Category Archives: Life as a Physicist

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.

“X Meets Y” Conferences

Most conferences focus on a specific sub-field. If you call a conference “Strings” or “Amplitudes”, people know what to expect. Likewise if you focus on something more specific, say Elliptic Integrals. But what if your conference is named after two sub-fields?

These conferences, with names like “QCD Meets Gravity” and “Scattering Amplitudes and the Conformal Bootstrap”, try to connect two different sub-fields together. I’ll call them “X Meets Y” conferences.

The most successful “X Meets Y” conferences involve two sub-fields that have been working together for quite some time. At that point, you don’t just have “X” researchers and “Y” researchers, but “X and Y” researchers, people who work on the connection between both topics. These people can glue a conference together, showing the separate “X” and “Y” researchers what “X and Y” research looks like. At a conference like that speakers have a clear idea of what to talk about: the “X” researchers know how to talk to the “Y” researchers, and vice versa, and the organizers can invite speakers who they know can talk to both groups.

If the sub-fields have less history of collaboration, “X Meets Y” conferences become trickier. You need at least a few “X and Y” researchers (or at least aspiring “X and Y” researchers) to guide the way. Even if most of the “X” researchers don’t know how to talk to “Y” researchers, the “X and Y” researchers can give suggestions, telling “X” which topics would be most interesting to “Y” and vice versa. With that kind of guidance, “X Meets Y” conferences can inspire new directions of research, opening one field up to the tools of another.

The biggest risk in an “X Meets Y” conference, that becomes more likely the fewer “X and Y” researchers there are, is that everyone just gives their usual talks. The “X” researchers talk about their “X”, and the “Y” researchers talk about their “Y”, and both groups nod politely and go home with no new ideas whatsoever. Scientists are fundamentally lazy creatures. If we already have a talk written, we’re tempted to use it, even if it doesn’t quite fit the occasion. Counteracting that is a tough job, and one that isn’t always feasible.

“X Meets Y” conferences can be very productive, the beginning of new interdisciplinary ideas. But they’re certainly hard to get right. Overall, they’re one of the trickier parts of the social side of science.

At Aspen

I’m at the Aspen Center for Physics this week, for a workshop on Scattering Amplitudes and the Conformal Bootstrap.

A place even greener than its ubiquitous compost bins

Aspen is part of a long and illustrious tradition of physics conference sites located next to ski resorts. It’s ten years younger than its closest European counterpart Les Houches School of Physics, but if anything its traditions are stricter: all blackboard talks, and a minimum two-week visit. Instead of the summer schools of Les Houches, Aspen’s goal is to inspire collaboration: to get physicists to spend time working and hiking around each other until inspiration strikes.

This workshop is a meeting between two communities: people who study the Conformal Bootstrap (nice popular description here) and my own field of Scattering Amplitudes. The Conformal Boostrap is one of our closest sister-fields, so there may be a lot of potential for collaboration. This week’s talks have been amplitudes-focused, I’m looking forward to the talks next week that will highlight connections between the two fields.

When to Read Someone Else’s Thesis

There’s a cynical truism we use to reassure grad students. A thesis is a big, daunting project, but it shouldn’t be too stressful: in the end, nobody else is going to read it.

This is mostly true. In many fields your thesis is a mix of papers you’ve already published, stitched together into your overall story. Anyone who’s interested will have read the papers the thesis is based on, they don’t need to read the thesis too.

Like every good truism, though, there is an exception. Some rare times, you will actually want to read someone else’s thesis. This isn’t usually because the material is new: rather it’s because it’s well explained.

When we academics publish, we’re often in a hurry, and there isn’t time to write well. When we publish more slowly, often we have more collaborators, so the paper is a set of compromises written by committee. Either way, we rarely make a concept totally crystal-clear.

A thesis isn’t always crystal-clear either, but it can be. It’s written by just one person, and that person is learning. A grad student who just learned a topic can be in the best position to teach it: they know exactly what confused them when they start out. Thesis-writing is also a slower process, one that gives more time to hammer at a text until it’s right. Finally, a thesis is written for a committee, and that committee usually contains people from different fields. A thesis needs to be an accessible introduction, in a way that a published paper doesn’t.

There are topics that I never really understood until I looked up the thesis of the grad student who helped discover it. There are tricks that never made it to published papers, that I’ve learned because they were tucked in to the thesis of someone who went on to do great things.

So if you’re finding a subject confusing, if you’ve read all the papers and none of them make any sense, look for the grad students. Sometimes the best explanation of a tricky topic isn’t in the published literature, it’s hidden away in someone’s thesis.

Academic Age

Growing up in the US there are a lot of age-based milestones. You can drive at 16, vote at 18, and drink at 21. Once you’re in academia though, your actual age becomes much less relevant. Instead, academics are judged based on academic age, the time since you got your PhD.

And no, we don’t get academic birthdays

Grants often have restrictions based on academic age. The European Research Council’s Starting Grant, for example, demands an academic age of 2-7. If you’re academically “older”, they expect more from you: you must instead apply for a Consolidator Grant, or an Advanced Grant.

More generally, when academics apply for jobs they are often weighed in terms of academic age. Compared to others, how long have you spent as a postdoc since your PhD? How many papers have you published since then, and how well cited were they? The longer you spend without finding a permanent position, the more likely employers are to wonder why, and the reasons they assume are rarely positive.

This creates some weird incentives. If you have a choice, it’s often better to graduate late than to graduate early. Employers don’t check how long you took to get your PhD, but they do pay attention to how many papers you published. If it’s an option, staying in school to finish one more project can actually be good for your career.

Biological age matters, but mostly for biological reasons: for example, if you plan to have children. Raising a family is harder if you have to move every few years, so those who find permanent positions by then have an easier time of it. That said, as academics have to take more temporary positions before settling down fewer people have this advantage.

Beyond that, biological age only matters again at the end of your career, especially if you work somewhere with a mandatory retirement age. Even then, retirement for academics doesn’t mean the same thing as for normal people: retired professors often have emeritus status, meaning that while technically retired they keep a role at the university, maintaining an office and often still doing some teaching or research.

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.