Congratulations to James Peebles, Michel Mayor, and Didier Queloz!

The 2019 Physics Nobel Prize was announced this week, awarded to James Peebles for work in cosmology and to Michel Mayor and Didier Queloz for the first observation of an exoplanet.

Peebles introduced quantitative methods to cosmology. He figured out how to use the Cosmic Microwave Background (light left over from the Big Bang) to understand how matter is distributed in our universe, including the presence of still-mysterious dark matter and dark energy. Mayor and Queloz were the first team to observe a planet outside of our solar system (an “exoplanet”), in 1995. By careful measurement of the spectrum of light coming from a star they were able to find a slight wobble, caused by a Jupiter-esque planet in orbit around it. Their discovery opened the floodgates of observation. Astronomers found many more planets than expected, showing that, far from a rare occurrence, exoplanets are quite common.

It’s a bit strange that this Nobel was awarded to two very different types of research. This isn’t the first time the prize was divided between two different discoveries, but all of the cases I can remember involve discoveries in closely related topics. This one didn’t, and I’m curious about the Nobel committee’s logic. It might have been that neither discovery “merited a Nobel” on its own, but I don’t think we’re supposed to think of shared Nobels as “lesser” than non-shared ones. It would make sense if the Nobel committee thought they had a lot of important results to “get through” and grouped them together to get through them faster, but if anything I have the impression it’s the opposite: that at least in physics, it’s getting harder and harder to find genuinely important discoveries that haven’t been acknowledged. Overall, this seems like a very weird pairing, and the Nobel committee’s citation “for contributions to our understanding of the evolution of the universe and Earth’s place in the cosmos” is a pretty loose justification.

Calabi-Yaus in Feynman Diagrams: Harder and Easier Than Expected

I’ve got a new paper up, about the weird geometrical spaces we keep finding in Feynman diagrams.

With Jacob Bourjaily, Andrew McLeod, and Matthias Wilhelm, and most recently Cristian Vergu and Matthias Volk, I’ve been digging up odd mathematics in particle physics calculations. In several calculations, we’ve found that we need a type of space called a Calabi-Yau manifold. These spaces are often studied by string theorists, who hope they represent how “extra” dimensions of space are curled up. String theorists have found an absurdly large number of Calabi-Yau manifolds, so many that some are trying to sift through them with machine learning. We wanted to know if our situation was quite that ridiculous: how many Calabi-Yaus do we really need?

So we started asking around, trying to figure out how to classify our catch of Calabi-Yaus. And mostly, we just got confused.

It turns out there are a lot of different tools out there for understanding Calabi-Yaus, and most of them aren’t all that useful for what we’re doing. We went in circles for a while trying to understand how to desingularize toric varieties, and other things that will sound like gibberish to most of you. In the end, though, we noticed one small thing that made our lives a whole lot simpler.

It turns out that all of the Calabi-Yaus we’ve found are, in some sense, the same. While the details of the physics varies, the overall “space” is the same in each case. It’s a space we kept finding for our “Calabi-Yau bestiary”, but it turns out one of the “traintrack” diagrams we found earlier can be written in the same way. We found another example too, a “wheel” that seems to be the same type of Calabi-Yau.

And that actually has a sensible name

We also found many examples that we don’t understand. Add another rung to our “traintrack” and we suddenly can’t write it in the same space. (Personally, I’m quite confused about this one.) Add another spoke to our wheel and we confuse ourselves in a different way.

So while our calculation turned out simpler than expected, we don’t think this is the full story. Our Calabi-Yaus might live in “the same space”, but there are also physics-related differences between them, and these we still don’t understand.

At some point, our abstract included the phrase “this paper raises more questions than it answers”. It doesn’t say that now, but it’s still true. We wrote this paper because, after getting very confused, we ended up able to say a few new things that hadn’t been said before. But the questions we raise are if anything more important. We want to inspire new interest in this field, toss out new examples, and get people thinking harder about the geometry of Feynman integrals.

Facts About Our Capabilities Are Facts About the World

A paper leaked from Google last week claimed that their researchers had achieved “quantum supremacy”, the milestone at which a quantum computer performs a calculation faster than any existing classical computer. Scott Aaronson has a great explainer about this. The upshot is that Google’s computer is much too small to crack all our encryptions (only 53 qubits, the equivalent of bits for quantum computers), but it still appears to be a genuine quantum computer doing a genuine quantum computation that is genuinely not feasible otherwise.

How impressed should we be about this?

On one hand, the practical benefits of a 53-qubit computer are pretty minimal. Scott discusses some applications: you can generate random numbers, distributed in a way that will let others verify that they are truly random, the kind of thing it’s occasionally handy to do in cryptography. Still, by itself this won’t change the world, and compared to the quantum computing hype I can understand if people find this underwhelming.

On the other hand, as Scott says, this falsifies the Extended Church-Turing Thesis! And that sounds pretty impressive, right?

Ok, I’m actually just re-phrasing what I said before. The Extended Church-Turing Thesis proposes that a classical computer (more specifically, a probabilistic Turing machine) can efficiently simulate any reasonable computation. Falsifying it means finding something that a classical computer cannot compute efficiently but another sort of computer (say, a quantum computer) can. If the calculation Google did truly can’t be done efficiently on a classical computer (this is not proven, though experts seem to expect it to be true) then yes, that’s what Google claims to have done.

So we get back to the real question: should we be impressed by quantum supremacy?

Well, should we have been impressed by the Higgs?

The detection of the Higgs boson in 2012 hasn’t led to any new Higgs-based technology. No-one expected it to. It did teach us something about the world: that the Higgs boson exists, and that it has a particular mass. I think most people accept that that’s important: that it’s worth knowing how the world works on a fundamental level.

Google may have detected the first-known violation of the Extended Church-Turing Thesis. This could eventually lead to some revolutionary technology. For now, though, it hasn’t. Instead, it teaches us something about the world.

It may not seem like it, at first. Unlike the Higgs boson, “Extended Church-Turing is false” isn’t a law of physics. Instead, it’s a fact about our capabilities. It’s a statement about the kinds of computers we can and cannot build, about the kinds of algorithms we can and cannot implement, the calculations we can and cannot do.

Facts about our capabilities are still facts about the world. They’re still worth knowing, for the same reasons that facts about the world are still worth knowing. They still give us a clearer picture of how the world works, which tells us in turn what we can and cannot do. According to the leaked paper, Google has taught us a new fact about the world, a deep fact about our capabilities. If that’s true we should be impressed, even without new technology.

The Changing Meaning of “Explain”

This is another “explanations are weird” post.

I’ve been reading a biography of James Clerk Maxwell, who formulated the theory of electromagnetism. Nowadays, we think about the theory in terms of fields: we think there is an “electromagnetic field”, filling space and time. At the time, though, this was a very unusual way to think, and not even Maxwell was comfortable with it. He felt that he had to present a “physical model” to justify the theory: a picture of tiny gears and ball bearings, somehow occupying the same space as ordinary matter.

Bang! Bang! Maxwell’s silver bearings…

Maxwell didn’t think space was literally filled with ball bearings. He did, however, believe he needed a picture that was sufficiently “physical”, that wasn’t just “mathematics”. Later, when he wrote down a theory that looked more like modern field theory, he still thought of it as provisional: a way to use Lagrange’s mathematics to ignore the unknown “real physical mechanism” and just describe what was observed. To Maxwell, field theory was a description, but not an explanation.

This attitude surprised me. I would have thought physicists in Maxwell’s day could have accepted fields. After all, they had accepted Newton.

In his time, there was quite a bit of controversy about whether Newton’s theory of gravity was “physical”. When rival models described planets driven around by whirlpools, Newton simply described the mathematics of the force, an “action at a distance”. Newton famously insisted hypotheses non fingo, “I feign no hypotheses”, and insisted that he wasn’t saying anything about why gravity worked, merely how it worked. Over time, as the whirlpool models continued to fail, people gradually accepted that gravity could be explained as action at a distance.

You’d think that this would make them able to accept fields as well. Instead, by Maxwell’s day the options for a “physical explanation” had simply been enlarged by one. Now instead of just explaining something with mechanical parts, you could explain it with action at a distance as well. Indeed, many physicists tried to explain electricity and magnetism with some sort of gravity-like action at a distance. They failed, though. You really do need fields.

The author of the biography is an engineer, not a physicist, so I find his perspective unusual at times. After discussing Maxwell’s discomfort with fields, the author says that today physicists are different: instead of insisting on a physical explanation, they accept that there are some things they just cannot know.

At first, I wanted to object: we do have physical explanations, we explain things with fields! We have electromagnetic fields and electron fields, gluon fields and Higgs fields, even a gravitational field for the shape of space-time. These fields aren’t papering over some hidden mechanism, they are the mechanism!

Are they, though?

Fields aren’t quite like the whirlpools and ball bearings of historical physicists. Sometimes fields that look different are secretly the same: the two “different explanations” will give the same result for any measurement you could ever perform. In my area of physics, we try to avoid this by focusing on the measurements instead, building as much as we can out of observable quantities instead of fields. In effect we’re going back yet another layer, another dose of hypotheses non fingo.

Physicists still ask for “physical explanations”, and still worry that some picture might be “just mathematics”. But what that means has changed, and continues to change. I don’t think we have a common standard right now, at least nothing as specific as “mechanical parts or action at a distance, and nothing else”. Somehow, we still care about whether we’ve given an explanation, or just a description, even though we can’t define what an explanation is.

Congratulations to Simon Caron-Huot and Pedro Vieira for the New Horizons Prize!

The 2020 Breakthrough Prizes were announced last week, awards in physics, mathematics, and life sciences. The physics prize was awarded to the Event Horizon Telescope, with the $3 million award to be split among the 347 members of the collaboration. The Breakthrough Prize Foundation also announced this year’s New Horizons prizes, six smaller awards of $100,000 each to younger researchers in physics and math. One of those awards went to two people I know, Simon Caron-Huot and Pedro Vieira. Extremely specialized as I am, I hope no-one minds if I ignore all the other awards and talk about them.

The award for Caron-Huot and Vieira is “For profound contributions to the understanding of quantum field theory.” Indeed, both Simon and Pedro have built their reputations as explorers of quantum field theories, the kind of theories we use in particle physics. Both have found surprising behavior in these theories, where a theory people thought they understood did something quite unexpected. Both also developed new calculation methods, using these theories to compute things that were thought to be out of reach. But this is all rather vague, so let me be a bit more specific about each of them:

Simon Caron-Huot is known for his penetrating and mysterious insight. He has the ability to take a problem and think about it in a totally original way, coming up with a solution that no-one else could have thought of. When I first worked with him, he took a calculation that the rest of us would have taken a month to do and did it by himself in a week. His insight seems to come in part from familiarity with the physics literature, forgotten papers from the 60’s and 70’s that turn out surprisingly useful today. Largely, though, his insight is his own, an inimitable style that few can anticipate. His interests are broad, from exotic toy models to well-tested theories that describe the real world, covering a wide range of methods and approaches. Physicists tend to describe each other in terms of standard “virtues”: depth and breadth, knowledge and originality. Simon somehow seems to embody all of them.

Pedro Vieira is mostly known for his work with integrable theories. These are theories where if one knows the right trick one can “solve” the theory exactly, rather than using the approximations that physicists often rely on. Pedro was a mentor to me when I was a postdoc at the Perimeter Institute, and one thing he taught me was to always expect more. When calculating with computer code I would wait hours for a result, while Pedro would ask “why should it take hours?”, and if we couldn’t propose a reason would insist we find a quicker way. This attitude paid off in his research, where he has used integrable theories to calculate things others would have thought out of reach. His Pentagon Operator Product Expansion, or “POPE”, uses these tricks to calculate probabilities that particles collide, and more recently he pushed further to other calculations with a hexagon-based approach (which one might call the “HOPE”). Now he’s working on “bootstrapping” up complicated theories from simple physical principles, once again asking “why should this be hard?”

In Life and in Science, Test

Think of a therapist, and you might picture a pipe-smoking Freudian, interrogating you about repressed feelings. These days, you’re more likely to meet a more modern form of therapy, like cognitive behavioral therapy (or CBT for short). CBT focuses on correcting distorted thoughts and maladaptive behaviors: basically, helping you reason through your problems. It’s supposed to be one of the types of therapy that has the most actual scientific evidence behind it.

What impresses me about CBT isn’t just the scientific evidence for it, but the way it tries to teach something like a scientific worldview. If you’re depressed or anxious, a common problem is obsessive thoughts about what others think of you. Maybe you worry that everyone is just putting up with you out of pity, or that you’re hopelessly behind your peers. For many scientists, these are familiar worries.

The standard CBT advice for these worries is as obvious as it is scary: if you worry what others think of you, ask!

This is, at its heart, a very scientific thing to do. If you’re curious about something, and you can test it, just test it! Of course, there are risks to doing this, both in your personal life and in your science, but typical CBT advice applies surprisingly well to both.

If you constantly ask your friends what they think about you, you end up annoying them. Similarly, if you perform the same experiment over and over, you can keep going until you get the result you want. In both cases, the solution is to commit to trusting your initial results: just like scientists pre-registering a study, if you ask your friends what they think you need to trust them and not second-guess what they say. If they say they’re happy with you, trust that. If they criticize, take their criticism seriously and see if you can improve.

Even then, you may be tempted to come up with reasons why you can’t trust what your friends say. You’ll come up with reasons why they might be forced to be polite, while they secretly still hate you. Similarly, as a scientist you can always come up with theories that get around the evidence: no matter what you observe, a complicated enough chain of logic can make it consistent with anything you want. In both cases, the solution is a dose of Occam’s Razor: don’t fixate on an extremely complicated explanation when a simpler one already fits. If your friends say they like you, they probably do.

In Defense of the Streetlight

If you read physics blogs, you’ve probably heard this joke before:

A policeman sees a drunk man searching for something under a streetlight and asks what the drunk has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, and that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, “this is where the light is”.

The drunk’s line of thinking has a name, the streetlight effect, and while it may seem ridiculous it’s a common error, even among experts. When it gets too tough to research something, scientists will often be tempted by an easier problem even if it has little to do with the original question. After all, it’s “where the light is”.

Physicists get accused of this all the time. Dark matter could be completely undetectable on Earth, but physicists still build experiments to search for it. Our universe appears to be curved one way, but string theory makes it much easier to study universes curved the other way, so physicists write a lot of nice proofs about a universe we don’t actually inhabit. In my own field, we spend most of our time studying a very nice theory that we know can’t describe the real world.

I’m not going to defend this behavior in general. There are real cases where scientists trick themselves into thinking they can solve an easy problem when they need to solve a hard one. But there is a crucial difference between scientists and drunkards looking for their keys, one that makes this behavior a lot more reasonable: scientists build technology.

As scientists, we can’t just grope around in the dark for our keys. The spaces we’re searching, from the space of all theories of gravity to actual outer space, are much too vast to search randomly. We need new ideas, new mathematics or new equipment, to do the search properly. If we were the drunkard of the story, we’d need to invent night-vision goggles.

Is the light better here, or is it just me?

Suppose you wanted to design new night-vision goggles, to search for your keys in the park. You could try to build them in the dark, but you wouldn’t be able to see what you were doing: you’d lose pieces, miss screws, and break lenses. Much better to build the goggles under that convenient streetlight.

Of course, if you build and test your prototype goggles under the streetlight, you risk that they aren’t good enough for the dark. You’ll have calibrated them in an unrealistic case. In all likelihood, you’ll have to go back and fix your goggles, tweaking them as you go, and you’ll run into the same problem: you can’t see what you’re doing in the dark.

At that point, though, you have an advantage: you now know how to build night-vision goggles. You’ve practiced building goggles in the light, and now even if the goggles aren’t good enough, you remember how you put them together. You can tweak the process, modify your goggles, and make something good enough to find your keys. You’re good enough at making goggles that you can modify them now, even in the dark.

Sometimes scientists really are like the drunk, searching under the most convenient streetlight. Sometimes, though, scientists are working where the light is for a reason. Instead of wasting their time lost in the dark, they’re building new technology and practicing new methods, getting better and better at searching until, when they’re ready, they can go back and find their keys. Sometimes, the streetlight is worth it.