Tag Archives: mathematics

Two Loops, Five Particles

There’s a very long-term view of the amplitudes field that gets a lot of press. We’re supposed to be eliminating space and time, or rebuilding quantum field theory from scratch. We build castles in the clouds, seven-loop calculations and all-loop geometrical quantum jewels.

There’s a shorter-term problem, though, that gets much less press, despite arguably being a bigger part of the field right now. In amplitudes, we take theories and turn them into predictions, order by order and loop by loop. And when we want to compare those predictions to the real world, in most cases the best we can do is two loops and five particles.

Five particles here counts the particles coming in and going out: if two gluons collide and become three gluons, we count that as five particles, two in plus three out. Loops, meanwhile, measure the complexity of the calculation, the number of closed paths you can draw in a Feynman diagram. If you use more loops, you expect more precision: you’re approximating nature step by step.

As a field we’re pretty good at one-loop calculations, enough to do them for pretty much any number of particles. As we try for more loops though, things rapidly get harder. Already for two loops, in many cases, we start struggling. We can do better if we dial down the number of particles: there are three-particle and two-particle calculations that get up to three, four, or even five loops. For more particles though, we can’t do as much. Thus the current state of the art, the field’s short term goal: two loops, five particles.

When you hear people like me talk about crazier calculations, we’ve usually got a trick up our sleeve. Often we’re looking at a much simpler theory, one that doesn’t describe the real world. For example, I like working with a planar theory, with lots of supersymmetry. Remove even one of those simplifications, and suddenly our life becomes a lot harder. Instead of seven loops and six particles, we get genuinely excited about, well, two loops five particles.

Luckily, two loops five particles is also about as good as the experiments can measure. As the Large Hadron Collider gathers more data, it measures physics to higher and higher precision. Currently for five-particle processes, its precision is just starting to be comparable with two-loop calculations. The result has been a flurry of activity, applying everything from powerful numerical techniques to algebraic geometry to the problem, getting results that genuinely apply to the real world.

“Two loops, five particles” isn’t as cool of a slogan as “space-time is doomed”. It doesn’t get much, or any media attention. But, steadily and quietly, it’s become one of the hottest topics in the amplitudes field.

Research Rooms, Collaboration Spaces

Math and physics are different fields with different cultures. Some of those differences are obvious, others more subtle.

I recently remembered a subtle difference I noticed at the University of Waterloo. The math building there has “research rooms”, rooms intended for groups of mathematicians to collaborate. The idea is that you invite visitors to the department, reserve the room, and spend all day with them trying to iron out a proof or the like.

Theoretical physicists collaborate like this sometimes too, but in my experience physics institutes don’t typically have this kind of “research room”. Instead, they have “collaboration spaces”. Unlike a “research room”, you don’t reserve a “collaboration space”. Typically, they aren’t even rooms: they’re a set of blackboards in the coffee room, or a cluster of chairs in the corner between two hallways. They’re open spaces, designed so that passers-by can overhear the conversation and (potentially) join in.

That’s not to say physicists never shut themselves in a room for a day (or night) to work. But when they do, it’s not usually in a dedicated space. Instead, it’s in an office, or a commandeered conference room.

Waterloo’s “research rooms” and physics institutes’ “collaboration spaces” can be used for similar purposes. The difference is in what they encourage.

The point of a “collaboration space” is to start new collaborations. These spaces are open in order to take advantage of serendipity: if you’re getting coffee or walking down the hall, you might hear something interesting and spark something new, with people you hadn’t planned to collaborate with before. Institutes with “collaboration spaces” are trying to make new connections between researchers, to be the starting point for new ideas.

The point of a “research room” is to finish a collaboration. They’re for researchers who are already collaborating, who know they’re going to need a room and can reserve it in advance. They’re enclosed in order to shut out distractions, to make sure the collaborators can sit down and focus and get something done. Institutes with “research rooms” want to give their researchers space to complete projects when they might otherwise be too occupied with other things.

I’m curious if this difference is more widespread. Do math departments generally tend to have “research rooms” or “collaboration spaces”? Are there physics departments with “research rooms”? I suspect there is a real cultural difference here, in what each field thinks it needs to encourage.

Amplitudes in String and Field Theory at NBI

There’s a conference at the Niels Bohr Institute this week, on Amplitudes in String and Field Theory. Like the conference a few weeks back, this one was funded by the Simons Foundation, as part of Michael Green’s visit here.

The first day featured a two-part talk by Michael Green and Congkao Wen. They are looking at the corrections that string theory adds on top of theories of supergravity. These corrections are difficult to calculate directly from string theory, but one can figure out a lot about them from the kinds of symmetry and duality properties they need to have, using the mathematics of modular forms. While Michael’s talk introduced the topic with a discussion of older work, Congkao talked about their recent progress looking at this from an amplitudes perspective.

Francesca Ferrari’s talk on Tuesday also related to modular forms, while Oliver Schlotterer and Pierre Vanhove talked about a different corner of mathematics, single-valued polylogarithms. These single-valued polylogarithms are of interest to string theorists because they seem to connect two parts of string theory: the open strings that describe Yang-Mills forces and the closed strings that describe gravity. In particular, it looks like you can take a calculation in open string theory and just replace numbers and polylogarithms with their “single-valued counterparts” to get the same calculation in closed string theory. Interestingly, there is more than one way that mathematicians can define “single-valued counterparts”, but only one such definition, the one due to Francis Brown, seems to make this trick work. When I asked Pierre about this he quipped it was because “Francis Brown has good taste…either that, or String Theory has good taste.”

Wednesday saw several talks exploring interesting features of string theory. Nathan Berkovitz discussed his new paper, which makes a certain context of AdS/CFT (a duality between string theory in certain curved spaces and field theory on the boundary of those spaces) manifest particularly nicely. By writing string theory in five-dimensional AdS space in the right way, he can show that if the AdS space is small it will generate the same Feynman diagrams that one would use to do calculations in N=4 super Yang-Mills. In the afternoon, Sameer Murthy showed how localization techniques can be used in gravity theories, including to calculate the entropy of black holes in string theory, while Yvonne Geyer talked about how to combine the string theory-like CHY method for calculating amplitudes with supersymmetry, especially in higher dimensions where the relevant mathematics gets tricky.

Thursday ended up focused on field theory. Carlos Mafra was originally going to speak but he wasn’t feeling well, so instead I gave a talk about the “tardigrade” integrals I’ve been looking at. Zvi Bern talked about his work applying amplitudes techniques to make predictions for LIGO. This subject has advanced a lot in the last few years, and now Zvi and collaborators have finally done a calculation beyond what others had been able to do with older methods. They still have a way to go before they beat the traditional methods overall, but they’re off to a great start. Lance Dixon talked about two-loop five-particle non-planar amplitudes in N=4 super Yang-Mills and N=8 supergravity. These are quite a bit trickier than the planar amplitudes I’ve worked on with him in the past, in particular it’s not yet possible to do this just by guessing the answer without considering Feynman diagrams.

Today was the last day of the conference, and the emphasis was on number theory. David Broadhurst described some interesting contributions from physics to mathematics, in particular emphasizing information that the Weierstrass formulation of elliptic curves omits. Eric D’Hoker discussed how the concept of transcendentality, previously used in field theory, could be applied to string theory. A few of his speculations seemed a bit farfetched (in particular, his setup needs to treat certain rational numbers as if they were transcendental), but after his talk I’m a bit more optimistic that there could be something useful there.

Pi Day Alternatives

On Pi Day, fans of the number pi gather to recite its digits and eat pies. It is the most famous of numerical holidays, but not the only one. Have you heard of the holidays for other famous numbers?

Tau Day: Celebrated on June 28. Observed by sitting around gloating about how much more rational one is than everyone else, then getting treated with high-energy tau leptons for terminal pedantry.

Canadian Modular Pi Day: Celebrated on February 3. Observed by confusing your American friends.

e Day: Celebrated on February 7. Observed in middle school classrooms, explaining the wonders of exponential functions and eating foods like eggs and eclairs. Once the students leave, drop tabs of ecstasy instead.

Golden Ratio Day: Celebrated on January 6. Rub crystals on pyramids and write vaguely threatening handwritten letters to every physicist you’ve heard of.

Euler Gamma Day: Celebrated on May 7 by dropping on the floor and twitching.

Riemann Zeta Daze: The first year, forget about it. The second, celebrate on January 6. The next year, January 2. After that, celebrate on New Year’s Day earlier and earlier in the morning each year until you can’t tell the difference any more.

This Week, at Scientific American

I’ve written an article for Scientific American! It went up online this week, the print versions go out on the 25th. The online version is titled “Loopy Particle Math”, the print one is “The Particle Code”, but they’re the same article.

For those who don’t subscribe to Scientific American, sorry about the paywall!

“The Particle Code” covers what will be familiar material to regulars on this blog. I introduce Feynman diagrams, and talk about the “amplitudeologists” who try to find ways around them. I focus on my corner of the amplitudes field, how the work of Goncharov, Spradlin, Vergu, and Volovich introduced us to “symbology”, a set of tricks for taking apart more complicated integrals (or “periods”) into simple logarithmic building blocks. I talk about how my collaborators and I use symbology, using these building blocks to compute amplitudes that would have been impossible with other techniques. Finally, I talk about the frontier of the field, the still-mysterious “elliptic polylogarithms” that are becoming increasingly well-understood.

(I don’t talk about the even more mysterious “Calabi-Yau polylogarithms“…another time for those!)

Working with Scientific American was a fun experience. I got to see how the professionals do things. They got me to clarify and explain, pointing out terms I needed to define and places I should pause to summarize. They took my rough gel-pen drawings and turned them into polished graphics. While I’m still a little miffed about them removing all the contractions, overall I learned a lot, and I think they did a great job of bringing the article to the printed page.

A Micrographia of Beastly Feynman Diagrams

Earlier this year, I had a paper about the weird multi-dimensional curves you get when you try to compute trickier and trickier Feynman diagrams. These curves were “Calabi-Yau”, a type of curve string theorists have studied as a way to curl up extra dimensions to preserve something called supersymmetry. At the time, string theorists asked me why Calabi-Yau curves showed up in these Feynman diagrams. Do they also have something to do with supersymmetry?

I still don’t know the general answer. I don’t know if all Feynman diagrams have Calabi-Yau curves hidden in them, or if only some do. But for a specific class of diagrams, I now know the reason. In this week’s paper, with Jacob Bourjaily, Andrew McLeod, and Matthias Wilhelm, we prove it.

We just needed to look at some more exotic beasts to figure it out.


Like this guy!

Meet the tardigrade. In biology, they’re incredibly tenacious microscopic animals, able to withstand the most extreme of temperatures and the radiation of outer space. In physics, we’re using their name for a class of Feynman diagrams.


A clear resemblance!

There is a long history of physicists using whimsical animal names for Feynman diagrams, from the penguin to the seagull (no relation). We chose to stick with microscopic organisms: in addition to the tardigrades, we have paramecia and amoebas, even a rogue coccolithophore.

The diagrams we look at have one thing in common, which is key to our proof: the number of lines on the inside of the diagram (“propagators”, which represent “virtual particles”) is related to the number of “loops” in the diagram, as well as the dimension. When these three numbers are related in the right way, it becomes relatively simple to show that any curves we find when computing the Feynman diagram have to be Calabi-Yau.

This includes the most well-known case of Calabi-Yaus showing up in Feynman diagrams, in so-called “banana” or “sunrise” graphs. It’s closely related to some of the cases examined by mathematicians, and our argument ended up pretty close to one made back in 2009 by the mathematician Francis Brown for a different class of diagrams. Oddly enough, neither argument works for the “traintrack” diagrams from our last paper. The tardigrades, paramecia, and amoebas are “more beastly” than those traintracks: their Calabi-Yau curves have more dimensions. In fact, we can show they have the most dimensions possible at each loop, provided all of our particles are massless. In some sense, tardigrades are “as beastly as you can get”.

We still don’t know whether all Feynman diagrams have Calabi-Yau curves, or just these. We’re not even sure how much it matters: it could be that the Calabi-Yau property is a red herring here, noticed because it’s interesting to string theorists but not so informative for us. We don’t understand Calabi-Yaus all that well yet ourselves, so we’ve been looking around at textbooks to try to figure out what people know. One of those textbooks was our inspiration for the “bestiary” in our title, an author whose whimsy we heartily approve of.

Like the classical bestiary, we hope that ours conveys a wholesome moral. There are much stranger beasts in the world of Feynman diagrams than anyone suspected.

When You Shouldn’t Listen to a Distinguished but Elderly Scientist

Of science fiction author Arthur C. Clarke’s sayings, the most famous is “Clarke’s third law”, that “Any sufficiently advanced technology is indistinguishable from magic.” Almost as famous, though, is his first law:

“When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.”

Recently Michael Atiyah, an extremely distinguished but also rather elderly mathematician, claimed that something was possible: specifically, he claimed it was possible that he had proved the Riemann hypothesis, one of the longest-standing and most difficult puzzles in mathematics. I won’t go into the details here, but people are, well, skeptical.

This post isn’t really about Atiyah. I’m not close enough to that situation to comment. Instead, it’s about a more general problem.

See, the public seems to mostly agree with Clarke’s law. They trust distinguished, elderly scientists, at least when they’re saying something optimistic. Other scientists know better. We know that scientists are human, that humans age…and that sometimes scientific minds don’t age gracefully.

Some of the time, that means Alzheimer’s, or another form of dementia. Other times, it’s nothing so extreme, just a mind slowing down with age, opinions calcifying and logic getting just a bit more fuzzy.

And the thing is, watching from the sidelines, you aren’t going to know the details. Other scientists in the field will, but this kind of thing is almost never discussed with the wider public. Even here, though specific physicists come to mind as I write this, I’m not going to name them. It feels rude, to point out that kind of all-too-human weakness in someone who accomplished so much. But I think it’s important for the public to keep in mind that these people exist. When an elderly Nobelist claims to have solved a problem that baffles mainstream science, the news won’t tell you they’re mentally ill. All you can do is keep your eyes open, and watch for warning signs:

Be wary of scientists who isolate themselves. Scientists who still actively collaborate and mentor almost never have this kind of problem. There’s a nasty feedback loop when those contacts start to diminish. Being regularly challenged is crucial to test scientific ideas, but it’s also important for mental health, especially in the elderly. As a scientist thinks less clearly, they won’t be able to keep up with their collaborators as much, worsening the situation.

Similarly, beware those famous enough to surround themselves with yes-men. With Nobel prizewinners in particular, many of the worst cases involve someone treated with so much reverence that they forget to question their own ideas. This is especially risky when commenting on an unfamiliar field: often, the Nobelist’s contacts in the new field have a vested interest in holding on to their big-name support, and ignoring signs of mental illness.

Finally, as always, bigger claims require better evidence. If everything someone works on is supposed to revolutionize science as we know it, then likely none of it will. The signs that indicate crackpots apply here as well: heavily invoking historical scientists, emphasis on notation over content, a lack of engagement with the existing literature. Be especially wary if the argument seems easy, deep problems are rarely so simple to solve.

Keep this in mind, and the next time a distinguished but elderly scientist states that something is possible, don’t trust them blindly. Ultimately, we’re still humans beings. We don’t last forever.