Monthly Archives: April 2021

Electromagnetism Is the Weirdest Force

13 Replies

For a long time, physicists only knew about two fundamental forces: electromagnetism, and gravity. Physics students follow the same path, studying Newtonian gravity, then E&M, and only later learning about the other fundamental forces. If you’ve just recently heard about the weak nuclear force and the strong nuclear force, it can be tempting to think of them as just slight tweaks on electromagnetism. But while that can be a helpful way to start, in a way it’s precisely backwards. Electromagnetism is simpler than the other forces, that’s true. But because of that simplicity, it’s actually pretty weird as a force.

The weirdness of electromagnetism boils down to one key reason: the electromagnetic field has no charge.

Maybe that sounds weird to you: if you’ve done anything with electromagnetism, you’ve certainly seen charges. But while you’ve calculated the field produced by a charge, the field itself has no charge. You can specify the positions of some electrons and not have to worry that the electric field will introduce new charges you didn’t plan. Mathematically, this means your equations are linear in the field, and thus not all that hard to solve.

The other forces are different. The strong nuclear force has three types of charge, dubbed red, green, and blue. Not just quarks, but the field itself has charges under this system, making the equations that describe it non-linear.

A depiction of a singlet state

Those properties mean that you can’t just think of the strong force as a push or pull between charges, like you could with electromagnetism. The strong force doesn’t just move quarks around, it can change their color, exchanging charge between the quark and the field. That’s one reason why when we’re more careful we refer to it as not the strong force, but the strong interaction.

The weak force also makes more sense when thought of as an interaction. It can change even more properties of particles, turning different flavors of quarks and leptons into each other, resulting in among other phenomena nuclear beta decay. It would be even more like the strong force, but the Higgs field screws that up, stirring together two more fundamental forces and spitting out the weak force and electromagnetism. The result ties them together in weird ways: for example, it means that the weak field can actually have an electric charge.

Interactions like the strong and weak forces are much more “normal” for particle physicists: if you ask us to picture a random fundamental force, chances are it will look like them. It won’t typically look like electromagnetism, the weird “degenerate” case with a field that doesn’t even have a charge. So despite how familiar electromagnetism may be to you, don’t take it as your model of what a fundamental force should look like: of all the forces, it’s the simplest and weirdest.

Building One’s Technology

2 Replies

There are theoretical physicists who can do everything they do with a pencil and a piece of paper. I’m not one of them. The calculations I do are long, complicated, or tedious enough that they’re often best done with a computer. For a calculation like that, I can’t just use existing software “out of the box”: I need to program special-purpose tools to do the kind of calculation I need. This means each project has its own kind of learning curve. If I already have the right code, or almost the right code, things go very smoothly: with a few tweaks I can do a lot of interesting calculations. If I don’t have the right code yet, things go much more slowly: I have to build up my technology, figuring out what I need piece by piece until I’m back up to my usual speed.

I don’t always need to use computers to do my calculations. Sometimes my work hinges on something more conceptual: understanding a mathematical proof, or the arguments from another physicist’s paper. While this seems different on the surface, I’ve found that it has the same kinds of learning curves. If I know the right papers and mathematical methods, I can go pretty quickly. If I don’t, I have to “build up my technology”, reading and practicing, a slow build-up to my goal.

The times when I have to “build my technology” are always a bit frustrating. I don’t work as fast as I’d like, and I get tripped up by dumb mistakes. I keep having to go back, almost to the beginning, realizing that some aspect of how I set things up needs to be changed to make the rest work. As I go, though, the work gets more and more satisfying. I find pieces (of the code, of my understanding) that become solid, that I can rely on. I build my technology, and I can do more and more, and feel better about myself in the bargain. Eventually, I get back up to my full abilities, my technology set up, and a wide variety of calculations become possible.

Doing Difficult Things Is Its Own Reward

Leave a reply

Does antimatter fall up, or down?

Technically, we don’t know yet. The ALPHA-g experiment would have been the first to check this, making anti-hydrogen by trapping anti-protons and positrons in a long tube and seeing which way it falls. While they got most of their setup working, the LHC complex shut down before they could finish. It starts up again next month, so we should have our answer soon.

That said, for most theorists’ purposes, we absolutely do know: antimatter falls down. Antimatter is one of the cleanest examples of a prediction from pure theory that was confirmed by experiment. When Paul Dirac first tried to write down an equation that described electrons, he found the math forced him to add another particle with the opposite charge. With no such particle in sight, he speculated it could be the proton (this doesn’t work, they need the same mass), before Carl D. Anderson discovered the positron in 1932.

The same math that forced Dirac to add antimatter also tells us which way it falls. There’s a bit more involved, in the form of general relativity, but the recipe is pretty simple: we know how to take an equation like Dirac’s and add gravity to it, and we have enough practice doing it in different situations that we’re pretty sure it’s the right way to go. Pretty sure doesn’t mean 100% sure: talk to the right theorists, and you’ll probably find a proposal or two in which antimatter falls up instead of down. But they tend to be pretty weird proposals, from pretty weird theorists.

Ok, but if those theorists are that “weird”, that outside the mainstream, why does an experiment like ALPHA-g exist? Why does it happen at CERN, one of the flagship facilities for all of mainstream particle physics?

This gets at a misconception I occasionally hear from critics of the physics mainstream. They worry about groupthink among mainstream theorists, the physics community dismissing good ideas just because they’re not trendy (you may think I did that just now, for antigravity antimatter!) They expect this to result in a self-fulfilling prophecy where nobody tests ideas outside the mainstream, so they find no evidence for them, so they keep dismissing them.

The mistake of these critics is in assuming that what gets tested has anything to do with what theorists think is reasonable.

Theorists talk to experimentalists, sure. We motivate them, give them ideas and justification. But ultimately, people do experiments because they can do experiments. I watched a talk about the ALPHA experiment recently, and one thing that struck me was how so many different techniques play into it. They make antiprotons using a proton beam from the accelerator, slow them down with magnetic fields, and cool them with lasers. They trap their antihydrogen in an extremely precise vacuum, and confirm it’s there with particle detectors. The whole setup is a blend of cutting-edge accelerator physics and cutting-edge tricks for manipulating atoms. At its heart, ALPHA-g feels like its primary goal is to stress-test all of those tricks: to push the state of the art in a dozen experimental techniques in order to accomplish something remarkable.

And so even if the mainstream theorists don’t care, ALPHA will keep going. It will keep getting funding, it will keep getting visited by celebrities and inspiring pop fiction. Because enough people recognize that doing something difficult can be its own reward.

In my experience, this motivation applies to theorists too. Plenty of us will dismiss this or that proposal as unlikely or impossible. But give us a concrete calculation, something that lets us use one of our flashy theoretical techniques, and the tune changes. If we’re getting the chance to develop our tools, and get a paper out of it in the process, then sure, we’ll check your wacky claim. Why not?

I suspect critics of the mainstream would have a lot more success with this kind of pitch-based approach. If you can find a theorist who already has the right method, who’s developing and extending it and looking for interesting applications, then make your pitch: tell them how they can answer your question just by doing what they do best. They’ll think of it as a chance to disprove you, and you should let them, that’s the right attitude to take as a scientist anyway. It’ll work a lot better than accusing them of hogging the grant money.

Theoretical Uncertainty and Uncertain Theory

5 Replies

Yesterday, Fermilab’s Muon g-2 experiment announced a new measurement of the magnetic moment of the muon, a number which describes how muons interact with magnetic fields. For what might seem like a small technical detail, physicists have been very excited about this measurement because it’s a small technical detail that the Standard Model seems to get wrong, making it a potential hint of new undiscovered particles. Quanta magazine has a great piece on the announcement, which explains more than I will here, but the upshot is that there are two different calculations on the market that attempt to predict the magnetic moment of the muon. One of them, using older methods, disagrees with the experiment. The other, with a new approach, agrees. The question then becomes, which calculation was wrong? And why?

What does it mean for a prediction to match an experimental result? The simple, wrong, answer is that the numbers must be equal: if you predict “3”, the experiment has to measure “3”. The reason why this is wrong is that in practice, every experiment and every prediction has some uncertainty. If you’ve taken a college physics class, you’ve run into this kind of uncertainty in one of its simplest forms, measurement uncertainty. Measure with a ruler, and you can only confidently measure down to the smallest divisions on the ruler. If you measure 3cm, but your ruler has ticks only down to a millimeter, then what you’re measuring might be as large as 3.1cm or as small as 2.9 cm. You just don’t know.

This uncertainty doesn’t mean you throw up your hands and give up. Instead, you estimate the effect it can have. You report, not a measurement of 3cm, but of 3cm plus or minus 1mm. If the prediction was 2.9cm, then you’re fine: it falls within your measurement uncertainty.

Measurements aren’t the only thing that can be uncertain. Predictions have uncertainty too, theoretical uncertainty. Sometimes, this comes from uncertainty on a previous measurement: if you make a prediction based on that experiment that measured 3cm plus or minus 1mm, you have to take that plus or minus into account and estimate its effect (we call this propagation of errors). Sometimes, the uncertainty comes instead from an approximation you’re making. In particle physics, we sometimes approximate interactions between different particles with diagrams, beginning with the simplest diagrams and adding on more complicated ones as we go. To estimate the uncertainty there, we estimate the size of the diagrams we left out, the more complicated ones we haven’t calculated yet. Other times, that approximation doesn’t work, and we need to use a different approximation, treating space and time as a finite grid where we can do computer simulations. In that case, you can estimate your uncertainty based on how small you made your grid. The new approach to predicting the muon magnetic moment uses that kind of approximation.

There’s a common thread in all of these uncertainty estimates: you don’t expect to be too far off on average. Your measurements won’t be perfect, but they won’t all be screwed up in the same way either: chances are, they will randomly be a little below or a little above the truth. Your calculations are similar: whether you’re ignoring complicated particle physics diagrams or the spacing in a simulated grid, you can treat the difference as something small and random. That randomness means you can use statistics to talk about your errors: you have statistical uncertainty. When you have statistical uncertainty, you can estimate, not just how far off you might get, but how likely it is you ended up that far off. In particle physics, we have very strict standards for this kind of thing: to call something new a discovery, we demand that it is so unlikely that it would only show up randomly under the old theory roughly one in a million times. The muon magnetic moment isn’t quite up to our standards for a discovery yet, but the new measurement brought it closer.

The two dueling predictions for the muon’s magnetic moment both estimate some amount of statistical uncertainty. It’s possible that the two calculations just disagree due to chance, and that better measurements or a tighter simulation grid would make them agree. Given their estimates, though, that’s unlikely. That takes us from the realm of theoretical uncertainty, and into uncertainty about the theoretical. The two calculations use very different approaches. The new calculation tries to compute things from first principles, using the Standard Model directly. The risk is that such a calculation needs to make assumptions, ignoring some effects that are too difficult to calculate, and one of those assumptions may be wrong. The older calculation is based more on experimental results, using different experiments to estimate effects that are hard to calculate but that should be similar between different situations. The risk is that the situations may be less similar than expected, their assumptions breaking down in a way that the bottom-up calculation could catch.

None of these risks are easy to estimate. They’re “unknown unknowns”, or rather, “uncertain uncertainties”. And until some of them are resolved, it won’t be clear whether Fermilab’s new measurement is a sign of undiscovered particles, or just a (challenging!) confirmation of the Standard Model.

Is Outreach for Everyone?

1 Reply

Betteridge’s law applies here: the answer is “no”. It’s a subtle “no”, though.

As a scientist, you will always need to be able to communicate your work. Most of the time you can get away with papers and talks aimed at your peers. But the longer you mean to stick around, the more often you will have to justify yourself to others: to departments, to universities, and to grant agencies. A scientist cannot survive on scientific ability alone: to get jobs, to get funding, to survive, you need to be able to promote yourself, at least a little.

Self-promotion isn’t outreach, though. Talking to the public, or to journalists, is a different skill from talking to other academics or writing grants. And it’s entirely possible to go through an entire scientific career without exercising that skill.

That’s a reassuring message for some. I’ve met people for whom science is a refuge from the mess of human interaction, people horrified by the thought of fame or even being mentioned in a newspaper. When I meet these people, they sometimes seem to worry that I’m silently judging them, thinking that they’re ignoring their responsibilities by avoiding outreach. They think this in part because the field seems to be going in that direction. Grants that used to focus just on science have added outreach as a requirement, demanding that each application come with a plan for some outreach project.

I can’t guarantee that more grants won’t add outreach requirements. But I can say at least that I’m on your side here: I don’t think you should have to do outreach if you don’t want to. I don’t think you have to, just yet. And I think if grant agencies are sensible, they’ll find a way to encourage outreach without making it mandatory.

I think that overall, collectively, we have a responsibility to do outreach. Beyond the old arguments about justifying ourselves to taxpayers, we also just ought to be open about what we do. In a world where people are actively curious about us, we ought to encourage and nurture that curiosity. I don’t think this is unique to science, I think it’s something every industry, every hobby, and every community should foster. But in each case, I think that communication should be done by people who want to do it, not forced on every member.

I also think that, potentially, anyone can do outreach. Outreach can take different forms for different people, anything from speaking to high school students to talking to journalists to writing answers for Stack Exchange. I don’t think anyone should feel afraid of outreach because they think they won’t be good enough. Chances are, you know something other people don’t: I guarantee if you want to, you will have something worth saying.