In the hour of darkness and peril and need

I recited the poem “Paul Revere’s Ride” to myself while walking across campus last week. 

A few hours earlier, I’d cancelled the seminar that I’d been slated to cohost two days later. In a few hours, I’d cancel the rest of the seminars in the series. Undergraduates would begin vacating their dorms within a day. Labs would shut down, and postdocs would receive instructions to work from home.

I memorized “Paul Revere’s Ride” after moving to Cambridge, following tradition: As a research assistant at Lancaster University in the UK, I memorized e. e. cummings’s “anyone lived in a pretty how town.” At Caltech, I memorized “Kubla Khan.” Another home called for another poem. “Paul Revere’s Ride” brooked no competition: Campus’s red bricks run into Boston, where Revere’s story began during the 1700s. 

Henry Wadsworth Longfellow, who lived a few blocks from Harvard, composed the poem. It centers on the British assault against the American colonies, at Lexington and Concord, on the eve of the Revolutionary War. A patriot learned of the British troops’ movements one night. He communicated the information to faraway colleagues by hanging lamps in a church’s belfry. His colleagues rode throughout the night, to “spread the alarm / through every Middlesex village and farm.” The riders included Paul Revere, a Boston silversmith.

The Boston-area bricks share their color with Harvard’s crest, crimson. So do the protrusions on the coronavirus’s surface in colored pictures. 

Screen Shot 2020-03-13 at 6.40.04 PM

I couldn’t have designed a virus to suit Harvard’s website better.

The yard that I was crossing was about to “de-densify,” the red-brick buildings were about to empty, and my home was about to lock its doors. I’d watch regulations multiply, emails keep pace, and masks appear. Revere’s messenger friend, too, stood back and observed his home:

he climbed to the tower of the church,
Up the wooden stairs, with stealthy tread,
To the belfry-chamber overhead, [ . . . ]
By the trembling ladder, steep and tall,
To the highest window in the wall,
Where he paused to listen and look down
A moment on the roofs of the town,
And the moonlight flowing over all.

I commiserated also with Revere, waiting on tenterhooks for his message:

Meanwhile, impatient to mount and ride,
Booted and spurred, with a heavy stride,
On the opposite shore walked Paul Revere.
Now he patted his horse’s side,
Now gazed on the landscape far and near,
Then impetuous stamped the earth,
And turned and tightened his saddle-girth…

The lamps ended the wait, and Revere rode off. His mission carried a sense of urgency, yet led him to serenity that I hadn’t expected:

He has left the village and mounted the steep,
And beneath him, tranquil and broad and deep,
Is the Mystic, meeting the ocean tides…

The poem’s final stanza kicks. Its message carries as much relevance to the 21st century as Longfellow, writing about the 1700s during the 1800s, could have dreamed:

So through the night rode Paul Revere;
And so through the night went his cry of alarm
To every Middlesex village and farm,—
A cry of defiance, and not of fear,
A voice in the darkness, a knock at the door,
And a word that shall echo forevermore!
For, borne on the night-wind of the Past,
Through all our history, to the last,
In the hour of darkness and peril and need,
The people will waken and listen to hear
The hurrying hoof-beats of that steed,
And the midnight message of Paul Revere.

Reciting poetry clears my head. I can recite on autopilot, while processing other information or admiring my surroundings. But the poem usually wins my attention at last. The rhythm and rhyme sweep me along, narrowing my focus. Reciting “Paul Revere’s Ride” takes me 5-10 minutes. After finishing that morning, I repeated the poem, and began repeating it again, until arriving at my institute on the edge of Harvard’s campus.

Isolation can benefit theorists. Many of us need quiet to study, capture proofs, and disentangle ideas. Many of us need collaboration; but email, Skype, Google hangouts, and Zoom connect us. Many of us share and gain ideas through travel; but I can forfeit a  little car sickness, air turbulence, and waiting in lines. Many of us need results from experimentalist collaborators, but experimental results often take long to gather in the absence of pandemics. Many of us are introverts who enjoy a little self-isolation.

 

April is National Poetry Month in the United States. I often celebrate by intertwining physics with poetry in my April blog post. Next month, though, I’ll have other news to report. Besides, my walk demonstrated, we need poetry now. 

Paul Revere found tranquility on the eve of a storm. Maybe, when the night clears and doors reopen, science born of the quiet will flood journals. Aren’t we fortunate, as physicists, to lead lives steeped in a kind of poetry?

The shape of MIP* = RE

There’s a famous parable about a group of blind men encountering an elephant for the very first time. The first blind man, who had his hand on the elephant’s side, said that it was like an enormous wall. The second blind man, wrapping his arms around the elephant’s leg, exclaimed that surely it was a gigantic tree trunk. The third, feeling the elephant’s tail, declared that it must be a thick rope. Vehement disagreement ensues, but after a while the blind men eventually come to realize that, while each person was partially correct, there is much more to the elephant than initially thought.

6-blind-men-hans-1024x6541-1

Last month, Zhengfeng, Anand, Thomas, John and I posted MIP* = RE to arXiv. The paper feels very much like the elephant of the fable — and not just because of the number of pages! To a computer scientist, the paper is ostensibly about the complexity of interactive proofs. To a quantum physicist, it is talking about mathematical models of quantum entanglement. To the mathematician, there is a claimed resolution to a long-standing problem in operator algebras. Like the blind men of the parable, each are feeling a small part of a new phenomenon. How do the wall, the tree trunk, and the rope all fit together?

I’ll try to trace the outline of the elephant: it starts with a mystery in quantum complexity theory, curves through the mathematical foundations of quantum mechanics, and arrives at a deep question about operator algebras.

The rope: The complexity of nonlocal games

In 2004, computer scientists Cleve, Hoyer, Toner, and Watrous were thinking about a funny thing called nonlocal games. A nonlocal game G involves three parties: two cooperating players named Alice and Bob, and someone called the verifier. The verifier samples a pair of random questions (x,y) and sends x to Alice (who responds with answer a), and y to Bob (who responds with answer b). The verifier then uses some function D(x,y,a,b) that tells her whether the players win, based on their questions and answers.

All three parties know the rules of the game before it starts, and Alice and Bob’s goal is to maximize their probability of winning the game. The players aren’t allowed to communicate with each other during the game, so it’s a nontrivial task for them to coordinate an optimal strategy (i.e., how they should individually respond to the verifier’s questions) before the game starts.

The most famous example of a nonlocal game is the CHSH game (which has made several appearances on this blog already): in this game, the verifier sends a uniformly random bit x to Alice (who responds with a bit a) and a uniformly random bit y to Bob (who responds with a bit b). The players win if a \oplus b = x \wedge y (in other words, the sum of their answer bits is equal to the product of the input bits modulo 2).

What is Alice’s and Bob’s maximum winning probability? Well, it depends on what type of strategy they use. If they use a strategy that can be modeled by classical physics, then their winning probability cannot exceed 75\% (we call this the classical value of CHSH). On the other hand, if they use a strategy based on quantum physics, Alice and Bob can do better by sharing two quantum bits (qubits) that are entangled. During the game each player measures their own qubit (where the measurement depends on their received question) to obtain answers that win the CHSH game with probability \cos^2(\pi/8) \approx .854\ldots (we call this the quantum value of CHSH). So even though the entangled qubits don’t allow Alice and Bob to communicate with each other, entanglement gives them a way to win with higher probability! In technical terms, their responses are more correlated than what is possible classically.

The CHSH game comes from physics, and was originally formulated not as a game involving Alice and Bob, but rather as an experiment involving two spatially separated devices to test whether stronger-than-classical correlations exist in nature. These experiments are known as Bell tests, named after John Bell. In 1964, he proved that correlations from quantum entanglement cannot be explained by any “local hidden variable theory” — in other words, a classical theory of physics.1 He then showed that a Bell test, like the CHSH game, gives a simple statistical test for the presence of nonlocal correlations between separated systems. Since the 1960s, numerous Bell tests have been conducted experimentally, and the verdict is clear: nature does not behave classically.

Cleve, Hoyer, Toner and Watrous noticed that nonlocal games/Bell tests can be viewed as a kind of multiprover interactive proof. In complexity theory, interactive proofs are protocols where some provers are trying to convince a verifier of a solution to a long, difficult computation, and the verifier is trying to efficiently determine if the solution is correct. In a Bell test, one can think of the provers as instead trying to convince the verifier of a physical statement: that they possess quantum entanglement.

With the computational lens trained firmly on nonlocal games, it then becomes natural to ask about their complexity. Specifically, what is the complexity of approximating the optimal winning probability in a given nonlocal game G? In complexity-speak, this is phrased as a question about characterizing the class MIP* (pronounced “M-I-P star”). This is also a well-motivated question for an experimentalist conducting Bell tests: at the very least, they’d want to determine if (a) quantum players can do better than classical players, and (b) what can the best possible quantum strategy achieve?

Studying this question in the case of classical players led to some of the most important results in complexity theory, such as MIP = NEXP and the PCP Theorem. Indeed, the PCP Theorem says that it is NP-hard to approximate the classical value of a nonlocal game (i.e. the maximum winning probability of classical players) to within constant additive accuracy (say \pm \frac{1}{10}). Thus, assuming that P is not equal to NP, we shouldn’t expect a polynomial-time algorithm for this. However it is easy to see that there is a “brute force” algorithm for this problem: by taking exponential time to enumerate over all possible deterministic player strategies, one can exactly compute the classical value of nonlocal games.

When considering games with entangled players, however, it’s not even clear if there’s a similar “brute force” algorithm that solves this in any amount of time — forget polynomial time; even if we allow ourselves exponential, doubly-exponential, Ackermann function amount of time, we still don’t know how to solve this quantum value approximation problem. The problem is that there is no known upper bound on the amount of entanglement that is needed for players to play a nonlocal game. For example, for a given game G, does an optimal quantum strategy require one qubit, ten qubits, or 10^{10^{10}} qubits of entanglement? Without any upper bound, a “brute force” algorithm wouldn’t know how big of a quantum strategy to search for — it would keep enumerating over bigger and bigger strategies in hopes of finding a better one.

Thus approximating the quantum value may not even be solvable in principle! But could it really be uncomputable? Perhaps we just haven’t found the right mathematical tool to give an upper bound on the dimension — maybe we just need to come up with some clever variant of, say, Johnson-Lindenstrauss or some other dimension reduction technique.2

In 2008, there was promising progress towards an algorithmic solution for this problem. Two papers [DLTW, NPA] (appearing on arXiv on the same day!) showed that an algorithm based on semidefinite programming can produce a sequence of numbers that converge to something called the commuting operator value of a nonlocal game.3 If one could show that the commuting operator value and the quantum value of a nonlocal game coincide, then this would yield an algorithm for solving this approximation problem!

Asking whether this commuting operator and quantum values are the same, however, immediately brings us to the precipice of some deep mysteries in mathematical physics and operator algebras, far removed from computer science and complexity theory. This takes us to the next part of the elephant.

The tree: mathematical foundations of locality

The mystery about the quantum value versus the commuting operator value of nonlocal games has to do with two different ways of modeling Alice and Bob in quantum mechanics. As I mentioned earlier, quantum physics predicts that the maximum winning probability in, say, the CHSH game when Alice and Bob share entanglement is approximately 85%. As with any physical theory, these predictions are made using some mathematical framework — formal rules for modeling physical experiments like the CHSH game.

In a typical quantum information theory textbook, players in the CHSH game are usually modelled in the following way: Alice’s device is described a state space \mathcal{H}_A (all the possible states the device could be in), a particular state |\psi_A\rangle from \mathcal{H}_A, and a set of measurement operators \mathcal{M}_A (operations that can be performed by the device). It’s not necessary to know what these things are formally; the important feature is that these three things are enough to make any prediction about Alice’s device — when treated in isolation, at least. Similarly, Bob’s device can be described using its own state space \mathcal{H}_B, state |\psi_B\rangle, and measurement operators \mathcal{M}_B.

In the CHSH game though, one wants to make predictions about Alice’s and Bob’s devices together. Here the textbooks say that Alice and Bob are jointly described by the tensor product formalism, which is a natural mathematical way of “putting separate spaces together”. Their state space is denoted by \mathcal{H}_A \otimes \mathcal{H}_B. The joint state |\psi_{AB}\rangle describing the devices comes from this tensor product space. When Alice and Bob independently make their local measurements, this is described by a measurement operator from the tensor product of operators from \mathcal{M}_A and \mathcal{M}_B. The strange correlations of quantum mechanics arise when their joint state |\psi_{AB}\rangle is entangled, i.e. it cannot be written as a well-defined state on Alice’s side combined with a well-defined state on Bob’s side (even though the state space itself is two independent spaces combined together!)

The tensor product model works well; it satisfies natural properties you’d want from the CHSH experiment, such as the constraint that Alice and Bob can’t instantaneously signal to each other. Furthermore, predictions made in this model match up very accurately with experimental results!

This is the not the whole story, though. The tensor product formalism works very well in non-relativistic quantum mechanics, where things move slowly and energies are low. To describe more extreme physical scenarios — like when particles are being smashed together at near-light speeds in the Large Hadron Collider — physicists turn to the more powerful quantum field theory. However, the notion of spatiotemporal separation in relativistic settings gets especially tricky. In particular, when trying to describe quantum mechanical systems, it is no longer evident how to assign Alice and Bob their own independent state spaces, and thus it’s not clear how to put relativistic Alice and Bob in the tensor product framework!

In quantum field theory, locality is instead described using the commuting operator model. Instead of assigning Alice and Bob their own individual state spaces and then tensoring them together to get a combined space, the commuting operator model stipulates that there is just a single monolithic space \mathcal{H} for both Alice and Bob. Their joint state is described using a vector |\psi\rangle from \mathcal{H}, and Alice and Bob’s measurement operators both act on \mathcal{H}. The constraint that they can’t communicate is captured by the fact that Alice’s measurement operators commute with Bob’s operators. In other words, the order in which the players perform their measurements on the system does not matter: Alice measuring before Bob, or Bob measuring before Alice, both yield the same statistical outcomes. Locality is enforced through commutativity.

The commuting operator framework contains the tensor product framework as a special case4, so it’s more general. Could the commuting operator model allow for correlations that can’t be captured by the tensor product model, even approximately56? This question is known as Tsirelson’s problem, named after the late mathematician Boris Tsirelson.

There is a simple but useful way to phrase this question using nonlocal games. What we call the “quantum value” of a nonlocal game G (denoted by \omega^* (G)) really refers to the supremum of success probabilities over tensor product strategies for Alice and Bob. If they use strategies from the more general commuting operator model, then we call their maximum success probability the commuting operator value of G (denoted by \omega^{co}(G)). Since tensor product strategies are a special case of commuting operator strategies, we have the relation \omega^* (G) \leq \omega^{co}(G) for all nonlocal games G.

Could there be a nonlocal game G whose tensor product value is different from its commuting operator value? With tongue-in-cheek: is there a game G that Alice and Bob could succeed at better if they were using quantum entanglement at near-light speeds? It is difficult to find even a plausible candidate game for which the quantum and commuting operator values may differ. The CHSH game, for example, has the same quantum and commuting operator value; this was proved by Tsirelson.

If the tensor product and the commuting operator models are the same (i.e., the “positive” resolution of Tsirelson’s problem), then as I mentioned earlier, this has unexpected ramifications: there would be an algorithm for approximating the quantum value of nonlocal games.

How does this algorithm work? It comes in two parts: a procedure to search from below, and one to search from above. The “search from below” algorithm computes a sequence of numbers \alpha_1,\alpha_2,\alpha_3,\ldots where \alpha_d is (approximately) the best winning probability when Alice and Bob use a d-qubit tensor product strategy. For fixed d, the number \alpha_d can be computed by enumerating over (a discretization of) the space of all possible d-qubit strategies. This takes a doubly-exponential amount of time in d — but at least this is still a finite time! This naive “brute force” algorithm will slowly plod along, computing a sequence of better and better winning probabilities. We’re guaranteed that in the limit as d goes to infinity, the sequence \{ \alpha_d\} converges to the quantum value \omega^* (G). Of course the issue is that the “search from below” procedure never knows how close it is to the true quantum value.

This is where the “search from above” comes in. This is an algorithm that computes a different sequence of numbers \beta_1,\beta_2,\beta_3,\ldots where each \beta_d is an upper bound on the commuting operator value \omega^{co}(G), and furthermore as d goes to infinity, \beta_d eventually converges to \omega^{co}(G). Furthermore, each \beta_d can be computed by a technique known as semidefinite optimization; this was shown by the two papers I mentioned.

Let’s put the pieces together. If the quantum and commuting operator values of a game G coincide (i.e. \omega^* (G) = \omega^{co}(G)), then we can run the “search from below” and “search from above” procedures in parallel, interleaving the computation of the \{\alpha_d\} and \{ \beta_d\}. Since both are guaranteed to converge to the quantum value, at some point the upper bound \beta_d will come within some \epsilon to the lower bound \alpha_d, and thus we would have homed in on (an approximation of) \omega^* (G). There we have it: an algorithm to approximate the quantum value of games.

All that remains to do, surely, is to solve Tsirelson’s problem in the affirmative (that commuting operator correlations can be approximated by tensor product correlations), and then we could put this pesky question about the quantum value to rest. Right?

The wall: Connes’ embedding problem

At the end of the 1920s, polymath extraordinaire John von Neumann formulated the first rigorous mathematical framework for the recently developed quantum mechanics. This framework, now familiar to physicists and quantum information theorists everywhere, posits that quantum states are vectors in a Hilbert space, and measurements are linear operators acting on those spaces. It didn’t take long for von Neumann to realize that there was a much deeper theory of operators on Hilbert spaces waiting to be discovered. With Francis Murray, in the 1930s he started to develop a theory of “rings of operators” — today these are called von Neumann algebras.

The theory of operator algebras has since flourished into a rich and beautiful area of mathematics. It remains inseparable from mathematical physics, but has established deep connections with subjects such as knot theory and group theory. One of the most important goals in operator algebras has been to provide a classification of von Neumann algebras. In their series of papers on the subject, Murray and von Neumann first showed that classifying von Neumann algebras reduces to understanding their factors, the atoms out of which all von Neumann algebras are built. Then, they showed that factors of von Neumann algebras come in one of three species: type I, type II, and type III. Type I factors were completely classified by Murray and von Neumann, and they made much progress on characterizing certain type II factors. However progress stalled until the 1970s, when Alain Connes provided a classification of type III factors (work for which he would later receive the Fields Medal). In the same 1976 classification paper, Connes makes a casual remark about something called type II_1 factors7:

We now construct an embedding of N into \mathcal{R}. Apparently such an embedding ought to exist for all II_1 factors.

This line, written in almost a throwaway manner, eventually came to be called “Connes’ embedding problem”: does every separable II_1 factor embed into an ultrapower of the hyperfinite II_1 factor? It seems that Connes surmises that it does (and thus this is also called “Connes’ embedding conjecture“). Since 1976, this problem has grown into a central question of operator algebras, with numerous equivalent formulations and consequences across mathematics.

In 2010, two papers (again appearing on the arXiv on the same day!) showed that the reach of Connes’ embedding conjecture extends back to the foundations of quantum mechanics. If Connes’ embedding problem has a positive answer (i.e. an embedding exists), then Tsirelson’s problem (i.e. whether commuting operator can be approximated by tensor product correlations) also has a positive answer! Later it was shown by Ozawa that Connes’ embedding problem is in fact equivalent to Tsirelson’s problem.

Remember that our approach to compute the value of nonlocal games hinged on obtaining a positive answer to Tsirelson’s problem. The sequence of papers [NPA, DLTW, Fritz, JNPPSW] together show that resolving — one way or another — whether this search-from-below, search-from-above algorithm works would essentially settle Connes’ embedding conjecture. What started as a funny question at the periphery of computer science and quantum information theory has morphed into an attack on one of the central problems in operator algebras.

MIP* = RE

We’ve now ended back where we started: the complexity of nonlocal games. Let’s take a step back and try to make sense of the elephant.

Even to a complexity theorist, “MIP* = RE” may appear esoteric. The complexity classes MIP* and RE refer to a bewildering grabbag of concepts: there’s Alice, Bob, Turing machines, verifiers, interactive proofs, quantum entanglement. What is the meaning of the equality of these two classes?

First, it says that the Halting problem has an interactive proof involving quantum entangled provers. In the Halting problem, you want to decide whether a Turing machine M, if you started running it, would eventually terminate with a well-defined answer, or if it would get stuck in an infinite loop. Alan Turing showed that this problem is undecidable: there is no algorithm that can solve this problem in general. Loosely speaking, the best thing you can do is to just flick on the power switch to M, and wait to see if it eventually stops. If M gets stuck in an infinite loop — well, you’re going to be waiting forever.

MIP* = RE shows with the help of all-powerful Alice and Bob, a time-limited verifier can run an interactive proof to “shortcut” the waiting. Given the Turing machine M‘s description (its “source code”), the verifier can efficiently compute a description of a nonlocal game G_M whose behavior reflects that of M. If M does eventually halt (which could happen after a million years), then there is a strategy for Alice and Bob that causes the verifier to accept with probability 1. In other words, \omega^* (G_M) = 1. If M gets stuck in an infinite loop, then no matter what strategy Alice and Bob use, the verifier always rejects with high probability, so \omega^* (G_M) is close to 0.

By playing this nonlocal game, the verifier can obtain statistical evidence that M is a Turing machine that eventually terminates. If the verifier plays G_M and the provers win, then the verifier should believe that it is likely that M halts. If they lose, then the verifier concludes there isn’t enough evidence that M halts8. The verifier never actually runs M in this game; she has offloaded the task to Alice and Bob, who we can assume are computational gods capable of performing million-year-long computations instantly. For them, the challenge is instead to convince the verifier that if she were to wait millions of years, she would witness the termination of M. Incredibly, the amount of work put in by the verifier in the interactive proof is independent of the time it takes for M to halt!

The fact that the Halting problem has an interactive proof seems borderline absurd: if the Halting problem is unsolvable, why should we expect it to be verifiable? Although complexity theory has taught us that there can be a large gap between the complexity of verification versus search, it has always been a difference of efficiency: if solutions to a problem can be efficiently verified, then solutions can also be found (albeit at drastically higher computational cost). MIP* = RE shows that, with quantum entanglement, there can be a chasm of computability between verifying solutions and finding them.

Now let’s turn to the non-complexity consequences of MIP* = RE. The fact that we can encode the Halting problem into nonlocal games also immediately tells us that there is no algorithm whatsoever to approximate the quantum value. Suppose there was an algorithm that could approximate \omega^* (G). Then, using the transformation from Turing machines to nonlocal games mentioned above, we could use this algorithm to solve the Halting problem, which is impossible.

Now the dominoes start to fall. This means that, in particular, the proposed “search-from-below”/”search-from-above” algorithm cannot succeed in approximating \omega^* (G). There must be a game G, then, for which the quantum value is different from the commuting operator value. But this implies Tsirelson’s problem has a negative answer, and therefore Connes’ embedding conjecture is false.

We’ve only sketched the barest of outlines of this elephant, and yet it is quite challenging to hold it in the mind’s eye all at once9. This story is intertwined with some of the most fundamental developments in the past century: modern quantum mechanics, operator algebras, and computability theory were birthed in the 1930s. Einstein, Podolsky and Rosen wrote their landmark paper questioning the nature of quantum entanglement in 1935, and John Bell discovered his famous test and inequality in 1964. Connes’ formulated his conjecture in the ’70s, Tsirelson made his contributions to the foundations of quantum mechanics in the ’80s, and about the same time computer scientists were inventing the theory of interactive proofs and probabilistically checkable proofs (PCPs).

We haven’t said anything about the proof of MIP* = RE yet (this may be the subject of future blog posts), but it is undeniably a product of complexity theory. The language of interactive proofs and Turing machines is not just convenient but necessary: at its heart MIP* = RE is the classical PCP Theorem, with the help of quantum entanglement, recursed to infinity.

What is going on in this proof? What parts of it are fundamental, and which parts are unnecessary? What is the core of it that relates to Connes’ embedding conjecture? Are there other consequences of this uncomputability result? These are questions to be explored in the coming days and months, and the answers we find will be fascinating.

Acknowledgments. Thanks to William Slofstra and Thomas Vidick for helpful feedback on this post.


  1. This is why quantum correlations are called “nonlocal”, and why we call the CHSH game a “nonlocal game”: it is a test for nonlocal behavior. 
  2. A reasonable hope would be that, for every nonlocal game G, there is a generic upper bound on the number of qubits needed to approximate the optimal quantum strategy (e.g., a game G with Q possible questions and A possible answers would require at most, say, 2^{O(Q \cdot A)} qubits to play optimally). 
  3. In those papers, they called it the field theoretic value
  4. The space \mathcal{H} can be broken down into the tensor product \mathcal{H}_A \otimes \mathcal{H}_B, and Alice’s measurements only act on the \mathcal{H}_A space and Bob’s measurements only act on the \mathcal{H}_B space. In this case, Alice’s measurements clearly commute with Bob’s. 
  5. In a breakthrough work in 2017, Slofstra showed that the tensor product framework is not exactly the same as the commuting operator framework; he shows that there is a nonlocal game G where players using commuting operator strategies can win with probability 1, but when they use a tensor-product strategy they can only win with probability strictly less than 1. However the perfect commuting operator strategy can be approximated by tensor-product strategies arbitrarily well, so the quantum values and the commuting operator values of G are the same. 
  6. The commuting operator model is motivated by attempts to develop a rigorous mathematical framework for quantum field theory from first principles (see, for example algebraic quantum field theory (AQFT)). In the “vanilla” version of AQFT, tensor product decompositions between casually independent systems do not exist a priori, but mathematical physicists often consider AQFTs augmented with an additional “split property”, which does imply tensor product decompositions. Thus in such AQFTs, Tsirelson’s problem has an affirmative answer. 
  7. Type II_1 is pronounced “type two one”. 
  8. This is not the same as evidence that M loops forever! 
  9. At least, speaking for myself. 

Sense, sensibility, and superconductors

Jonathan Monroe disagreed with his PhD supervisor—with respect. They needed to measure a superconducting qubit, a tiny circuit in which current can flow forever. The qubit emits light, which carries information about the qubit’s state. Jonathan and Kater intensify the light using an amplifier. They’d fabricated many amplifiers, but none had worked. Jonathan suggested changing their strategy—with a politeness to which Emily Post couldn’t have objected. Jonathan’s supervisor, Kater Murch, suggested repeating the protocol they’d performed many times.

“That’s the definition of insanity,” Kater admitted, “but I think experiment needs to involve some of that.”

I watched the exchange via Skype, with more interest than I’d have watched the Oscars with. Someday, I hope, I’ll be able to weigh in on such a debate, despite working as a theorist. Someday, I’ll have partnered with enough experimentalists to develop insight.

I’m partnering with Jonathan and Kater on an experiment that coauthors and I proposed in a paper blogged about here. The experiment centers on an uncertainty relation, an inequality of the sort immortalized by Werner Heisenberg in 1927. Uncertainty relations imply that, if you measure a quantum particle’s position, the particle’s momentum ceases to have a well-defined value. If you measure the momentum, the particle ceases to have a well-defined position. Our uncertainty relation involves weak measurements. Weakly measuring a particle’s position doesn’t disturb the momentum much and vice versa. We can interpret the uncertainty in information-processing terms, because we cast the inequality in terms of entropies. Entropies, described here, are functions that quantify how efficiently we can process information, such as by compressing data. Jonathan and Kater are checking our inequality, and exploring its implications, with a superconducting qubit.

With chip

I had too little experience to side with Jonathan or with Kater. So I watched, and I contemplated how their opinions would sound if expressed about theory. Do I try one strategy again and again, hoping to change my results without changing my approach? 

At the Perimeter Institute for Theoretical Physics, Masters students had to swallow half-a-year of course material in weeks. I questioned whether I’d ever understand some of the material. But some of that material resurfaced during my PhD. Again, I attended lectures about Einstein’s theory of general relativity. Again, I worked problems about observers in free-fall. Again, I calculated covariant derivatives. The material sank in. I decided never to question, again, whether I could understand a concept. I might not understand a concept today, or tomorrow, or next week. But if I dedicate enough time and effort, I chose to believe, I’ll learn.

My decision rested on experience and on classes, taught by educational psychologists, that I’d taken in college. I’d studied how brains change during learning and how breaks enhance the changes. Sense, I thought, underlay my decision—though expecting outcomes to change, while strategies remain static, sounds insane.

Old cover

Does sense underlie Kater’s suggestion, likened to insanity, to keep fabricating amplifiers as before? He’s expressed cynicism many times during our collaboration: Experiment needs to involve some insanity. The experiment probably won’t work for a long time. Plenty more things will likely break. 

Jonathan and I agree with him. Experiments have a reputation for breaking, and Kater has a reputation for knowing experiments. Yet Jonathan—with professionalism and politeness—remains optimistic that other methods will prevail, that we’ll meet our goals early. I hope that Jonathan remains optimistic, and I fancy that Kater hopes, too. He prophesies gloom with a quarter of a smile, and his record speaks against him: A few months ago, I met a theorist who’d collaborated with Kater years before. The theorist marveled at the speed with which Kater had operated. A theorist would propose an experiment, and boom—the proposal would work.

Sea monsters

Perhaps luck smiled upon the implementation. But luck dovetails with the sense that underlies Kater’s opinion: Experiments involve factors that you can’t control. Implement a protocol once, and it might fail because the temperature has risen too high. Implement the protocol again, and it might fail because a truck drove by your building, vibrating the tabletop. Implement the protocol again, and it might fail because you bumped into a knob. Implement the protocol a fourth time, and it might succeed. If you repeat a protocol many times, your environment might change, changing your results.

Sense underlies also Jonathan’s objections to Kater’s opinions. We boost our chances of succeeding if we keep trying. We derive energy to keep trying from creativity and optimism. So rebelling against our PhD supervisors’ sense is sensible. I wondered, watching the Skype conversation, whether Kater the student had objected to prophesies of doom as Jonathan did. Kater exudes the soberness of a tenured professor but the irreverence of a Californian who wears his hair slightly long and who tattooed his wedding band on. Science thrives on the soberness and the irreverence.

Green cover

Who won Jonathan and Kater’s argument? Both, I think. Last week, they reported having fabricated amplifiers that work. The lab followed a protocol similar to their old one, but with more conscientiousness. 

I’m looking forward to watching who wins the debate about how long the rest of the experiment takes. Either way, check out Jonathan’s talk about our experiment if you attend the American Physical Society’s March Meeting. Jonathan will speak on Thursday, March 5, at 12:03, in room 106. Also, keep an eye out for our paper—which will debut once Jonathan coaxes the amplifier into synching with his qubit.

Interaction + Entanglement = Efficient Proofs of Halting

A couple weeks ago my co-authors Zhengfeng Ji (UTS Sydney), Heny Yuen (University of Toronto) and Anand Natarajan and John Wright (both at Caltech’s IQIM, with John soon moving to UT Austin) & I posted a manuscript on the arXiv preprint server entitled

MIP*=RE

The magic of the single-letter formula quickly made its effect, and our posting received some attention on the blogosphere (see links below). Within computer science, complexity theory is at an advantage in its ability to capture powerful statements in few letters: who has not head of P, NP, and, for readers of this blog, BQP and QMA? (In contrast, I am under no illusion that my vague attempt at a more descriptive title has, by the time you reach this line, all but vanished from the reader’s memory.)

Even accounting for this popularity however, it is a safe bet that fewer of our readers have heard of MIP* or RE. Yet we are promised that the above-stated equality has great consequences for physics (“Tsirelson’s problem” in the study of nonlocality) and mathematics (“Connes’ embedding problem” in the theory of von Neumann algebras). How so — how can complexity-theoretic alphabet soup have any consequence for, on the one hand, physical reality, and on the other, abstract mathematics?

The goal of this post and the next one is to help the interested reader grasp the significance of interactive proofs (that lie between the symbols MIP*) and undecidability (that lies behind RE) for quantum mechanics.

The bulk of the present post is an almost identical copy of a post I wrote for my personal blog. To avoid accusations of self-plagiarism, I will substantiate it with a little picture and a story, see below. The post gives a very personal take on the research that led to the aforementioned result. In the next post, my co-author Henry Yuen has offered to give a more scientific introduction to the result and its significance.

Before proceeding, it is important to make it clear that the research described in this post and the next has not been refereed or thoroughly vetted by the community. This process will take place over the coming months, and we should wait until it is completed before placing too much weight on the results. As an author, I am proud of my work; yet I am aware that there is due process to be made before the claims can be officialised. As such, these posts only represent my opinion (and Henry’s) and not necessarily that of the wider scientific community.

For more popular introductions to our result, see the blog posts of Scott Aaronson, Dick Lipton, and Gil Kalai and reporting by Davide Castelvecchi for Nature and Emily Conover for Science.

Now for the personal post…and the promised picture. IMG_8074Isn’t it beautiful? The design is courtesy of Tony Metger and Alexandru Gheorghiu, the first a visiting student and the second a postdoctoral scholar at Caltech’s IQIM. While Tony and Andru came up with the idea, the execution is courtesy of the bakery store employee, who graciously implemented the custom design (apparently writing equations on top of cakes is not  common enough to be part of the standard offerings, so they had to go for the custom option). Although it is unclear if the executioner grasped the full depth of the signs they were copying, note how perfect the execution: not a single letter is out of place! Thanks to Tony, Andru, and the anonymous chef for the tasty souvenir.

Now for the story. In an earlier post on my personal research blog, I had reported on the beautiful recent result by Natarajan and Wright showing the astounding power of multi-prover interactive proofs with quantum provers sharing entanglement: in letters, \text{NEEXP} \subseteq \text{MIP}^\star. In the remainder of this post I will describe our follow-up work with Ji, Natarajan, Wright, and Yuen. In this post I will tell the story from a personal point of view, with all the caveats that this implies: the “hard science” will be limited (but there could be a hint as to how “science”, to use a big word, “progresses”, to use an ill-defined one; see also the upcoming post by Henry Yuen for more), the story is far too long, and it might be mostly of interest to me only. It’s a one-sided story, but that has to be. (In particular below I may at times attribute credit in the form “X had this idea”. This is my recollection only, and it is likely to be inaccurate. Certainly I am ignoring a lot of important threads.) I wrote this because I enjoyed recollecting some of the best moments in the story just as much as some the hardest; it is fun to look back and find meanings in ideas that initially appeared disconnected. Think of it as an example of how different lines of work can come together in unexpected ways; a case for open-ended research. It’s also an antidote against despair that I am preparing for myself: whenever I feel I’ve been stuck on a project for far too long, I’ll come back to this post and ask myself if it’s been 14 years yet — if not, then press on.

It likely comes as a surprise to me only that I am no longer fresh out of the cradle. My academic life started in earnest some 14 years ago, when in the Spring of 2006 I completed my Masters thesis in Computer Science under the supervision of Julia Kempe, at Orsay in France. I had met Julia the previous term: her class on quantum computing was, by far, the best-taught and most exciting course in the Masters program I was attending, and she had gotten me instantly hooked. Julia agreed to supervise my thesis, and suggested that I look into some interesting recent result by Stephanie Wehner that linked the study of entanglement and nonlocality in quantum mechanics to complexity-theoretic questions about interactive proof systems (specifically, this was Stephanie’s paper showing that \text{XOR-MIP}^\star \subseteq \text{QIP}(2)).

At the time the topic was very new. It had been initiated the previous year with a beautiful paper by Cleve et al. (that I have recommended to many a student since!) It was a perfect fit for me: the mathematical aspects of complexity theory and quantum computing connected to my undergraduate background, while the relative concreteness of quantum mechanics (it is a physical theory after all) spoke to my desire for real-world connection (not “impact” or even “application” — just “connection”). Once I got myself up to speed in the area (which consisted of three papers: the two I already mentioned, together with a paper by Kobayashi and Matsumoto where they studied interactive proofs with quantum messages), Julia suggested looking into the “entangled-prover” class \text{MIP}^\star introduced in the aforementioned paper by Cleve et al. Nothing was known about this class! Nothing besides the trivial inclusion of single-prover interactive proofs, IP, and the containment in…ALL, the trivial class that contains all languages.

Yet the characterization MIP=NEXP of its classical counterpart by Babai et al. in the 1990s had led to one of the most productive lines of work in complexity of the past few decades, through the PCP theorem and its use from hardness of approximation to efficient cryptographic schemes. Surely, studying \text{MIP}^\star had to be a productive direction? In spite of its well-established connection to classical complexity theory, via the formalism of interactive proofs, this was a real gamble. The study of entanglement from the complexity-theoretic perspective was entirely new, and bound to be fraught with difficulty; very few results were available and the existing lines of works, from the foundations of non-locality to more recent endeavors in device-independent cryptography, provided little other starting point than strong evidence that even the simplest examples came with many unanswered questions. But my mentor was fearless, and far from a novice in terms of defraying new areas, having done pioneering work in areas ranging from quantum random walks to Hamiltonian complexity through adiabatic computation. Surely this would lead to something?

It certainly did. More sleepless nights than papers, clearly, but then the opposite would only indicate dullness. Julia’s question led to far more unexpected consequences than I, or I believe she, could have imagined at the time. I am writing this post to celebrate, in a personal way, the latest step in 15 years of research by dozens of researchers: today my co-authors and I uploaded to the quant-ph arXiv what we consider a complete characterization of the power of entangled-prover interactive proof systems by proving the equality \text{MIP}^\star = \text{RE}, the class of all recursively enumerable languages (a complete problem for RE is the halting problem). Without going too much into the result itself (if you’re interested, look for an upcoming post here that goes into the proof a bit more), and since this is a more personal post, I will continue on with some personal thoughts about the path that got us there.

When Julia & I started working on the question, our main source of inspiration were the results by Cleve et al. showing that the non-local correlations of entanglement had interesting consequences when seen through the lens of interactive proof systems in complexity theory. Since the EPR paper, a lot of work in understanding entanglement had already been accomplished in the Physics community, most notably by Mermin, Peres, Bell, and more recently the works in device-independent quantum cryptography by Acin, Pironio, Scarani and many others, stimulated by Ekert’s proposal for quantum key distribution and Mayers and Yao’s idea for “device-independent cryptography”. By then we certainly knew that “spooky action-at-a-distance” did not entail any faster-than-light communication, and indeed was not really “action-at-a-distance” in the first place but merely “correlation-at-a-distance”. What Cleve et al. recognized is that these “spooky correlations-at-a-distance” were sufficiently special so as to not only give numerically different values in “Bell inequalities”, the tool invented by Bell to evidence non-locality in quantum mechanics, but also have some potentially profound consequences in complexity theory.

In particular, examples such as the “Magic Square game” demonstrated that enough correlation could be gained from entanglement so as to defeat basic proof systems whose soundness relied only on the absence of communication between the provers, an assumption that until then had been wrongly equated with the assumption that any computation performed by the provers could be modeled entirely locally. I think that the fallacy of this implicit assumption came as a surprise to complexity theorists, who may still not have entirely internalized it. Yet the perfect quantum strategy for the Magic Square game provides a very concrete “counter-example” to the soundness of the “clause-vs-variable” game for 3SAT. Indeed this game, a reformulation by Aravind and Cleve-Mermin of a Bell Inequality discovered by Mermin and Peres in 1990, can be easily re-framed as a 3SAT system of equations that is not satisfiable, and yet is such that the associated two-player clause-vs-variable game has a perfect quantum strategy. It is this observation, made in the paper by Cleve et al., that gave the first strong hint that the use of entanglement in interactive proof systems could make many classical results in the area go awry.

By importing the study of non-locality into complexity theory Cleve et al. immediately brought it into the realm of asymptotic analysis. Complexity theorists don’t study fixed objects, they study families of objects that tend to have a uniform underlying structure and whose interesting properties manifest themselves “in the limit”. As a result of this new perspective focus shifted from the study of single games or correlations to infinite families thereof. Some of the early successes of this translation include the “unbounded violations” that arose from translating asymptotic separations in communication complexity to the language of Bell inequalities and correlations (e.g. this paper). These early successes attracted the attention of some physicists working in foundations as well as some mathematical physicists, leading to a productive exploration that combined tools from quantum information, functional analysis and complexity theory.

The initial observations made by Cleve et al. had pointed to \text{MIP}^\star as a possibly interesting complexity class to study. Rather amazingly, nothing was known about it! They had shown that under strong restrictions on the verifier’s predicate (it should be an XOR of two answer bits), a collapse took place: by the work of Hastad, XOR-MIP equals NEXP, but \text{MIP}^\star is included in EXP. This seemed very fortuitous (the inclusion is proved via a connection with semidefinite programming that seems tied to the structure of XOR-MIP protocols): could entanglement induce a collapse of the entire, unrestricted class? We thought (at this point mostly Julia thought, because I had no clue) that this ought not to be the case, and so we set ourselves to show that the equality \text{MIP}^\star=\text{NEXP}, that would directly parallel Babai et al.’s characterization MIP=NEXP, holds. We tried to show this by introducing techniques to “immunize” games against entanglement: modify an interactive proof system so that its structure makes it “resistant” to the kind of “nonlocal powers” that can be used to defeat the clause-vs-variable game (witness the Magic Square). This was partially successful, and led to one of the papers I am most proud of — I am proud of it because I think it introduced elementary techniques (such as the use of the Cauchy-Schwarz inequality — inside joke — more seriously, basic things such as “prover-switching”, “commutation tests”, etc.) that are now routine manipulations in the area. The paper was a hard sell! It’s good to remember the first rejections we received. They were not unjustified: the main point of criticism was that we were only able to establish a hardness result for exponentially small completeness-soundness gap. A result for such a small gap in the classical setting follows directly from a very elementary analysis based on the Cook-Levin theorem. So then why did we have to write so many pages (and so many applications of Cauchy-Schwarz!) to arrive at basically the same result (with a ^\star)?

Eventually we got lucky and the paper was accepted to a conference. But the real problem, of establishing any non-trivial lower bound on the class \text{MIP}^\star with constant (or, in the absence of any parallel repetition theorem, inverse-polynomial) completeness-soundness gap, remained. By that time I had transitioned from a Masters student in France to a graduate student in Berkeley, and the problem (pre-)occupied me during some of the most difficult years of my Ph.D. I fully remember spending my first year entirely thinking about this (oh and sure, that systems class I had to pass to satisfy the Berkeley requirements), and then my second year — yet, getting nowhere. (I checked the arXiv to make sure I’m not making this up: two full years, no posts.) I am forever grateful to my fellow student Anindya De for having taken me out of the cycle of torture by knocking on my door with one of the most interesting questions I have studied, that led me into quantum cryptography and quickly resulted in an enjoyable paper. It was good to feel productive again! (Though the paper had fun reactions as well: after putting it on the arXiv we quickly heard from experts in the area that we had solved an irrelevant problem, and that we better learn about information theory — which we did, eventually leading to another paper, etc.) The project had distracted me and I set interactive proofs aside; clearly, I was stuck.

About a year later I visited IQC in Waterloo. I don’t remember in what context the visit took place. What I do remember is a meeting in the office of Tsuyoshi Ito, at the time a postdoctoral scholar at IQC. Tsuyoshi asked me to explain our result with Julia. He then asked a very pointed question: the bedrock for the classical analysis of interactive proof systems is the “linearity test” of Blum-Luby-Rubinfeld (BLR). Is there any sense in which we could devise a quantum version of that test?

What a question! This was great. At first it seemed fruitless: in what sense could one argue that quantum provers apply a “linear function”? Sure, quantum mechanics is linear, but that is besides the point. The linearity is a property of the prover’s answers as a function of their question. So what to make of the quantum state, the inherent randomness, etc.?

It took us a few months to figure it out. Once we got there however, the answer was relatively simple — the prover should be making a question-independent measurement that returns a linear function that it applies to its question in order to obtain the answer returned to the verifier — and it opened the path to our subsequent paper showing that the inclusion of NEXP in \text{MIP}^\star indeed holds. Tsuyoshi’s question about linearity testing had allowed us to make the connection with PCP techniques; from there to MIP=NEXP there was only one step to make, which is to analyze multi-linearity testing. That step was suggested by my Ph.D. advisor, Umesh Vazirani, who was well aware of the many pathways towards the classical PCP theorem, since the theorem had been obtained in great part by his former student Sanjeev Arora. It took a lot of technical work, yet conceptually a single question from my co-author had sufficed to take me out of a 3-year slumber.

This was in 2012, and I thought we were done. For some reason the converse inclusion, of \text{MIP}^\star in NEXP, seemed to resist our efforts, but surely it couldn’t resist much longer. Navascues et al. had introduced a hierarchy of semidefinite programs that seemed to give the right answer (technically they could only show convergence to a relaxation, the commuting value, but that seemed like a technicality; in particular, the values coincide when restricted to finite-dimensional strategies, which is all we computer scientists cared about). There were no convergence bounds on the hierarchy, yet at the same time commutative SDP hierarchies were being used to obtain very strong results in combinatorial optimization, and it seemed like it would only be a matter of time before someone came up with an analysis of the quantum case. (I had been trying to solve a related “dimension reduction problem” with Oded Regev for years, and we were making no progress; yet it seemed someone ought to!)

In Spring 2014 during an open questions session at a workshop at the Simons Institute in Berkeley Dorit Aharonov suggested that I ask the question of the possible inclusion of QMA-EXP, the exponential-sized-proofs analogue of QMA, in \text{MIP}^\star. A stronger result than the inclusion of NEXP (under assumptions), wouldn’t it be a more natural “fully quantum” analogue of MIP=NEXP? Dorit’s suggestion was motivated by research on the “quantum PCP theorem”, that aims to establish similar hardness results in the realm of the local Hamiltonian problem; see e.g. this post for the connection. I had no idea how to approach the question — I also didn’t really believe the answer could be positive — but what can you do, if Dorit asks you something… So I reluctantly went to the board and asked the question. Joe Fitzsimons was in the audience, and he immediately picked it up! Joe had the fantastic ideas of using quantum error-correction, or more specifically secret-sharing, to distribute a quantum proof among the provers. His enthusiasm overcame my skepticism, and we eventually showed the desired inclusion. Maybe \text{MIP}^\star was bigger than \text{NEXP} after all.

Our result, however, had a similar deficiency as the one with Julia, in that the completeness-soundness gap was exponentially small. Obtaining a result with a constant gap took 3 years of couple more years of work and the fantastic energy and insights of a Ph.D. student at MIT, Anand Natarajan. Anand is the first person I know of to have had the courage to dive into the most technical aspects of the analysis of the aforementioned results, while also bringing in the insights of a “true quantum information theorist” that were supported by Anand’s background in Physics and upbringing in the group of Aram Harrow at MIT. (In contrast I think of myself more as a “raw” mathematician; I don’t really understand quantum states other than as positive-semidefinite matrices…not that I understand math either of course; I suppose I’m some kind of a half-baked mish-mash.) Anand had many ideas but one of the most beautiful ones led to what he poetically called the “Pauli braiding test”, a “truly quantum” analogue of the BLR linearity test that amounts to doing two linearity tests in conjugate bases and piecing the results together into a robust test for {n}-qubit entanglement (I wrote about our work on this here).

At approximately the same time, Zhengfeng Ji had another wonderful idea that was in some sense orthogonal to our work. (My interpretation of) Zhengfeng’s idea is that one can see an interactive proof system as a computation (verifier-prover-verifier) and use Kitaev’s circuit-to-Hamiltonian construction to transform the entire computation into a “quantum CSP” (in the same sense that the local Hamiltonian problem is a quantum analogue of classical constraint satisfaction problems (CSP)) that could then itself be verified by a quantum multi-prover interactive proof system…with exponential gains in efficiency! Zhengfeng’s result implied an exponential improvement in complexity compared to the result by Julia and myself, showing inclusion of NEEXP, instead of NEXP, in \text{MIP}^\star. However, Zhengfeng’s technique suffered from the same exponentially small completeness-soundness gap as we had, so that the best lower bound on \text{MIP}^\star per se remained NEXP.

Both works led to follow-ups. With Natarajan we promoted the Pauli braiding test into a “quantum low-degree test” that allowed us to show the inclusion of QMA-EXP into \text{MIP}^\star, with constant gap, thereby finally answering the question posed by Aharonov 4 years after it was asked. (I should also say that by then all results on \text{MIP}^\star started relying on a sequence of parallel repetition results shown by Bavarian, Yuen, and others; I am skipping this part.) In parallel, with Ji, Fitzsimons, and Yuen we showed that Ji’s compression technique could be “iterated” an arbitrary number of times. In fact, by going back to “first principles” and representing verifiers uniformly as Turing machines we realized that the compression technique could be used iteratively to (up to small caveats) give a new proof of the fact (first shown by Slofstra using an embedding theorem for finitely presented group) that the zero-gap version of \text{MIP}^\star contains the halting problem. In particular, the entangled value is uncomputable! This was not the first time that uncomputability crops in to a natural problem in quantum computing (e.g. the spectral gap paper), yet it still surprises when it shows up. Uncomputable! How can anything be uncomputable!

As we were wrapping up our paper Henry Yuen realized that our “iterated compression of interactive proof systems” was likely optimal, in the following sense. Even a mild improvement of the technique, in the form of a slower closing of the completeness-soundness gap through compression, would yield a much stronger result: undecidability of the constant-gap class \text{MIP}^\star. It was already known by work of Navascues et al., Fritz, and others, that such a result would have, if not surprising, certainly consequences that seemed like they would be taking us out of our depth. In particular, undecidability of any language in \text{MIP}^\star would imply a negative resolution to a series of equivalent conjectures in functional analysis, from Tsirelson’s problem to Connes’ Embedding Conjecture through Kirchberg’s QWEP conjecture. While we liked our result, I don’t think that we believed it could resolve any conjecture(s) in functional analysis.

So we moved on. At least I moved on, I did some cryptography for a change. But Anand Natarajan and his co-author John Wright did not stop there. They had the last major insight in this story, which underlies their recent STOC best paper described in the previous post. Briefly, they were able to combine the two lines of work, by Natarajan & myself on low-degree testing and by Ji et al. on compression, to obtain a compression that is specially tailored to the existing \text{MIP}^\star protocol for NEXP and compresses that protocol without reducing its completeness-soundness gap. This then let them show Ji’s result that \text{MIP}^\star contains NEEXP, but this time with constant gap! The result received well-deserved attention. In particular, it is the first in this line of works to not suffer from any caveats (such as a closing gap, or randomized reductions, or some kind of “unfair” tweak on the model that one could attribute the gain in power to), and it implies an unconditional separation between MIP and \text{MIP}^\star.

As they were putting the last touches on their result, suddenly something happened, which is that a path towards a much bigger result opened up. What Natarajan & Wright had achieved is a one-step gapless compression. In our iterated compression paper we had observed that iterated gapless compression would lead to \text{MIP}^\star=\text{RE}, implying negative answers to the aforementioned conjectures. So then?

I suppose it took some more work, but in some way all the ideas had been laid out in the previous 15 years of work in the complexity of quantum interactive proof systems; we just had to put it together. And so a decade after the characterization QIP = PSPACE of single-prover quantum interactive proof systems, we have arrived at a characterization of quantum multiprover interactive proof systems, \text{MIP}^\star = \text{RE}. With one author in common between the two papers: congratulations Zhengfeng!

Even though we just posted a paper, in a sense there is much more left to do. I am hopeful that our complexity-theoretic result will attract enough interest from the mathematicians’ community, and especially operator algebraists, for whom CEP is a central problem, that some of them will be willing to devote time to understanding the result. I also recognize that much effort is needed on our own side to make it accessible in the first place! I don’t doubt that eventually complexity theory will not be needed to obtain the purely mathematical consequences; yet I am hopeful that some of the ideas may eventually find their way into the construction of interesting mathematical objects (such as, who knows, a non-hyperlinear group).

That was a good Masters project…thanks Julia!

On the merits of flatworm reproduction

On my right sat a quantum engineer. She was facing a melanoma specialist who works at a medical school. Leftward of us sat a networks expert, a flatworm enthusiast, and a condensed-matter theorist.

Farther down sat a woman who slices up mouse brains. 

Welcome to “Coherent Spins in Biology,” a conference that took place at the University of California, Los Angeles (UCLA) this past December. Two southern Californians organized the workshop: Clarice Aiello heads UCLA’s Quantum Biology Tech lab. Thorsten Ritz, of the University of California, Irvine, cofounded a branch of quantum biology.

Clarice logo

Quantum biology served as the conference’s backdrop. According to conventional wisdom, quantum phenomena can’t influence biology significantly: Biological systems have high temperatures, many particles, and fluids. Quantum phenomena, such as entanglement (a relationship that quantum particles can share), die quickly under such conditions.

Yet perhaps some survive. Quantum biologists search for biological systems that might use quantum resources. Then, they model and measure the uses and resources. Three settings (at least) have held out promise during the past few decades: avian navigation, photosynthesis, and olfaction. You can read about them in this book, cowritten by a conference participant for the general public. I’ll give you a taste (or a possibly quantum smell?) by sketching the avian-navigation proposal, developed by Thorsten and colleagues.

Bird + flower

Birds migrate southward during the autumn and northward during the spring. How do they know where to fly? At least partially by sensing the Earth’s magnetic field, which leads compass needles to point northward. How do birds sense the field?

Possibly with a protein called “cryptochrome.” A photon (a particle of light) could knock an electron out of part of the protein and into another part. Each part would have one electron that lacked a partner. The electrons would share entanglement. One electron would interact with the Earth’s magnetic field differently than its partner, because its surroundings would differ. (Experts: The electrons would form a radical pair. One electron would neighbor different atoms than the other, so the electron would experience a different local magnetic field. The discrepancy would change the relative phase between the electrons’ spins.) The discrepancy could affect the rate at which the chemical system could undergo certain reactions. Which reactions occur could snowball into large and larger effects, eventually signaling the brain about where the bird should fly.

Angry bird

Quantum mechanics and life rank amongst the universe’s mysteries. How could a young researcher resist the combination? A postdoc warned me away, one lunchtime at the start of my PhD. Quantum biology had enjoyed attention several years earlier, he said, but noise the obscured experimental data. Controversy marred the field.

I ate lunch with that postdoc in 2013. Interest in quantum biology is reviving, as evidenced in the conference. Two reasons suggested themselves: new technologies and new research avenues. For example, Thorsten described the disabling and deletion of genes that code for cryptochrome. Such studies require years’ more work but might illuminate whether cryptochrome affects navigation.

Open door

The keynote speaker, Harvard’s Misha Lukin, illustrated new technologies and new research avenues. Misha’s lab has diamonds that contain quantum defects, which serve as artificial atoms. The defects sense tiny magnetic fields and temperatures. Misha’s group applies these quantum sensors to biology problems.

For example, different cells in an embryo divide at different times. Imagine reversing the order in which the cells divide. Would the reversal harm the organism? You could find out by manipulating the temperatures in different parts of the embryo: Temperature controls the rate at which cells divide.

Misha’s team injected nanoscale diamonds into a worm embryo. (See this paper for a related study.) The diamonds reported the temperature at various points in the worm. This information guided experimentalists who heated the embryo with lasers.

The manipulated embryos grew into fairly normal adults. But their cells, and their descendants’ cells, cycled through the stages of life slowly. This study exemplified, to me, one of the most meaningful opportunities for quantum physicists interested in biology: to develop technologies and analyses that can answer biology questions.

Thermometer

I mentioned, in an earlier blog post, another avenue emerging in quantum biology: Physicist Matthew Fisher proposed a mechanism by which entanglement might enhance coordinated neuron firing. My collaborator Elizabeth Crosson and I analyzed how the molecules in Matthew’s proposal—Posner clusters—could process quantum information. The field of Posner quantum biology had a population of about two, when Elizabeth and I entered, and I wondered whether anyone would join us.

The conference helped resolve my uncertainty. Three speakers (including me) presented work based on Matthew’s; two other participants were tilling the Posner soil; and another speaker mentioned Matthew’s proposal. The other two Posner talks related data from three experiments. The experimentalists haven’t finished their papers, so I won’t share details. But stay tuned.

Posner 2

Posner molecule (image by Swift et al.)

Clarice and Thorsten’s conference reminded me of a conference I’d participated in at the end of my PhD: Last month, I moonlighted as a quantum biologist. In 2017, I moonlighted as a quantum-gravity theorist. Two years earlier, I’d been dreaming about black holes and space-time. At UCLA, I was finishing the first paper I’ve coauthored with biophysicists. What a toolkit quantum information theory and thermodynamics provide, that it can unite such disparate fields. 

The contrast—on top of what I learned at UCLA—filled my mind for weeks. And reminded me of the description of asexual reproduction that we heard from the conference’s flatworm enthusiast. According to Western Michigan University’s Wendy Beane, a flatworm “glues its butt down, pops its head off, and grows a new one. Y’know. As one does.” 

I hope I never flinch from popping my head off and growing a new one—on my quantum-information-thermodynamics spine—whenever new science calls for figuring out.

 

With thanks to Clarice, Thorsten, and UCLA for their invitation and hospitality.

An equation fit for a novel

Archana Kamal was hunting for an apartment in Cambridge, Massachusetts. She was moving MIT, to work as a postdoc in physics. The first apartment she toured had housed John Updike, during his undergraduate career at Harvard. No other apartment could compete; Archana signed the lease.

The apartment occupied the basement of a red-brick building covered in vines. The rooms spanned no more than 350 square feet. Yet her window opened onto the neighbors’ garden, whose leaves she tracked across the seasons. And Archana cohabited with history.

Apartment photos

She’s now studying the universe’s history, as an assistant professor of physics at the University of Massachusetts Lowell. The cosmic microwave background (CMB) pervades the universe. The CMB consists of electromagnetic radiation, or light. Light has particle-like properties and wavelike properties. The wavelike properties include wavelength, the distance between successive peaks. Long-wavelength light includes red light, infrared light, and radio waves. Short-wavelength light includes blue light, ultraviolet light, and X-rays. Light of one wavelength and light of another wavelength are said to belong to different modes.

Wavelength

Does the CMB have nonclassical properties, impossible to predict with classical physics but (perhaps) predictable with quantum theory? The CMB does according to the theory of inflation. According to the theory, during a short time interval after the Big Bang, the universe expanded very quickly: Spacetime stretched. Inflation explains features of our universe, though we don’t know what mechanism would have effected the expansion.

According to inflation, around the Big Bang time, all the light in the universe crowded together. The photons (particles of light) interacted, entangling (developing strong quantum correlations). Spacetime then expanded, and the photons separated. But they might retain entanglement.

Detecting that putative entanglement poses challenges. For instance, the particles that you’d need to measure could produce a signal too weak to observe. Cosmologists have been scratching their heads about how to observe nonclassicality in the CMB. One team—Nishant Agarwal at UMass Lowell and Sarah Shandera at Pennsylvania State University—turned to Archana for help.

A sky full of stars

Archana studies the theory of open quantum systems, quantum systems that interact with their environments. She thinks most about systems such as superconducting qubits, tiny circuits with which labs are building quantum computers. But the visible universe constitutes an open quantum system.

We can see only part of the universe—or, rather, only part of what we believe is the whole universe. Why? We can see only stuff that’s emitted light that has reached us, and light has had only so long to travel. But the visible universe interacts (we believe) with stuff we haven’t seen. For instance, according to the theory of inflation, that rapid expansion stretched some light modes’ wavelengths. Those wavelengths grew longer than the visible universe. We can’t see those modes’ peak-to-peak variations or otherwise observe the modes, often called “frozen.” But the frozen modes act as an environment that exchanges information and energy with the visible universe.

We describe an open quantum system’s evolution with a quantum master equation, which I blogged about four-and-a-half years ago. Archana and collaborators constructed a quantum master equation for the visible universe. The frozen modes, they found, retain memories of the visible universe. (Experts: the bath is non-Markovian.) Next, they need to solve the equation. Then, they’ll try to use their solution to identify quantum observables that could reveal nonclassicality in the CMB.

Frozen modes

Frozen modes

Archana’s project caught my fancy for two reasons. First, when I visited her in October, I was collaborating on a related project. My coauthors and I were concocting a scheme for detecting nonclassical correlations in many-particle systems by measuring large-scale properties. Our paper debuted last month. It might—with thought and a dash of craziness—be applied to detect nonclassicality in the CMB. Archana’s explanation improved my understanding of our scheme’s potential. 

Second, Archana and collaborators formulated a quantum master equation for the visible universe. A quantum master equation for the visible universe. The phrase sounded romantic to me.1 It merited a coauthor who’d seized on an apartment lived in by a Pulitzer Prize-winning novelist. 

Archana’s cosmology and Updike stories reminded me of one reason why I appreciate living in the Boston area: History envelops us here. Last month, while walking to a grocery, I found a sign that marks the building in which the poet e. e. cummings was born. My walking partner then generously tolerated a recitation of cummings’s “anyone lived in a pretty how town.” History enriches our lives—and some of it might contain entanglement.

 

1It might sound like gobbledygook to you, if I’ve botched my explanations of the terminology.

With thanks to Archana and the UMass Lowell Department of Physics and Applied Physics for their hospitality and seminar invitation.

Breaking up the band structure

Note from the editor: During the Summer of 2019, a group of thirteen undergraduate students from Caltech and universities around the world, spent 10 weeks on campus performing research in experimental quantum physics. Below, Aiden Cullo, a student from Binghampton University in New York, shares his experience working in Professor Yeh’s lab. The program, termed QuantumSURF, will run again during the Summer of 2020.

This summer, I worked in Nai-Chang Yeh’s experimental condensed matter lab. The aim of my project was to observe the effects of a magnetic field on our topological insulator (TI) sample, {(BiSb)}_2{Te}_3. The motivation behind this project was to examine more closely the transformation between a topological insulator and a state exhibiting the anomalous hall effect (AHE).

Both states of matter have garnered a good deal of interest in condensed matter research because of their interesting transport properties, among other things. TIs have gained popularity due to their applications in electronics (spintronics), superconductivity, and quantum computation. TIs are peculiar in that they simultaneously have insulating bulk states and conducting surface state. Due to time-reversal symmetry (TRS) and spin-momentum locking, these surface states have a very symmetric hourglass-like gapless energy band structure (Dirac cone).

The focus of our particular study was the effects of “c-plane” magnetization of our TI’s surface state. Theory predicts TRS and spin-momentum locking will be broken, resulting in a gapped spectrum with a single connection between the valence and conduction bands. This gapping has been theorized and shown experimentally in Chromium (Cr)-doped {(BiSb)}_2{Te}_3 and numerous other TIs with similar make-up.

In 2014, Nai-Chang Yeh’s group showed that Cr-doped {Bi}_2{Se}_3 exhibit this gap opening due to the surface state of {Bi}_2{Se}_3 interacting via the proximity effect with a ferromagnet. Our contention is that a similar material, Cr-doped {(BiSb)}_2{Te}_3, exhibits a similar effect, but more homogeneously because of reduced structural strain between atoms. Specifically, at temperatures below the Curie temperature (Tc), we expect to see a gap in the energy band and an overall increase in the gap magnitude. In short, the main goal of my summer project was to observe the gapping of our TI’s energy band.

Overall, my summer project entailed a combination of reading papers/textbooks and hands-on experimental work. It was difficult to understand fully the theory behind my project in such a short amount of time, but even with a cursory knowledge of topological insulators, I was able to provide a meaningful analysis/interpretation of our data.

Additionally, my experiment relied heavily on external factors such as our supplier for liquid helium, argon gas, etc. As a result, our progress was slowed if an order was delayed or not placed far enough in advance. Most of the issues we encountered were not related to the abstract theory of the materials/machinery, but rather problems with less complex mechanisms such as wiring, insulation, and temperature regulation.

While I expected to spend a good deal of time troubleshooting, I severely underestimated the amount of time that would be spent dealing with quotidian problems such as configuring software or etching STM tips. Working on a machine as powerful as an STM was frustrating at times, but also very rewarding as eventually we were able to collect a large amount of data on our samples.

An important (and extremely difficult) part of our analysis of STM data was whether patterns/features in our data set were artifacts or genuine phenomena, or a combination. I was fortunate enough to be surrounded by other researchers that helped me sift through the volumes of data and identify traits of our samples. Reflecting on my SURF, I believe it was a positive experience as it not only taught me a great deal about research, but also, more importantly, closely mimicked the experience of graduate school.

The paper that begged for a theme song

A year ago, the “I’m a little teapot” song kept playing in my head.

I was finishing a collaboration with David Limmer, a theoretical chemist at the University of California Berkeley. David studies quantum and classical systems far from equilibrium, including how these systems exchange energy and information with their environments. Example systems include photoisomers.

A photoisomer is a molecular switch. These switches appear across nature and technologies. We have photoisomers in our eyes, and experimentalists have used photoisomers to boost solar-fuel storage. A photoisomer has two functional groups, or collections of bonded atoms, attached to a central axis. 

Photoisomer

Your average-Joe photoisomer spends much of its life in equilibrium, exchanging heat with room-temperature surroundings. The molecule has the shape above, called the cis configuration. Imagine shining a laser or sunlight on the photoisomer. The molecule can absorb a photon, or particle of light, gaining energy. The energized switch has the opportunity to switch: One chemical group can rotate downward. The molecule will occupy its trans configuration.

Switch

The molecule now has more energy than it had while equilibrium, albeit less energy than it had right after absorbing the photon. The molecule can remain in this condition for a decent amount of time. (Experts: The molecule occupies a metastable state.) That is, the molecule can store sunlight. For that reason, experimentalists at Harvard and MIT attached photoisomers to graphene nanotubules, improving the nanotubules’ storage of solar fuel.

Teapot 1

With what probability does a photoisomer switch upon absorbing a photon? This question has resisted easy answering, because photoisomers prove difficult to model: They’re small, quantum, and far from equilibrium. People have progressed by making assumptions, but such assumptions can lack justifications or violate physical principles. David wanted to derive a simple, general bound—of the sort in which thermodynamicists specialize—on a photoisomer’s switching probability.

He had a hunch as to how he could derive such a bound. I’ve blogged, many times, about thermodynamic resource theories. Thermodynamic resource theories are simple models, developed in quantum information theory, for exchanges of heat, particles, information, and more. These models involve few assumptions: the conservation of energy, quantum theory, and, to some extent, the existence of a large environment (Markovianity). With such a model, David suspected, he might derive his bound.

Teapot 2

I knew nothing about photoisomers when I met David, but I knew about thermodynamic resource theories. I’d contributed to their development, to the theorems that have piled up in the resource-theory corner of quantum information theory. Then, the corner had given me claustrophobia. Those theorems felt so formal, abstract, and idealized. Formal, abstract theory has drawn me ever since I started studying physics in college. But did resource theories model physical reality? Could they impact science beyond our corner of quantum information theory? Did resource theories matter?

I called for connecting thermodynamic resource theories to physical reality four years ago, in a paper that begins with an embarrassing story about me. Resource theorists began designing experiments whose results should agree with our theorems. Theorists also tried to improve the accuracy with which resource theories model experimentalists’ limitations. See David’s and my paper for a list of these achievements. They delighted me, as a step toward the broadening of resource theories’ usefulness. 

Like any first step, this step pointed toward opportunities. Experiments designed to test our theorems essentially test quantum mechanics. Scientists have tested quantum mechanics for decades; we needn’t test it much more. Such experimental proposals can push experimentalists to hone their abilities, but I hoped that the community could accomplish more. We should be able to apply resource theories to answer questions cultivated in other fields, such as condensed matter and chemistry. We should be useful to scientists outside our corner of quantum information.

Teapot 3

David’s idea lit me up like photons on a solar-fuel-storage device. He taught me about photoisomers, I taught him about resource theories, and we derived his bound. Our proof relies on the “second laws of thermodynamics.” These abstract resource-theory results generalize the second law of thermodynamics, which helps us understand why time flows in only one direction. We checked our bound against numerical simulations (experts: of Lindbladian evolution). Our bound is fairly tight if the photoisomer has a low probability of absorbing a photon, as in the Harvard-MIT experiment. 

Experts: We also quantified the photoisomer’s coherences relative to the energy eigenbasis. Coherences can’t boost the switching probability, we concluded. But, en route to this conclusion, we found that the molecule is a natural realization of a quantum clock. Our quantum-clock modeling extends to general dissipative Landau-Zener transitions, prevalent across condensed matter and chemistry.

Teapot 4

As I worked on our paper one day, a jingle unfolded in my head. I recognized the tune first: “I’m a little teapot.” I hadn’t sung that much since kindergarten, I realized. Lyrics suggested themselves: 

I’m a little isomer
with two hands.
Here is my cis pose;
here is my trans.

Stand me in the sunlight;
watch me spin.
I’ll keep solar
energy in!

The song lodged itself in my head for weeks. But if you have to pay an earworm to collaborate with David, do.

Quantum Error Correction with Molecules

In the previous blog post (titled, “On the Coattails of Quantum Supremacy“) we started with Google and ended up with molecules! I also mentioned a recent paper by John Preskill, Jake Covey, and myself (see also this videoed talk) where we assume that, somewhere in the (near?) future, experimentalists will be able to construct quantum superpositions of several orientations of molecules or other rigid bodies. Next, I’d like to cover a few more details on how to construct error-correcting codes for anything from classical bits in your phone to those future quantum computers, molecular or otherwise.

Classical error correction: the basics

Error correction is concerned with the design of an encoding that allows for protection against noise. Let’s say we want to protect one classical bit, which is in either “0” or “1”. If the bit is say in “0”, and the environment (say, the strong magnetic field from a magnet you forgot was laying next to your hard drive) flipped it to “1” without our knowledge, an error would result (e.g., making your phone think you swiped right!)

Now let’s encode our single logical bit into three physical bits, whose 2^3=8 possible states are represented by the eight corners of the cube below. Let’s encode the logical bit as “0” —> 000 and “1” —> 111, corresponding to the corners of the cube marked by the black and white ball, respectively. For our (local) noise model, we assume that flips of only one of the three physical bits are more likely to occur than flips of two or three at the same time.

Error correction is, like many Hollywood movies, an origin story. If, say, the first bit flips in our above code, the 000 state is mapped to 100, and 111 is mapped to 011. Since we have assumed that the most likely error is a flip of one of the bits, we know upon observing that 100 must have come from the clean 000, and 011 from 111. Thus, in either case of the logical bit being “0” or “1”, we can recover the information by simply observing which state the majority of the bits are in. The same things happen when the second or third bits flip. In all three cases, the logical “0” state is mapped to one of its three neighboring points (above, in blue) while the logical “1” is mapped to its own three points, which, crucially, are distinct from the neighbors of “0”. The set of points \{000,100,010,001\} that are closer to 000 than to 111 is called a Voronoi tile.

Now, let’s adapt these ideas to molecules. Consider the rotational states of a dumb-bell molecule consisting of two different atoms. (Let’s assume that we have frozen this molecule to the point that the vibration of the inter-atomic bond is limited, essentially creating a fixed distance between the two atoms.) This molecule can orient itself in any direction, and each such orientation can be represented as a point \mathbf{v} on the surface of a sphere. Now let us encode a classical bit using the north and south poles of this sphere (represented in the picture below as a black and a white ball, respectively). The north pole of the sphere corresponds to the molecule being parallel to the z-axis, while the south pole corresponds to the molecule being anti-parallel.

This time, the noise consists of small shifts in the molecule’s orientation. Clearly, if such shifts are small, the molecule just wiggles a bit around the z-axis. Such wiggles still allow us to infer that the molecule is (mostly) parallel and anti-parallel to the axis, as long as they do not rotate the molecule all the way past the equator. Upon such correctable rotations, the logical “0” state — the north pole — is mapped to a point in the northern hemisphere, while logical “1” — the south pole — is mapped to a point in the southern hemisphere. The northern hemisphere forms a Voronoi tile of the logical “0” state (blue in the picture), which, along with the corresponding tile of the logical “1” state (the southern hemisphere), tiles the entire sphere.

Quantum error correction

To upgrade these ideas to the quantum realm, recall that this time we have to protect superpositions. This means that, in addition to shifting our quantum logical state to other states as before, noise can also affect the terms in the superposition itself. Namely, if, say, the superposition is equal — with an amplitude of +1/\sqrt{2} in “0” and +1/\sqrt{2} in “1” — noise can change the relative sign of the superposition and map one of the amplitudes to -1/\sqrt{2}. We didn’t have to worry about such sign errors before, because our classical information would always be the definite state of “0” or “1”. Now, there are two effects of noise to worry about, so our task has become twice as hard!

Not to worry though. In order to protect against both sources of noise, all we need to do is effectively stagger the above constructions. Now we will need to design a logical “0” state which is itself a superposition of different points, with each point separated from all of the points that are superimposed to make the logical “1” state.

Diatomic molecules: For the diatomic molecule example, consider superpositions of all four corners of two antipodal tetrahedra for the two respective logical states.

blog_tet

The logical “0” state for the quantum code is now itself a quantum superposition of orientations of our diatomic molecule corresponding to the four black points on the sphere to the left (the sphere to the right is a top-down view). Similarly, the logical “1” quantum state is a superposition of all orientations corresponding to the white points.

Each orientation (black or white point) present in our logical states rotates under fluctuations in the position of the molecule. However, the entire set of orientations for say logical “0” — the tetrahedron — rotates rigidly under such rotations. Therefore, the region from which we can successfully recover after rotations is fully determined by the Voronoi tile of any one of the corners of the tetrahedron. (Above, we plot the tile for the point at the north pole.) This cell is clearly smaller than the one for classical north-south-pole encoding we used before. However, the tetrahedral code now provides some protection against phase errors — the other type of noise that we need to worry about if we are to protect quantum information. This is an example of the trade-off we must make in order to protect against both types of noise; a licensed quantum mechanic has to live with such trade-offs every day.

Oscillators: Another example of a quantum encoding is the GKP encoding in the phase space of the harmonic oscillator. Here, we have at our disposal the entire two-dimensional plane indexing different values of position and momentum. In this case, we can use a checkerboard approach, superimposing all points at the centers of the black squares for the logical “0” state, and similarly all points at the centers of the white squares for the logical “1”. The region depicting correctable momentum and position shifts is then the Voronoi cell of the point at the origin: if a shift takes our central black point to somewhere inside the blue square, we know (most likely) where that point came from! In solid state circles, the blue square is none other than the primitive or unit cell of the lattice consisting of points making up both of the logical states.

Asymmetric molecules (a.k.a. rigid rotors): Now let’s briefly return to molecules. Above, we considered diatomic molecules that had a symmetry axis, i.e., that were left unchanged under rotations about the axis that connects the two atoms. There are of course more general molecules out there, including ones that are completely asymmetric under any possible (proper) 3D rotation (see figure below for an example).

mol-f0 - blog

BONUS: There is a subtle mistake relating to the geometry of the rotation group in the labeling of this figure. Let me know if you can find it in the comments!

All of the orientations of the asymmetric molecule, and more generally a rigid body, can no longer be parameterized by the sphere. They can be parameterized by the 3D rotation group \mathsf{SO}(3): each orientation of an asymmetric molecule is labeled by the 3D rotation necessary to obtain said orientation from a reference state. Such rotations, and in turn the orientations themselves, are parameterized by an axis \mathbf{v} (around which to rotate) and an angle \omega (by which one rotates). The rotation group \mathsf{SO}(3) luckily can still be viewed by humans on a sheet of paper. Namely, \mathsf{SO}(3) can be thought of as a ball of radius \pi with opposite points identified. The direction of each vector \omega\mathbf{v} lying inside the ball corresponds to the axis of rotation, while the length corresponds to the angle. This may take some time to digest, but it’s not crucial to the story.

So far we’ve looked at codes defined on cubes of bits, spheres, and phase-space lattices. Turns out that even \mathsf{SO}(3) can house similar encodings! In other words, \mathsf{SO}(3) can also be cut up into different Voronoi tiles, which in turn can be staggered to create logical “0” and “1” states consisting of different molecular orientations. There are many ways to pick such states, corresponding to various subgroups of \mathsf{SO}(3). Below, we sketch two sets of black/white points, along with the Voronoi tile corresponding to the rotations that are corrected by each encoding.

Voronoi tiles of the black point at the center of the ball representing the 3D rotation group, for two different molecular codes. This and the Voronoi cells corresponding to the other points tile together to make up the entire ball. 3D printing all of these tiles would make for cool puzzles!

In closing…

Achieving supremacy was a big first step towards making quantum computing a practical and universal tool. However, the largest obstacles still await, namely handling superposition-poisoning noise coming from the ever-curious environment. As quantum technologies advance, other possible routes for error correction are by encoding qubits in harmonic oscillators and molecules, alongside the “traditional” approach of using arrays of physical qubits. Oscillator and molecular qubits possess their own mechanisms for error correction, and could prove useful (granted that the large high-energy space required for the procedures to work can be accessed and controlled). Even though molecular qubits are not yet mature enough to be used in quantum computers, we have at least outlined a blueprint for how some of the required pieces can be built. We are by no means done however: besides an engineering barrier, we need to further develop how to run robust computations on these exotic spaces.

Author’s note: I’d like to acknowledge Jose Gonzalez for helping me immensely with the writing of this post, as well as for drawing the comic panels in the previous post. The figures above were made possible by Mathematica 12.

On the Coattails of Quantum Supremacy

Most readers have by now heard that Google has “achieved” quantum “supremacy”. Notice the only word not in quotes is “quantum”, because unlike previous proposals that have also made some waves, quantumness is mostly not under review here. (Well, neither really are the other two words, but that story has already been covered quite eloquently by John, Scott, and Toby.) The Google team has managed to engineer a device that, although noisy, can do the right thing a large-enough fraction of the time for people to be able to “quantify its quantumness”.

However, the Google device, while less so than previous incarnations, is still noisy. Future devices like it will continue to be noisy. Noise is what makes quantum computers so darn difficult to build; it is what destroys the fragile quantum superpositions that we are trying so hard to protect (remember, unlike a classical computer, we are not protecting things we actually observe, but their superposition).

Protecting quantum information is like taking your home-schooled date (who has lived their entire life in a bunker) to the prom for the first time. It is a fun and necessary part of a healthy relationship to spend time in public, but the price you pay is the possibility that your date will hit it off with someone else. This will leave you abandoned, dancing alone to Taylor Swift’s “You Belong With Me” while crying into your (spiked?) punch.

When the environment corrupts your quantum date.

The high school sweetheart/would-be dance partner in the above provocative example is the quantum superposition — the resource we need for a working quantum computer. You want it all to yourself, but your adversary — the environment — wants it too. No matter how much you try to protect it, you’ll have to observe it eventually (after all, you want to know the answer to your computation). And when you do (take your date out onto the crowded dance floor), you run the risk of the environment collapsing the information before you do, leaving you with nothing.

Protecting quantum information is also like (modern!) medicine. The fussy patient is the quantum information, stored in delicate superposition, while quantumists are the doctors aiming to prevent the patient from getting sick (or “corrupted”). If our patient incurs say “quasiparticle poisoning”, we first diagnose the patient’s syndromes, and, based on this diagnosis, apply procedures like “lattice surgery” and “state injection” to help our patient successfully recover.

The medical analogy to QEC, noticed first by Daniel Litinski. All terms are actually used in papers. Cartoon by Jose Gonzalez.

Error correction with qubits

Error correction sounds hard, and it should! Not to fear: plenty of very smart people have thought hard about this problem, and have come up with a plan — to redundantly encode the quantum superposition in a way that allows protection from errors caused by noise. Such quantum error-correction is an expansion of the techniques we currently use to protect classical bits in your phone and computer, but now the aim is to protect, not the definitive bit states 0 or 1, but their quantum superpositions. Things are even harder now, as the protection machinery has to do its magic without disturbing the superposition itself (after all, we want our quantum calculation to run to its conclusion and hack your bank).

For example, consider a qubit — the fundamental quantum unit represented by two shelves (which, e.g., could be the ground and excited states of an atom, the absence or presence of a photon in a box, or the zeroth and first quanta of a really cold LC circuit). This qubit can be in any quantum superposition of the two shelves, described by 2 probability amplitudes, one corresponding to each shelf. Observing this qubit will collapse its state onto either one of the shelves, changing the values of the 2 amplitudes. Since the resource we use for our computation is precisely this superposition, we definitely do not want to observe this qubit during our computation. However, we are not the only ones looking: the environment (other people at the prom: the trapping potential of our atom, the jiggling atoms of our metal box, nearby circuit elements) is also observing this system, thereby potentially manipulating the stored quantum state without our knowledge and ruining our computation.

Now consider 50 such qubits. Such a space allows for a superposition with 2^{50} different amplitudes (instead of just 2^1 for the case of a single qubit). We are once again plagued by noise coming from the environment. But what if we now, less ambitiously, want to store only one qubit’s worth of information in this 50-qubit system? Now there is room to play with! A clever choice of how to do this (a.k.a. the encoding) helps protect from the bad environment. 

The entire prospect of building a bona-fide quantum computer rests on this extra overhead or quantum redundancy of using a larger system to encode a smaller one. It sounds daunting at first: if we need 50 physical qubits for each robust logical qubit, then we’d need “I-love-you-3000” physical qubits for 60 logical ones? Yes, this is a fact we all have to live with. But granted we can scale up our devices to that many qubits, there is no fundamental obstacle that prevents us from then using error correction to make next-level computers.

To what extent do we need to protect our quantum superposition from the environment? It would be too ambitious to protect it from a meteor shower. Or a power outage (although that would be quite useful here in California). So what then can we protect against?

Our working answer is local noise — noise that affects only a few qubits that are located near each other in the device. We can never be truly certain if this type of noise is all that our quantum computers will encounter. However, our belief that this is the noise we should focus on is grounded in solid physical principles — that nature respects locality, that affecting things far away from you is harder than making an impact nearby. (So far Google has not reported otherwise, although much more work needs to be done to verify this intuition.)

The harmonic oscillator

In what other ways can we embed our two-shelf qubit into a larger space? Instead of scaling up using many physical qubits, we can utilize a fact that we have so far swept under the rug: in any physical system, our two shelves are already part of an entire bookcase! Atoms have more than one excited state, there can be more than one photon in a box, and there can be more than one quantum in a cold LC circuit. Why don’t we use some of that higher-energy space for our redundant encoding?

The noise in our bookcase will certainly be different, since the structure of the space, and therefore the notion of locality, is different. How to cope with this? The good news is that such a space — the space of the harmonic oscillator — also has a(t least one) natural notion of locality!

Whatever the incarnation, the oscillator has associated with it a position and momentum (different jargon for these quantities may be used, depending on the context, but you can just think of a child on a swing, just quantized). Anyone who knows the joke about Heisenberg getting pulled over, will know that these two quantities cannot be set simultaneously.

Cartoon by Jose Gonzalez.

Nevertheless, local errors can be thought of as small shifts in position or momentum, while nonlocal errors are ones that suddenly shift our bewildered swinging quantized child from one side of the swing to the other.

Armed with a local noise model, we can extend our know-how from multi-qubit land to the oscillator. One of the first such oscillator codes were developed by Gottesman, Kitaev, and Preskill (GKP). Proposed in 2001, GKP encodings posed a difficult engineering challenge: some believed that GKP states could never be realized, that they “did not exist”. In the past few years however, GKP states have been realized nearly simultaneously in two experimental platforms. (Food for thought for the non-believers!)

Parallel to GKP codes, another promising oscillator encoding using cat states is also being developed. This encoding has historically been far easier to create experimentally. It is so far the only experimental procedure achieving the break-even point, at which the actively protected logical information has the same lifetime as the system’s best unprotected degree of freedom.

Can we mix and match all of these different systems? Why yes! While Google is currently trying to build the surface code out of qubits, using oscillators (instead of qubits) for the surface code and encoding said oscillators either in GKP (see related IBM post) [1,2,3] or cat [4,5] codes is something people are seriously considering. There is even more overhead, but the extra information one gets from the correction procedure might make for a more fault-tolerant machine. With all of these different options being explored, it’s an exciting time to be into quantum!

Molecules?

It turns out there are still other systems we can consider, although because they are sufficiently more “out there” at the moment, I should first say “bear with me!” as I explain. Forget about atoms, photons in a box, and really cold LC circuits. Instead, consider a rigid 3-dimensional object whose center of mass has been pinned in such a way that the object can rotate any way it wants. Now, “quantize” it! In other words, consider the possibility of having quantum superpositions of different orientations of this object. Just like superpositions of a dead and alive cat, of a photon and no photon, the object can be in quantum superposition of oriented up, sideways, and down, for example. Superpositions of all possible orientations then make up our new configuration space (read: playground), and we are lucky that it too inherits many of the properties we know and love from its multi-qubit and oscillator cousins.

Examples of rigid bodies include airplanes (which can roll, pitch and yaw, even while “fixed” on a particular trajectory vector) and robot arms (which can rotate about multiple joints). Given that we’re not quantizing those (yet?), what rigid body should we have in mind as a serious candidate? Well, in parallel to the impressive engineering successes of the multi-qubit and oscillator paradigms, physicists and chemists have made substantial progress in trapping and cooling molecules. If a trapped molecule is cold enough, it’s vibrational and electronic states can be neglected, and its rotational states form exactly the rigid body we are interested in. Such rotational states, as far as we can tell, are not in the realm of Avengers-style science fiction.

Superpositions of molecular orientations don’t violate the Deutsch proposition.

The idea to use molecules for quantum computing dates all the way back to a 2001 paper by Dave DeMille, but in a recent paper by Jacob Covey, John Preskill, and myself, we propose a framework of how to utilize the large space of molecular orientations to protect against (you guessed it!) a type of local noise. In the second part of the story, called “Quantum Error Correction with Molecules“, I will cover a particular concept that is not only useful for a proper error-correcting code (classical and quantum), but also one that is quite fun to try and understand. The concept is based on a certain kind of tiling, called Voronoi tiles or Thiessen polygons, which can be used to tile anything from your bathroom floor to the space of molecular orientations. Stay tuned!