (IIRC, maybe a hundred thousand qubits and a few hours’ worth of gates—scary, but not Shor’s algorithm scary).

I also learned about two claims about quantum algorithms that startups have made, and which are being wrongly interpreted. The basic pattern is one that I’ve come to know well over the years, and which you could call a science version of the motte-and-bailey. (For those not up on nerd blogosphere terminology: in medieval times, the motte was a dank castle to which you’d retreat while under attack; the bailey was the desirable land that you’d farm once the attackers left.)

To wit:

1. Startup makes claims that have both a true boring interpretation (e.g., you can do X with a quantum computer), as well as a false exciting interpretation (e.g., you can do X with a quantum computer, and it would actually make sense to do this, because you’ll get an asymptotic speedup over the best known classical algorithm).
2. Lots of business and government people get all excited, because they assume the false exciting interpretation must be true (or why else would everyone be talking about this?). Some of those people ask me for comment.
3. I look into it, perhaps by asking the folks at the startup. The startup folks clarify that they meant only the true boring interpretation. To be sure, they’re actively exploring the false exciting interpretation—whether some parts of it might be true after all—but they’re certainly not making any claims about it that would merit, say, a harsh post on Shtetl-Optimized.
4. I’m satisfied to have gotten to the bottom of things, and I tell the startup folks to go their merry way.
5. Yet many people continue to seem as excited as if the false exciting interpretation had been shown to be true. They continue asking me questions that presuppose its truth.

Our first instance of this pattern is the recent claim, by Zapata Computing, to have set a world record for integer factoring (1,099,551,473,989 = 1,048,589 × 1,048,601) with a quantum computer, by running a QAOA/variational algorithm on IBM’s superconducting device. Gosh! That sure sounds a lot better than the 21 that’s been factored with Shor’s algorithm, doesn’t it?

I read the Zapata paper that this is based on, entitled “Variational Quantum Factoring,” and I don’t believe that a single word in it is false. My issue is something the paper omits: namely, that once you’ve reduced factoring to a generic optimization problem, you’ve thrown away all the mathematical structure that Shor’s algorithm cleverly exploits, and that makes factoring asymptotically easy for a quantum computer. And hence there’s no reason to expect your quantum algorithm to scale any better than brute-force trial division (or in the most optimistic scenario, trial division enhanced with Grover search). On large numbers, your algorithm will be roundly outperformed even by classical algorithms that do exploit structure, like the Number Field Sieve. Indeed, the quantum computer’s success at factoring the number will have had little or nothing to do with its being quantum at all—a classical optimization algorithm would’ve served as well. And thus, the only reasons to factor a number on a quantum device in this way, would seem to be stuff like calibrating the device.

Admittedly, to people who work in quantum algorithms, everything above is so obvious that it doesn’t need to be said. But I learned at Q2B that there are interested people for whom this is not obvious, and even comes as a revelation. So that’s why I’m saying it.

Again and again over the past twenty years, I’ve seen people reinvent the notion of a “simpler alternative” to Shor’s algorithm: one that cuts out all the difficulty of building a fault-tolerant quantum computer. In every case, the trouble, typically left unstated, has been that these alternatives also cut out the exponential speedup that’s Shor’s algorithm’s raison d’être.

Our second example today of a quantum computing motte-and-bailey is the claim, by Toronto-based quantum computing startup Xanadu, that Gaussian BosonSampling can be used to solve all sorts of graph problems, like graph isomorphism, graph similarity, and densest subgraph. As the co-inventor of BosonSampling, few things would warm my heart more than finding an actual application for that model (besides quantum supremacy experiments and, perhaps, certified random number generation). But I still regard this as an open problem—if by “application,” we mean outperforming what you could’ve done classically.

In papers (see for example here, here, here), members of the Xanadu team have given all sorts of ways to take a graph, and encode it into an instance of Gaussian BosonSampling, in such a way that the output distribution will then reveal features of the graph, like its isomorphism type or its dense subgraphs. The trouble is that so far, I’ve seen no indications that this will actually lead to quantum algorithms that outperform the best classical algorithms, for any graph problems of practical interest.

In the case of Densest Subgraph, the Xanadu folks use the output of a Gaussian BosonSampler to seed (that is, provide an initial guess for) a classical local search algorithm. They say they observe better results this way than if they seed that classical local search algorithm with completely random initial conditions. But of course, the real question is: could we get equally good results by seeding with the output of some classical heuristic? Or by solving Densest Subgraph with a different approach entirely? Given how hard it’s turned out to be just to verify that the outputs of a BosonSampling device come from such a device at all, it would seem astonishing if the answer to these questions wasn’t “yes.”

In the case of Graph Isomorphism, the situation is even clearer. There, the central claim made by the Xanadu folks is that given a graph G, they can use a Gaussian BosonSampling device to sample a probability distribution that encodes G’s isomorphism type. So, isn’t this “promising” for solving GI with a quantum computer? All you’d need to do now is invent some fast classical algorithm that could look at the samples coming from two graphs G and H, and tell you whether the probability distributions were the same.

Except, not really. While the Xanadu paper never says so, if all you want is to sample a distribution that encodes a graph’s isomorphism type, that’s easy to do classically! (I even put this on the final exam for my undergraduate Quantum Information Science course a couple weeks ago.) Here’s how: given as input a graph G, just output G but with its vertices randomly permuted. Indeed, this will even provide a further property, better than anything the BosonSampling approach has been shown to provide (or than it probably does provide): namely, if G and H are not isomorphic, then the two probability distributions will not only be different but will have disjoint supports. Alas, this still leaves us with the problem of distinguishing which distribution a given sample came from, which is as hard as Graph Isomorphism itself. None of these approaches, classical or quantum, seem to lead to any algorithm that’s subexponential time, let alone competitive with the “Babai approach” of thinking really hard about graphs.

All of this stuff falls victim to what I regard as the Fundamental Error of Quantum Algorithms Research: namely, to treat it as “promising” that a quantum algorithm works at all, or works better than some brute-force classical algorithm, without asking yourself whether there are any indications that your approach will ever be able to exploit interference of amplitudes to outperform the best classical algorithm.

Incidentally, I’m not sure exactly why, but in practice, a major red flag that the Fundamental Error is about to be committed is when someone starts talking about “hybrid quantum/classical algorithms.” By this they seem to mean: “outside the domain of traditional quantum algorithms, so don’t judge us by the standards of that domain.” But I liked the way someone at Q2B put it to me: every quantum algorithm is a “hybrid quantum/classical algorithm,” with classical processors used wherever they can be, and qubits used only where they must be.

The other thing people do, when challenged, is to say “well, admittedly we have no rigorous proof of an asymptotic quantum speedup”—thereby brilliantly reframing the whole conversation, to make people like me look like churlish theoreticians insisting on an impossible and perhaps irrelevant standard of rigor, blind to some huge practical quantum speedup that’s about to change the world. The real issue, of course, is not that they haven’t given a proof of a quantum speedup (in either the real world or the black-box world); rather, it’s that they’ve typically given no reasons whatsoever to think that there might be a quantum speedup, compared to the best classical algorithms available.

In the holiday spirit, let me end on a positive note. When I did the Q&A at Q2B—the same one where Sarah Kaiser asked me to comment on the term “quantum supremacy”—one of my answers touched on the most important theoretical open problems about sampling-based quantum supremacy experiments. At the top of the list, I said, was whether there’s some interactive protocol by which a near-term quantum computer can not only exhibit quantum supremacy, but prove it to a polynomial-time-bounded classical skeptic. I mentioned that there was one proposal for how to do this, in the IQP model, due to Bremner and Shepherd, from way back in 2008. I said that their proposal deserved much more attention than it had received, and that trying to break it would be one obvious thing to work on. Little did I know that, literally while I was speaking, a paper was being posted to the arXiv, by Gregory Kahanamoku-Meyer, that claims to break Bremner and Shepherd’s protocol. I haven’t yet studied the paper, but assuming it’s correct, it represents the first clear progress on this problem in years (even though of a negative kind). Cool!!

### Quantum Dominance, Hegemony, and Superiority

Thursday, December 19th, 2019

Yay! I’m now a Fellow of the ACM. Along with my fellow new inductee Peter Shor, who I hear is a real up-and-comer in the quantum computing field. I will seek to use this awesome responsibility to steer the ACM along the path of good rather than evil.

Also, last week, I attended the Q2B conference in San Jose, where a central theme was the outlook for practical quantum computing in the wake of the first clear demonstration of quantum computational supremacy. Thanks to the folks at QC Ware for organizing a fun conference (full disclosure: I’m QC Ware’s Chief Scientific Advisor). I’ll have more to say about the actual scientific things discussed at Q2B in future posts.

None of that is why you’re here, though. You’re here because of the battle over “quantum supremacy.”

A week ago, my good friend and collaborator Zach Weinersmith, of SMBC Comics, put out a cartoon with a dark-curly-haired scientist named “Dr. Aaronson,” who’s revealed on a hot mic to be an evil “quantum supremacist.” Apparently a rush job, this cartoon is far from Zach’s finest work. For one thing, if the character is supposed to be me, why not draw him as me, and if he isn’t, why call him “Dr. Aaronson”? In any case, I learned from talking to Zach that the cartoon’s timing was purely coincidental: Zach didn’t even realize what a hornet’s-nest he was poking with this.

Ever since John Preskill coined it in 2012, “quantum supremacy” has been an awkward term. Much as I admire John Preskill’s wisdom, brilliance, generosity, and good sense, in physics as in everything else—yeah, “quantum supremacy” is not a term I would’ve coined, and it’s certainly not a hill I’d choose to die on. Once it had gained common currency, though, I sort of took a liking to it, mostly because I realized that I could mine it for dark one-liners in my talks.

The thinking was: even as white supremacy was making its horrific resurgence in the US and around the world, here we were, physicists and computer scientists and mathematicians of varied skin tones and accents and genders, coming together to pursue a different and better kind of supremacy—a small reflection of the better world that we still believed was possible. You might say that we were reclaiming the word “supremacy”—which, after all, just means a state of being supreme—for something non-sexist and non-racist and inclusive and good.

In the world of 2019, alas, perhaps it was inevitable that people wouldn’t leave things there.

My first intimation came a month ago, when Leonie Mueck—someone who I’d gotten to know and like when she was an editor at Nature handling quantum information papers—emailed me about her view that our community should abandon the term “quantum supremacy,” because of its potential to make women and minorities uncomfortable in our field. She advocated using “quantum advantage” instead.

So I sent Leonie back a friendly reply, explaining that, as the father of a math-loving 6-year-old girl, I understood and shared her concerns—but also, that I didn’t know an alternative term that really worked.

See, it’s like this. Preskill meant “quantum supremacy” to refer to a momentous event that seemed likely to arrive in a matter of years: namely, the moment when programmable quantum computers would first outpace the ability of the fastest classical supercomputers on earth, running the fastest algorithms known by humans, to simulate what the quantum computers were doing (at least on special, contrived problems). And … “the historic milestone of quantum advantage”? It just doesn’t sound right. Plus, as many others pointed out, the term “quantum advantage” is already used to refer to … well, quantum advantages, which might fall well short of supremacy.

But one could go further. Suppose we did switch to “quantum advantage.” Couldn’t that term, too, remind vulnerable people about the unfair advantages that some groups have over others? Indeed, while “advantage” is certainly subtler than “supremacy,” couldn’t that make it all the more insidious, and therefore dangerous?

Oblivious though I sometimes am, I realized Leonie would be unhappy if I offered that, because of my wholehearted agreement, I would henceforth never again call it “quantum supremacy,” but only “quantum superiority,” “quantum dominance,” or “quantum hegemony.”

But maybe you now see the problem. What word does the English language provide to describe one thing decisively beating or being better than a different thing for some purpose, and which doesn’t have unsavory connotations?

I’ve heard “quantum ascendancy,” but that makes it sound like we’re a UFO cult—waiting to ascend, like ytterbium ions caught in a laser beam, to a vast quantum computer in the sky.

I’ve heard “quantum inimitability” (that is, inability to imitate using a classical computer), but who can pronounce that?

Yesterday, my brilliant former student Ewin Tang (yes, that one) relayed to me a suggestion by Kevin Tian: “quantum eclipse” (that is, the moment when quantum computers first eclipse classical ones for some task). But would one want to speak of a “quantum eclipse experiment”? And shouldn’t we expect that, the cuter and cleverer the term, the harder it will be to use unironically?

In summary, while someone might think of a term so inspired that it immediately supplants “quantum supremacy” (and while I welcome suggestions), I currently regard it as an open problem.

Anyway, evidently dissatisfied with my response, last week Leonie teamed up with 13 others to publish a letter in Nature, which was originally entitled “Supremacy is for racists—use ‘quantum advantage,'” but whose title I see has now been changed to the less inflammatory “Instead of ‘supremacy’ use ‘quantum advantage.'” Leonie’s co-signatories included four of my good friends and colleagues: Alan Aspuru-Guzik, Helmut Katzgraber, Anne Broadbent, and Chris Granade (the last of whom got started in the field by helping me edit Quantum Computing Since Democritus).

(Update: Leonie pointed me to a longer list of signatories here, at their website called “quantumresponsibility.org.” A few names that might be known to Shtetl-Optimized readers are Andrew White, David Yonge-Mallo, Debbie Leung, Matt Leifer, Matthias Troyer.)

Their letter says:

The community claims that quantum supremacy is a technical term with a specified meaning. However, any technical justification for this descriptor could get swamped as it enters the public arena after the intense media coverage of the past few months.

In our view, ‘supremacy’ has overtones of violence, neocolonialism and racism through its association with ‘white supremacy’. Inherently violent language has crept into other branches of science as well — in human and robotic spaceflight, for example, terms such as ‘conquest’, ‘colonization’ and ‘settlement’ evoke the terra nullius arguments of settler colonialism and must be contextualized against ongoing issues of neocolonialism.

Instead, quantum computing should be an open arena and an inspiration for a new generation of scientists.

When I did an “Ask Me Anything” session, as the closing event at Q2B, Sarah Kaiser asked me to comment on the Nature petition. So I repeated what I’d said in my emailed response to Leonie—running through the problems with each proposed alternative term, talking about the value of reclaiming the word “supremacy,” and mostly just trying to diffuse the tension by getting everyone laughing together. Sarah later tweeted that she was “really disappointed” in my response.

Then the Wall Street Journal got in on the action, with a brief editorial (warning: paywalled) mocking the Nature petition:

There it is, folks: Mankind has hit quantum wokeness. Our species, akin to Schrödinger’s cat, is simultaneously brilliant and brain-dead. We built a quantum computer and then argued about whether the write-up was linguistically racist.

Taken seriously, the renaming game will never end. First put a Sharpie to the Supremacy Clause of the U.S. Constitution, which says federal laws trump state laws. Cancel Matt Damon for his 2004 role in “The Bourne Supremacy.” Make the Air Force give up the term “air supremacy.” Tell lovers of supreme pizza to quit being so chauvinistic about their toppings. Please inform Motown legend Diana Ross that the Supremes are problematic.

The quirks of quantum mechanics, some people argue, are explained by the existence of many universes. How did we get stuck in this one?

Steven Pinker also weighed in, with a linguistically-informed tweetstorm:

This sounds like something from The Onion but actually appeared in Nature … It follows the wokified stigmatization of other innocent words, like “House Master” (now, at Harvard, Residential Dean) and “NIPS” (Neural Information Processing Society, now NeurIPS). It’s a familiar linguistic phenomenon, a lexical version of Gresham’s Law: bad meanings drive good ones out of circulation. Examples: the doomed “niggardly” (no relation to the n-word) and the original senses of “cock,” “ass,” “prick,” “pussy,” and “booty.” Still, the prissy banning of words by academics should be resisted. It dumbs down understanding of language: word meanings are conventions, not spells with magical powers, and all words have multiple senses, which are distinguished in context. Also, it makes academia a laughingstock, tars the innocent, and does nothing to combat actual racism & sexism.

Others had a stronger reaction. Curtis Yarvin, better known as Mencius Moldbug, is one of the founders of “neoreaction” (and a significant influence on Steve Bannon, Michael Anton, and other Trumpists). Regulars might remember that Yarvin argued with me in Shtetl-Optimized‘s comment section, under a post in which I denounced Trump’s travel ban and its effects on my Iranian PhD student. Since then, Yarvin has sent me many emails, which have ranged from long to extremely long, and whose message could be summarized as: “[labored breathing] Abandon your liberal Enlightenment pretensions, young Nerdwalker. Come over the Dark Side.”

After the “supremacy is for racists” letter came out in Nature, though, Yarvin sent me his shortest email ever. It was simply a link to the letter, along with the comment “I knew it would come to this.”

He meant: “What more proof do you need, young Nerdawan, that this performative wokeness is a cancer that will eventually infect everything you value—even totally apolitical research in quantum information? And by extension, that my whole worldview, which warned of this, is fundamentally correct, while your faith in liberal academia is naïve, and will be repaid only with backstabbing?”

In a subsequent email, Yarvin predicted that in two years, the whole community will be saying “quantum advantage” instead of “quantum supremacy,” and in five years I’ll be saying “quantum advantage” too. As Yarvin famously wrote: “Cthulhu may swim slowly. But he only swims left.”

So what do I really think about this epic battle for (and against) supremacy?

Truthfully, half of me just wants to switch to “quantum advantage” right now and be done with it. As I said, I know some of the signatories of the Nature letter to be smart and reasonable and kind. They don’t wish to rid the planet of everyone like me. They’re not Amanda Marcottes or Arthur Chus. Furthermore, there’s little I despise more than a meaty scientific debate devolving into a pointless semantic one, with brilliant friend after brilliant friend getting sucked into the vortex (“you too?”). I’m strongly in the Pinkerian camp, which holds that words are just arbitrary designators, devoid of the totemic power to dictate thoughts. So if friends and colleagues—even just a few of them—tell me that they find some word I use to be offensive, why not just be a mensch, apologize for any unintended hurt, switch words midsentence, and continue discussing the matter at hand?

But then the other half of me wonders: once we’ve ceded an open-ended veto over technical terms that remind anyone of anything bad, where does it stop? How do we ever certify a word as kosher? At what point do we all get to stop arguing and laugh together?

To make this worry concrete, look back at Sarah Kaiser’s Twitter thread—the one where she expresses disappointment in me. Below her tweet, someone remarks that, besides “quantum supremacy,” the word “ancilla” (as in ancilla qubit, a qubit used for intermediate computation or other auxiliary purposes) is problematic as well. Here’s Sarah’s response:

I agree, but I wanted to start by focusing on the obvious one, Its harder for them to object to just one to start with, then once they admit the logic, we can expand the list

(What would Curtis Yarvin say about that?)

You’re probably now wondering: what’s wrong with “ancilla”? Apparently, in ancient Rome, an “ancilla” was a female slave, and indeed that’s the Latin root of the English adjective “ancillary” (as in “providing support to”). I confess that I hadn’t known that—had you? Admittedly, once you do know, you might never again look at a Controlled-NOT gate—pitilessly flipping an ancilla qubit, subject only to the whims of a nearby control qubit—in quite the same way.

(Ah, but the ancilla can fight back against her controller! And she does—in the Hadamard basis.)

The thing is, if we’re gonna play this game: what about annihilation operators? Won’t those need to be … annihilated from physics?

And what about unitary matrices? Doesn’t their very name negate the multiplicity of perspectives and cultures?

What about Dirac’s oddly-named bra/ket notation, with its limitless potential for puerile jokes, about the “bra” vectors displaying their contents horizontally and so forth? (Did you smile at that, you hateful pig?)

What about daggers? Don’t we need a less violent conjugate tranpose?

Not to beat a dead horse, but once you hunt for examples, you realize that the whole dictionary is shot through with domination and brutality—that you’d have to massacre the English language to take it out. There’s nothing special about math or physics in this respect.

The same half of me also thinks about my friends and colleagues who oppose claims of quantum supremacy, or even the quest for quantum supremacy, on various scientific grounds. I.e., either they don’t think that the Google team achieved what it said, or they think that the task wasn’t hard enough for classical computers, or they think that the entire goal is misguided or irrelevant or uninteresting.

Which is fine—these are precisely the arguments we should be having—except that I’ve personally seen some of my respected colleagues, while arguing for these positions, opportunistically tack on ideological objections to the term “quantum supremacy.” Just to goose up their case, I guess. And I confess that every time they did this, it made me want to keep saying “quantum supremacy” from now till the end of time—solely to deny these colleagues a cheap and unearned “victory,” one they apparently felt they couldn’t obtain on the merits alone. I realize that this is childish and irrational.

Most of all, though, the half of me that I’m talking about thinks about Curtis Yarvin and the Wall Street Journal editorial board, cackling with glee to see their worldview so dramatically confirmed—as theatrical wokeness, that self-parodying modern monstrosity, turns its gaze on (of all things) quantum computing research. More red meat to fire up the base—or at least that sliver of the base nerdy enough to care. And the left, as usual, walks right into the trap, sacrificing its credibility with the outside world to pursue a runaway virtue-signaling spiral.

The same half of me thinks: do we really want to fight racism and sexism? Then let’s work together to assemble a broad coalition that can defeat Trump. And Jair Bolsonaro, and Viktor Orbán, and all the other ghastly manifestations of humanity’s collective lizard-brain. Then, if we’re really fantasizing, we could liberalize the drug laws, and get contraception and loans and education to women in the Third World, and stop the systematic disenfranchisement of black voters, and open up the world’s richer, whiter, and higher-elevation countries to climate refugees, and protect the world’s remaining indigenous lands (those that didn’t burn to the ground this year).

In this context, the trouble with obsessing over terms like “quantum supremacy” is not merely that it diverts attention, while contributing nothing to fighting the world’s actual racism and sexism. The trouble is that the obsessions are actually harmful. For they make academics—along with progressive activists—look silly. They make people think that we must not have meant it when we talked about the existential urgency of climate change and the world’s other crises. They pump oxygen into right-wing echo chambers.

But it’s worse than ridiculous, because of the message that I fear is received by many outside the activists’ bubble. When you say stuff like “[quantum] supremacy is for racists,” what’s heard might be something more like:

“Watch your back, you disgusting supremacist. Yes, you. You claim that you mentor women and minorities, donate to good causes, try hard to confront the demons in your own character? Ha! None of that counts for anything with us. You’ll never be with-it enough to be our ally, so don’t bother trying. We’ll see to it that you’re never safe, not even in the most abstruse and apolitical fields. We’ll comb through your words—even words like ‘ancilla qubit’—looking for any that we can cast as offensive by our opaque and ever-shifting standards. And once we find some, we’ll have it within our power to end your career, and you’ll be reduced to groveling that we don’t. Remember those popular kids who bullied you in second grade, giving you nightmares of social ostracism that persist to this day? We plan to achieve what even those bullies couldn’t: to shame you with the full backing of the modern world’s moral code. See, we’re the good guys of this story. It’s goodness itself that’s branding you as racist scum.”

In short, I claim that the message—not the message intended, of course, by anyone other than a Chu or a Marcotte or a SneerClubber, but the message received—is basically a Trump campaign ad. I claim further that our civilization’s current self-inflicted catastrophe will end—i.e., the believers in science and reason and progress and rule of law will claw their way back to power—when, and only when, a generation of activists emerges that understands these dynamics as well as Barack Obama did.

Wouldn’t it be awesome if, five years from now, I could say to Curtis Yarvin: you were wrong? If I could say to him: my colleagues and I still use the term ‘quantum supremacy’ whenever we care to, and none of us have been cancelled or ostracized for it—so maybe you should revisit your paranoid theories about Cthulhu and the Cathedral and so forth? If I could say: quantum computing researchers now have bigger fish to fry than arguments over words—like moving beyond quantum supremacy to the first useful quantum simulations, as well as the race for scalability and fault-tolerance? And even: progressive activists now have bigger fish to fry too—like retaking actual power all over the world?

Anyway, as I said, that’s how half of me feels. The other half is ready to switch to “quantum advantage” or any other serviceable term and get back to doing science.

### Guest post by Greg Kuperberg: Archimedes’ other principle and quantum supremacy

Tuesday, November 26th, 2019

Scott’s Introduction: Happy Thanksgiving! Please join me in giving thanks for the beautiful post below, by friend-of-the-blog Greg Kuperberg, which tells a mathematical story that stretches from the 200s BC all the way to Google’s quantum supremacy result last month.

## Archimedes’ other principle and quantum supremacy

by Greg Kuperberg

Note: UC Davis is hiring in CS theory! Scott offered me free ad space if I wrote a guest post, so here we are. The position is in all areas of CS theory, including QC theory although the search is not limited to that.

In this post, I wear the hat of a pure mathematician in a box provided by Archimedes. I thus set aside what everyone else thinks is important about Google’s 53-qubit quantum supremacy experiment, that it is a dramatic milestone in quantum computing technology. That’s only news about the physical world, whose significance pales in comparison to the Platonic world of mathematical objects. In my happy world, I like quantum supremacy as a demonstration of a beautiful coincidence in mathematics that has been known for more than 2000 years in a special case. The single-qubit case was discovered by Archimedes, duh. As Scott mentions in Quantum Computing Since Democritus, Bill Wootters stated the general result in a 1990 paper, but Wootters credits a 1974 paper by the Czech physicist Stanislav Sýkora. I learned of it in the substantially more general context of symplectic geometric that mathematicians developed independently between Sýkora’s prescient paper and Wootters’ more widely known citation. Much as I would like to clobber you with highly abstract mathematics, I will wait for some other time.

Suppose that you pick a pure state $$|\psi\rangle$$ in the Hilbert space $$\mathbb{C}^d$$ of a $$d$$-dimensional qudit, and then make many copies and fully measure each one, so that you sample many times from some distribution $$\mu$$ on the $$d$$ outcomes. You can think of such a distribution $$\mu$$ as a classical randomized state on a digit of size $$d$$. The set of all randomized states on a $$d$$-digit makes a $$(d-1)$$-dimensional simplex $$\Delta^{d-1}$$ in the orthant $$\mathbb{R}_{\ge 0}^d$$. The coincidence is that if $$|\psi\rangle$$ is uniformly random in the unit sphere in $$\mathbb{C}^d$$, then $$\mu$$ is uniformly random in $$\Delta^{d-1}$$. I will call it the Born map, since it expresses the Born rule of quantum mechanics that amplitudes yield probabilities. Here is a diagram of the Born map of a qutrit, except with the laughable simplification of the 5-sphere in $$\mathbb{C}^3$$ drawn as a 2-sphere.

If you pretend to be a bad probability student, then you might not be surprised by this coincidence, because you might suppose that all probability distributions are uniform other than treacherous exceptions to your intuition. However, the principle is certainly not true for a “rebit” (a qubit with real amplitudes) or for higher-dimensional “redits.” With real amplitudes, the probability density goes to infinity at the sides of the simplex $$\Delta^{d-1}$$ and is even more favored at the corners. It also doesn’t work for mixed qudit states; the projection then favors the middle of $$\Delta^{d-1}$$.

### Archimedes’ theorem

The theorem of Archimedes is that a natural projection from the unit sphere to a circumscribing vertical cylinder preserves area. The projection is the second one that you might think of: Project radially from a vertical axis rather than radially in all three directions. Since Archimedes was a remarkably prescient mathematician, he was looking ahead to the Bloch sphere of pure qubit states $$|\psi\rangle\langle\psi|$$ written in density operator form. If you measure $$|\psi\rangle\langle\psi|$$ in the computational basis, you get a randomized bit state $$\mu$$ somewhere on the interval from guaranteed 0 to guaranteed 1.

This transformation from a quantum state to a classical randomized state is a linear projection to a vertical axis. It is the same as Archimedes’ projection, except without the angle information. It doesn’t preserve dimension, but it does preserve measure (area or length, whatever) up to a factor of $$2\pi$$. In particular, it takes a uniformly random $$|\psi\rangle\langle\psi|$$ to a uniformly random $$\mu$$.

Archimedes’ projection is also known as the Lambert cylindrical map of the world. This is the map that squishes Greenland along with the top of North America and Eurasia to give them proportionate area.

(I forgive Lambert if he didn’t give prior credit to Archimedes. There was no Internet back then to easily find out who did what first.) Here is a calculus-based proof of Archimedes’ theorem: In spherical coordinates, imagine an annular strip on the sphere at a polar angle of $$\theta$$. (The polar angle is the angle from vertical in spherical coordinates, as depicted in red in the Bloch sphere diagram.) The strip has a radius of $$\sin\theta$$, which makes it shorter than its unit radius friend on the cylinder. But it’s also tilted from vertical by an angle of $$\frac{\pi}2-\theta$$, which makes it wider by a factor of $$1/(\sin \theta)$$ than the height of its projection onto the $$z$$ axis. The two factors exactly cancel out, making the area of the strip exactly proportional to the length of its projection onto the $$z$$ axis. This is a coincidence which is special to the 2-sphere in 3 dimensions. As a corollary, we get that the surface area of a unit sphere is $$4\pi$$, the same as an open cylinder with radius 1 and height 2. If you want to step through this in even more detail, Scott mentioned to me an action video which is vastly spiffier than anything that I could ever make.

The projection of the Bloch sphere onto an interval also shows what goes wrong if you try this with a rebit. The pure rebit states — again expressed in density operator form $$|\psi\rangle\langle\psi|$$ are a great circle in the Bloch sphere. If you linearly project a circle onto an interval, then the length of the circle is clearly bunched up at the ends of the interval and the projected measure on the interval is not uniform.

### Sýkora’s generalization

It is a neat coincidence that the Born map of a qubit preserves measure, but a proof that relies on Archimedes’ theorem seems to depend on the special geometry of the Bloch sphere of a qubit. That the higher-dimensional Born map also preserves measure is downright eerie. Scott challenged me to write an intuitive explanation. I remembered two different (but similar) proofs, neither of which is original to me. Scott and I disagree as to which proof is nicer.

As a first step of the first proof, it is easy to show that the Born map $$p = |z|^2$$ for a single amplitude $$z$$ preserves measure as a function from the complex plane $$\mathbb{C}$$ to the ray $$\mathbb{R}_{\ge 0}$$. The region in the complex numbers $$\mathbb{C}$$ where the length of $$z$$ is between $$a$$ and $$b$$, or $$a \le |z| \le b$$, is $$\pi(b^2 – a^2)$$. The corresponding interval for the probability is $$a^2 \le p \le b^2$$, which thus has length $$b^2-a^2$$. That’s all, we’ve proved it! More precisely, the area of any circularly symmetric region in $$\mathbb{C}$$ is $$\pi$$ times the length of its projection onto $$\mathbb{R}_{\ge 0}$$.

The second step is to show the same thing for the Born map from the $$d$$-qudit Hilbert space $$\mathbb{C}^d$$ to the $$d$$-digit orthant $$\mathbb{R}_{\ge 0}^d$$, again without unit normalization. It’s also measure-preserving, up to a factor of $$\pi^d$$ this time, because it’s the same thing in each coordinate separately. To be precise, the volume ratio holds for any region in $$\mathbb{C}^d$$ that is invariant under separately rotating each of the $$d$$ phases. (Because you can approximate any such region with a union of products of thin annuli.)

The third and final step is the paint principle for comparing surface areas. If you paint the hoods of two cars with the same thin layer of paint and you used the same volume of paint for each one, then you can conclude that the two car hoods have nearly same area. In our case, the Born map takes the region $1 \le |z_0|^2 + |z_1|^2 + \cdots + |z_{d-1}|^2 \le 1+\epsilon$ in $$\mathbb{C}^d$$ to the region $1 \le p_0 + p_1 + \cdots + p_{d-1} \le 1+\epsilon$ in the orthant $$\mathbb{R}_{\ge 0}^d$$. The former is the unit sphere $$S^{2d-1}$$ in $$\mathbb{C}^d$$ painted to a thickness of roughly $$\epsilon/2$$. The latter is the probability simplex $$\Delta^{n-1}$$ painted to a thickness of exactly $$\epsilon$$. Taking the limit $$\epsilon \to 0$$, the Born map from $$S^{2d-1}$$ to $$\Delta^{n-1}$$ preserves measure up to a factor of $$2\pi^n$$.

You might wonder “why” this argument works even if you accept that it does work. The key is that the exponent 2 appears in two different ways: as the dimension of the complex numbers, and as the exponent used to set probabilities and define spheres. If we try the same argument with real amplitudes, then the volume between “spheres” of radius $$a$$ and $$b$$ is just $$2(b-a)$$, which does not match the length $$b^2-a^2$$. The Born map for a single real amplitude is the parabola $$p = x^2$$, which clearly distorts length since it is not linear. The higher-dimensional real Born map similarly distorts volumes, whether or not you restrict to unit-length states.

If you’re a bitter-ender who still wants Archimedes’ theorem for real amplitudes, then you might consider the variant formula $$p = |x|$$ to obtain a probability $$p$$ from a “quantum amplitude” $$x$$. Then the “Born” map does preserve measure, but for the trivial reason that $$x = \pm p$$ is not really a quantum amplitude, it is a probability with a vestigial sign. Also the unit “sphere” in $$\mathbb{R}^d$$ is not really a sphere in this theory, it is a hyperoctahedron. The only “unitary” operators that preserve the unit hyperoctahedron are signed permutation matrices. You can only use them for reversible classical computing or symbolic dynamics; they don’t have the strength of true quantum computing or quantum mechanics.

The fact that the Born map preserves measure also yields a bonus calculation of the volume of the unit ball in $$2d$$ real dimensions, if we interpret that as $$d$$ complex dimensions. The ball $|z_0|^2 + |z_1|^2 + \cdots + |z_{d-1}|^2 \le 1$ in $$\mathbb{C}^d$$ is sent to a different simplex $p_0 + p_1 + \cdots + p_{d-1} \le 1$ in $$\mathbb{R}_{\ge 0}^d$$. If we recall that the volume of a $$d$$-dimensional pyramid is $$\frac1d$$ times base times height and calculate by induction on $$d$$, we get that this simplex has volume $$\frac1{d!}$$. Thus, the volume of the $$2d$$-dimensional unit ball is $$\frac{\pi^d}{d!}$$.

You might ask whether the volume of a $$d$$-dimensional unit ball is always $$\frac{\pi^{d/2}}{(d/2)!}$$ for both $$d$$ even and odd. The answer is yes if we interpret factorials using the gamma function formula $$x! = \Gamma(x+1)$$ and look up that $$\frac12! = \Gamma(\frac32) = \frac{\sqrt{\pi}}2$$. The gamma function was discovered by Euler as a solution to the question of defining fractional factorials, but the notation $$\Gamma(x)$$ and the cumbersome shift by 1 is due to Legendre. Although Wikipedia says that no one knows why Legendre defined it this way, I wonder if his goal was to do what the Catholic church later did for itself in 1978: It put a Pole at the origin.

(Scott wanted to censor this joke. In response, I express my loyalty to my nation of birth by quoting the opening of the Polish national anthem: “Poland has not yet died, so long as we still live!” I thought at first that Stanislav Sýkora is Polish since Stanisław and Sikora are both common Polish names, but his name has Czech spelling and he is Czech. Well, the Czechs are cool too.)

Sýkora’s 1974 proof of the generalized Archimedes’ theorem is different from this one. He calculates multivariate moments of the space of unit states $$S^{2d-1} \subseteq \mathbb{C}^d$$, and confirms that they match the moments in the probability simplex $$\Delta^{d-1}$$. There are inevitably various proofs of this result, and I will give another one.

### Another proof, and quantum supremacy

There is a well-known and very useful algorithm to generate a random point on the unit sphere in either $$\mathbb{R}^d$$ or $$\mathbb{C}^d$$, and a similar algorithm to generate a random point in a simplex. In the former algorithm, we make each real coordinate $$x$$ into an independent Gaussian random variable with density proportional to $$e^{-x^2}\;dx$$, and then rescale the result to unit length. Since the exponents combine as $e^{-x_0^2}e^{-x_1^2}\cdots e^{-x_{d-1}^2} = e^{-(x_0^2 + x_1^2 + \cdots + x_{d-1}^2)},$ we learn that the total exponent is spherically symmetric. Therefore after rescaling, the result is a uniformly random point on the unit sphere $$S^{d-1} \subseteq \mathbb{R}^d$$. Similarly, the other algorithm generates a point in the orthant $$\mathbb{R}_{\ge 0}^d$$ by making each real coordinate $$p \ge 0$$ an independent random variable with exponential distribution $$e^{-p}\;dp$$. This time we rescale the vector until its sum is 1. This algorithm likewise produces a uniformly random point in the simplex $$\Delta^{d-1} \subseteq \mathbb{R}_{\ge 0}^d$$ because the total exponent of the product $e^{-p_0}e^{-p_1}\cdots e^{-p_{d-1}} = e^{-(p_0 + p_1 + \cdots + p_{d-1})}$ only depends on the sum of the coordinates. Wootters describes both of these algorithms in his 1990 paper, but instead of relating them to give his own proof of the generalized Archimedes’ theorem, he cites Sýkora.

The gist of the proof is that the Born map takes the Gaussian algorithm to the exponential algorithm. Explicitly, the Gaussian probability density for a single complex amplitude $z = x+iy = re^{i\theta}$ can be converted from Cartesian to polar coordinate as follows: $\frac{e^{-|z|^2}\;dx\;dy}{\pi} = \frac{e^{-r^2}r\;dr\;d\theta}{\pi}.$ I have included the factor of $$r$$ that is naturally present in an area integral in polar coordinates. We will need it, and it is another way to see that the theorem relies on the fact that the complex numbers are two-dimensional. To complete the proof, we substitute $$p = r^2$$ and remember that $$dp = 2r\;dr$$, and then integrate over $$\theta$$ (trivially, since the integrand does not depend on $$\theta$$). The density simplifies to $$e^{-p}\;dp$$, which is exactly the exponential distribution for a real variable $$p \ge 0$$. Since the Born map takes the Gaussian algorithm to the exponential algorithm, and since each algorithm produces a uniformly random point, the Born map must preserve uniform measure. (Scott likes this proof better because it is algorithmic, and because it is probabilistic.)

Now about quantum supremacy. You might think that a random chosen quantum circuit on $$n$$ qubits produces a nearly uniformly random quantum state $$|\psi\rangle$$ in their joint Hilbert space, but it’s not quite not that simple. When $$n=53$$, or otherwise as $$n \to \infty$$, a manageable random circuit is not nearly creative enough to either reach or approximate most of the unit states in the colossal Hilbert space of dimension $$d = 2^n$$. The state $$|\psi\rangle$$ that you get from (say) a polynomial-sized circuit resembles a fully random state in various statistical and computational respects, both proven and conjectured. As a result, if you measure the qubits in the computational basis, you get a randomized state on $$n$$ bits that resembles a uniformly random point in $$\Delta^{2^n-1}$$.

If you choose $$d$$ probabilities, and if each one is an independent exponential random variable, then the law of large numbers says that the sum (which you use for rescaling) is close to $$d$$ when $$d$$ is large. When $$d$$ is really big like $$2^{53}$$, a histogram of the probabilities of the bit strings of a supremacy experiment looks like an exponential curve $$f(p) \propto e^{-pd}$$. In a sense, the statistical distribution of the bit strings is almost the same almost every time, independent of which random quantum circuit you choose to generate them. The catch is that the position of any given bit string does depend on the circuit and is highly scrambled. I picture it in my mind like this:

It is thought to be computationally intractable to calculate where each bit string lands on this exponential curve, or even where just one of them does. (The exponential curve is attenuated by noise in the actual experiment, but it’s the same principle.) That is one reason that random quantum circuits are supreme.

### The Aaronson-Ambainis Conjecture (2008-2019)

Sunday, November 17th, 2019

Update: Sadly, Nathan Keller and Ohad Klein tell me that they’ve retracted their preprint, because of what currently looks like a fatal flaw in Lemma 5.3, uncovered by Paata Ivanishvili. I wish them the best of luck in fixing the problem. In the meantime, I’m leaving up this post for “historical” reasons.

Around 1999, one of the first things I ever did in quantum computing theory was to work on a problem that Fortnow and Rogers suggested in a paper: is it possible to separate P from BQP relative to a random oracle? (That is, without first needing to separate P from PSPACE or whatever in the real world?) Or to the contrary: suppose that a quantum algorithm Q makes T queries to a Boolean input string X. Is there then a classical simulation algorithm that makes poly(T) queries to X, and that approximates Q’s acceptance probability for most values of X? Such a classical simulation, were it possible, would still be consistent with the existence of quantum algorithms like Simon’s and Shor’s, which are able to achieve exponential (and even greater) speedups in the black-box setting. It would simply demonstrate the importance, for Simon’s and Shor’s algorithms, of global structure that makes the string X extremely non-random: for example, encoding a periodic function (in the case of Shor’s algorithm), or encoding a function that hides a secret string s (in the case of Simon’s). It would underscore that superpolynomial quantum speedups depend on structure.

I never managed to solve this problem. Around 2008, though, I noticed that a solution would follow from a perhaps-not-obviously-related conjecture, about influences in low-degree polynomials. Namely, let p:Rn→R be a degree-d real polynomial in n variables, and suppose p(x)∈[0,1] for all x∈{0,1}n. Define the variance of p to be
Var(p):=Ex,y[|p(x)-p(y)|],
and define the influence of the ith variable to be
Infi(p):=Ex[|p(x)-p(xi)|].
Here the expectations are over strings in {0,1}n, and xi means x with its ith bit flipped between 0 and 1. Then the conjecture is this: there must be some variable i such that Infi(p) ≥ poly(Var(p)/d) (in other words, that “explains” a non-negligible fraction of the variance of the entire polynomial).

Why would this conjecture imply the statement about quantum algorithms? Basically, because of the seminal result of Beals et al. from 1998: that if a quantum algorithm makes T queries to a Boolean input X, then its acceptance probability can be written as a real polynomial over the bits of X, of degree at most 2T. Given that result, if you wanted to classically simulate a quantum algorithm Q on most inputs—and if you only cared about query complexity, not computation time—you’d simply need to do the following:
(1) Find the polynomial p that represents Q’s acceptance probability.
(2) Find a variable i that explains at least a 1/poly(T) fraction of the total remaining variance in p, and query that i.
(3) Keep repeating step (2), until p has been restricted to a polynomial with not much variance left—i.e., to nearly a constant function p(X)=c. Whenever that happens, halt and output the constant c.
The key is that by hypothesis, this algorithm will halt, with high probability over X, after only poly(T) steps.

Anyway, around the same time, Andris Ambainis had a major break on a different problem that I’d told him about: namely, whether randomized and quantum query complexities are polynomially related for all partial functions with permutation symmetry (like the collision and the element distinctness functions). Andris and I decided to write up the two directions jointly. The result was our 2011 paper entitled The Need for Structure in Quantum Speedups.

Of the two contributions in the “Need for Structure” paper, the one about random oracles and influences in low-degree polynomials was clearly the weaker and less satisfying one. As the reviewers pointed out, that part of the paper didn’t solve anything: it just reduced one unsolved problem to a new, slightly different problem that was also unsolved. Nevertheless, that part of the paper acquired a life of its own over the ensuing decade, as the world’s experts in analysis of Boolean functions and polynomials began referring to the “Aaronson-Ambainis Conjecture.” Ryan O’Donnell, Guy Kindler, and many others had a stab. I even got Terry Tao to spend an hour or two on the problem when I visited UCLA.

Now, at long last, Nathan Keller and Ohad Klein say they’ve proven the Aaronson-Ambainis Conjecture, in a preprint whose title is a riff on ours: “Quantum Speedups Need Structure.”

Their paper hasn’t yet been peer-reviewed, and I haven’t yet carefully studied it, but I could and should: at 19 pages, it looks very approachable and clear, if not as radically short as (say) Huang’s proof of the Sensitivity Conjecture. Keller and Klein’s argument subsumes all the earlier results that I knew would need to be subsumed, and involves all the concepts (like a real analogue of block sensitivity) that I knew would need to be involved somehow.

My plan had been as follows:
(1) Read their paper in detail. Understand every step of their proof.
(2) Write a blog post that reflects my detailed understanding.

Unfortunately, this plan did not sufficiently grapple with the fact that I now have two kids. It got snagged for a week at step (1). So I’m now executing an alternative plan, which is to jump immediately to the blog post.

Assuming Keller and Klein’s result holds up—as I expect it will—by combining it with the observations in my and Andris’s paper, one immediately gets an explanation for why no one has managed to separate P from BQP relative to a random oracle, but only relative to non-random oracles. This complements the work of Kahn, Saks, and Smyth, who around 2000 gave a precisely analogous explanation for the difficulty of separating P from NP∩coNP relative to a random oracle.

Unfortunately, the polynomial blowup is quite enormous: from a quantum algorithm making T queries, Keller and Klein apparently get a classical algorithm making O(T18) queries. But such things can almost always be massively improved.

Feel free to use the comments to ask any questions about this result or its broader context. I’ll either do my best to answer from the limited amount I know, or else I’ll pass the questions along to Nathan and Ohad themselves. Maybe, at some point, I’ll even be forced to understand the new proof.

Congratulations to Nathan and Ohad!

Update (Nov. 20): Tonight I finally did what I should’ve done two weeks ago, and worked through the paper from start to finish. Modulo some facts about noise operators, hypercontractivity, etc. that I took on faith, I now have a reasonable (albeit imperfect) understanding of the proof. It’s great!

In case it’s helpful to anybody, here’s my one-paragraph summary of how it works. First, you hit your bounded degree-d function f with a random restriction to attenuate its higher-degree Fourier coefficients (reminiscent of Linial-Mansour-Nisan).  Next, in that attenuated function, you find a small “coalition” of influential variables—by which we mean, a set of variables for which there’s some assignment that substantially biases f.  You keep iterating—finding influential coalitions in subfunctions on n/4, n/8, etc. variables. All the while, you keep track of the norm of the vector of all the block-sensitivities of all the inputs (the authors don’t clearly explain this in the intro, but they reveal it near the end). Every time you find another influential coalition, that norm goes down by a little, but by approximation theory, it can only go down O(d2) times until it hits rock bottom and your function is nearly constant. By the end, you’ll have approximated f itself by a decision tree of depth poly(d, 1/ε, log(n)).  Finally, you get rid of the log(n) term by using the fact that f essentially depended on at most exp(O(d)) variables anyway.

Anyway, I’m not sure how helpful it is to write more: the paper itself is about 95% as clear as it could possibly be, and even where it isn’t, you’d probably need to read it first (and, uh, know something about influences, block sensitivity, random restrictions, etc.) before any further clarifying remarks would be of use. But happy to discuss more in the comments, if anyone else is reading it.