A Taste of Normal

I grew up in the US. I’ve roamed over the years, but each year I’ve managed to come back around this time. My folks throw the kind of Thanksgiving you see in movies, a table overflowing with turkey and nine kinds of pie.

This year, obviously, is different. No travel, no big party. Still, I wanted to capture some of the feeling here in my cozy Copenhagen apartment. My wife and I baked mini-pies instead, a little feast just for us two.

In these weird times, it’s good to have the occasional taste of normal, a dose of tradition to feel more at home. That doesn’t just apply to personal life, but to academic life as well.

One tradition among academics is the birthday conference. Often timed around a 60th birthday, birthday conferences are a way to celebrate the achievements of professors who have made major contributions to a field. There are talks by their students and close collaborators, filled with stories of the person being celebrated.

Last week was one such conference, in honor of one of the pioneers of my field, Dirk Kreimer. The conference was Zoom-based, and it was interesting to compare with the other Zoom conferences I’ve seen this year. One thing that impressed me was how they handled the “social side” of the conference. Instead of a Slack space like the other conferences, they used a platform called Gather. Gather gives people avatars on a 2D map, mocked up to look like an old-school RPG. Walk close to a group of people, and it lets you video chat with them. There are chairs and tables for private conversations, whiteboards to write on, and in this case even a birthday card to sign.

I didn’t get a chance to try Gather. My guess is it’s a bit worse than Slack for some kinds of discussion. Start a conversation in a Slack channel and people can tune in later from other time zones, each posting new insights and links to references. It’s a good way to hash out an idea.

But a birthday conference isn’t really about hashing out ideas. It’s about community and familiarity, celebrating people we care about. And for that purpose, Gather seems great. You want that little taste of normalcy, of walking across the room and seeing a familiar face, chatting with the folks you keep seeing year after year.

I’ve mused a bit about what it takes to do science when we can’t meet in person. Part of that is a question of efficiency: what does it take it get research done? But if we focus too much on that, we might forget the role of culture. Scientists are people, we form a community, and part of what we value is comfort and familiarity. Keeping that community alive means not just good research discussions, but traditions as well, ways of referencing things we’ve done to carry forward to new circumstances. We will keep changing, our practices will keep evolving. But if we want those changes to stick, we should tie them to the past too. We should keep giving people those comforting tastes of normal.

Science and Its Customers

In most jobs, you know who you’re working for.

A chef cooks food, and people eat it. A tailor makes clothes, and people wear them. An artist has an audience, an engineer has end users, a teacher has students. Someone out there benefits directly from what you do. Make them happy, and they’ll let you know. Piss them off, and they’ll stop hiring you.

Science benefits people too…but most of its benefits are long-term. The first person to magnetize a needle couldn’t have imagined worldwide electronic communication, and the scientists who uncovered quantum mechanics couldn’t have foreseen transistors, or personal computers. The world benefits just by having more expertise in it, more people who spend their lives understanding difficult things, and train others to understand difficult things. But those benefits aren’t easy to see for each individual scientist. As a scientist, you typically don’t know who your work will help, or how much. You might not know for years, or even decades, what impact your work will have. Even then, it will be difficult to tease out your contribution from the other scientists of your time.

We can’t ask the customers of the future to pay for the scientists of today. (At least, not straightforwardly.) In practice, scientists are paid by governments and foundations, groups trying on some level to make the future a better place. Instead of feedback from customers we get feedback from each other. If our ideas get other scientists excited, maybe they’ll matter down the road.

This is a risky thing to do, of course. Governments, foundations, and scientists can’t tell the future. They can try to act in the interests of future generations, but they might just act for themselves instead. Trying to plan ahead like this makes us prey to all the cognitive biases that flesh is heir to.

But we don’t really have an alternative. If we want to have a future at all, if we want a happier and more successful world, we need science. And if we want science, we can’t ask its real customers, the future generations, to choose whether to pay for it. We need to work for the smiles on our colleagues faces and the checks from government grant agencies. And we need to do it carefully enough that at the end of the day, we still make a positive difference.

Truth Doesn’t Have to Break the (Word) Budget

Imagine you saw this headline:

Scientists Say They’ve Found the Missing 40 Percent of the Universe’s Matter

It probably sounds like they’re talking about dark matter, right? And if scientists found dark matter, that could be a huge discovery: figuring out what dark matter is made of is one of the biggest outstanding mysteries in physics. Still, maybe that 40% number makes you a bit suspicious…

Now, read this headline instead:

Astronomers Have Finally Found Most of The Universe’s Missing Visible Matter

Visible matter! Ah, what a difference a single word makes!

These are two articles, the first from this year and the second from 2017, talking about the same thing. Leave out dark matter and dark energy, and the rest of the universe is made of ordinary protons, neutrons, and electrons. We sometimes call that “visible matter”, but that doesn’t mean it’s easy to spot. Much of it lingers in threads of gas and dust between galaxies, making it difficult to detect. These two articles are about astronomers who managed to detect this matter in different ways. But while the articles cover the same sort of matter, one headline is a lot more misleading.

Now, I know science writing is hard work. You can’t avoid misleading your readers, if only a little, because you can never include every detail. Introduce too many new words and you’ll use up your “vocabulary budget” and lose your audience. I also know that headlines get tweaked by editors at the last minute to maximize “clicks”, and that news that doesn’t get enough “clicks” dies out, replaced by news that does.

But that second headline? It’s shorter than the first. They were able to fit that crucial word “visible” in, without breaking the budget. And while I don’t have the data, I doubt the first headline was that much more viral. They could have afforded to get this right, if they wanted to.

Read each article further, and you see the same pattern. The 2020 article does mention visible matter in the first sentence at least, so they don’t screw that one up completely. But another important detail never gets mentioned.

See, you might be wondering, if one of these articles is from 2017 and the other is from 2020, how are they talking about the same thing? If astronomers found this matter already in 2017, how did they find it again in 2020?

There’s a key detail that the 2017 article mentions and the 2020 article leaves out. Here’s a quote from the 2017 article, emphasis mine:

We now have our first solid piece of evidence that this matter has been hiding in the delicate threads of cosmic webbing bridging neighbouring galaxies, right where the models predicted.

This “missing” matter was expected to exist, was predicted by models to exist. It just hadn’t been observed yet. In 2017, astronomers detected some of this matter indirectly, through its effect on the Cosmic Microwave Background. In 2020, they found it more directly, through X-rays shot out from the gases themselves.

Once again, the difference is just a short phrase. By saying “right where the models predicted”, the 2017 article clears up an important point, that this matter wasn’t a surprise. And all it took was five words.

These little words and phrases make a big difference. If you’re writing about science, you will always face misunderstandings. But if you’re careful and clever, you can clear up the most obvious ones. With just a few well-chosen words, you can have a much better piece.

Discovering the Rules, Discovering the Consequences

Two big physics experiments consistently make the news. The Large Hadron Collider, or LHC, and the Laser Interferometer Gravitational-Wave Observatory, or LIGO. One collides protons, the other watches colliding black holes and neutron stars. But while this may make the experiments sound quite similar, their goals couldn’t be more different.

The goal of the LHC, put simply, is to discover the rules that govern reality. Should the LHC find a new fundamental particle, it will tell us something we didn’t know about the laws of physics, a newly discovered fact that holds true everywhere in the universe. So far, it has discovered the Higgs boson, and while that particular rule was expected we didn’t know the details until they were tested. Now physicists hope to find something more, a deviation from the Standard Model that hints at a new law of nature altogether.

LIGO, in contrast, isn’t really for discovering the rules of the universe. Instead, it discovers the consequences of those rules, on a grand scale. Even if we knew the laws of physics completely, we can’t calculate everything from those first principles. We can simulate some things, and approximate others, but we need experiments to tweak those simulations and test those approximations. LIGO fills that role. We can try to estimate how common black holes are, and how large, but LIGO’s results were still a surprise, suggesting medium-sized black holes are more common than researchers expected. In the future, gravitational wave telescopes might discover more of these kinds of consequences, from the shape of neutron stars to the aftermath of cosmic inflation.

There are a few exceptions for both experiments. The LHC can also discover the consequences of the laws of physics, especially when those consequences are very difficult to calculate, finding complicated arrangements of known particles, like pentaquarks and glueballs. And it’s possible, though perhaps not likely, that LIGO could discover something about quantum gravity. Quantum gravity’s effects are expected to be so small that these experiments won’t see them, but some have speculated that an unusually large effect could be detected by a gravitational wave telescope.

As scientists, we want to know everything we can about everything we find. We want to know the basic laws that govern the universe, but we also want to know the consequences of those laws, the story of how our particular universe came to be the way it is today. And luckily, we have experiments for both.

Halloween Post: Superstimuli for Physicists

For Halloween, this blog has a tradition of covering “the spooky side” of physics. This year, I’m bringing in a concept from biology to ask a spooky physics “what if?”

In the 1950’s, biologists discovered that birds were susceptible to a worryingly effective trick. By giving them artificial eggs larger and brighter than their actual babies, they found that the birds focused on the new eggs to the exclusion of their own. They couldn’t help trying to hatch the fake eggs, even if they were so large that they would fall off when they tried to sit on them. The effect, since observed in other species, became known as a supernormal stimulus, or superstimulus.

Can this happen to humans? Some think so. They worry about junk food we crave more than actual nutrients, or social media that eclipses our real relationships. Naturally, this idea inspires horror writers, who write about haunting music you can’t stop listening to, or holes in a wall that “fit” so well you’re compelled to climb in.

(And yes, it shows up in porn as well.)

But this is a physics blog, not a biology blog. What kind of superstimulus would work on physicists?

Abstruse goose knows what’s up

Well for one, this sounds a lot like some criticisms of string theory. Instead of a theory that just unifies some forces, why not unify all the forces? Instead of just learning some advanced mathematics, why not learn more, and more? And if you can’t be falsified by any experiment, well, all that would do is spoil the fun, right?

But it’s not just string theory you could apply this logic to. Astrophysicists study not just one world but many. Cosmologists study the birth and death of the entire universe. Particle physicists study the fundamental pieces that make up the fundamental pieces. We all partake in the euphoria of problem-solving, a perpetual rush where each solution leads to yet another question.

Do I actually think that string theory is a superstimulus, that astrophysics or particle physics is a superstimulus? In a word, no. Much as it might look that way from the news coverage, most physicists don’t work on these big, flashy questions. Far from being lured in by irresistible super-scale problems, most physicists work with tabletop experiments and useful materials. For those of us who do look up at the sky or down at the roots of the world, we do it not just because it’s compelling but because it has a good track record: physics wouldn’t exist if Newton hadn’t cared about the orbits of the planets. We study extremes because they advance our understanding of everything else, because they give us steam engines and transistors and change everyone’s lives for the better.

Then again, if I had fallen victim to a superstimulus, I’d say that anyway, right?

*cue spooky music*

What You Don’t Know, You Can Parametrize

In physics, what you don’t know can absolutely hurt you. If you ignore that planets have their own gravity, or that metals conduct electricity, you’re going to calculate a lot of nonsense. At the same time, as physicists we can’t possibly know everything. Our experiments are never perfect, our math never includes all the details, and even our famous Standard Model is almost certainly not the whole story. Luckily, we have another option: instead of ignoring what we don’t know, we can parametrize it, and estimate its effect.

Estimating the unknown is something we physicists have done since Newton. You might think Newton’s big discovery was the inverse-square law for gravity, but others at the time, like Robert Hooke, had also been thinking along those lines. Newton’s big discovery was that gravity was universal: that you need to know the effect of gravity, not just from the sun, but from all the other planets as well. The trouble was, Newton didn’t know how to calculate the motion of all of the planets at once (in hindsight, we know he couldn’t have). Instead, he estimated, using what he knew to guess how big the effect of what he didn’t would be. It was the accuracy of those guesses, not just the inverse square law by itself, that convinced the world that Newton was right.

If you’ve studied electricity and magnetism, you get to the point where you can do simple calculations with a few charges in your sleep. The world doesn’t have just a few charges, though: it has many charges, protons and electrons in every atom of every object. If you had to keep all of them in your calculations you’d never pass freshman physics, but luckily you can once again parametrize what you don’t know. Often you can hide those charges away, summarizing their effects with just a few numbers. Other times, you can treat materials as boundaries, and summarize everything beyond in terms of what happens on the edge. The equations of the theory let you do this, but this isn’t true for every theory: for the Navier-Stokes equation, which we use to describe fluids, it still isn’t known whether you can do this kind of trick.

Parametrizing what we don’t know isn’t just a trick for college physics, it’s key to the cutting edge as well. Right now we have a picture for how all of particle physics works, called the Standard Model, but we know that picture is incomplete. There are a million different theories you could write to go beyond the Standard Model, with a million different implications. Instead of having to use all those theories, physicists can summarize them all with what we call an effective theory: one that keeps track of the effect of all that new physics on the particles we already know. By summarizing those effects with a few parameters, we can see what they would have to be to be compatible with experimental results, ruling out some possibilities and suggesting others.

In a world where we never know everything, there’s always something that can hurt us. But if we’re careful and estimate what we don’t know, if we write down numbers and parameters and keep our options open, we can keep from getting burned. By focusing on what we do know, we can still manage to understand the world.

Congratulations to Roger Penrose, Reinhard Genzel, and Andrea Ghez!

The 2020 Physics Nobel Prize was announced last week, awarded to Roger Penrose for his theorems about black holes and Reinhard Genzel and Andrea Ghez for discovering the black hole at the center of our galaxy.

Of the three, I’m most familiar with Penrose’s work. People had studied black holes before Penrose, but only the simplest of situations, like an imaginary perfectly spherical star. Some wondered whether black holes in nature were limited in this way, if they could only exist under perfectly balanced conditions. Penrose showed that wasn’t true: he proved mathematically that black holes not only can form, they must form, in very general situations. He’s also worked on a wide variety of other things. He came up with “twistor space”, an idea intended for a new theory of quantum gravity that ended up as a useful tool for “amplitudeologists” like me to study particle physics. He discovered a set of four types of tiles such that if you tiled a floor with them the pattern would never repeat. And he has some controversial hypotheses about quantum gravity and consciousness.

I’m less familiar with Genzel and Ghez, but by now everyone should be familiar with what they found. Genzel and Ghez led two teams that peered into the center of our galaxy. By carefully measuring the way stars moved deep in the core, they figured out something we now teach children: that our beloved Milky Way has a dark and chewy center, an enormous black hole around which everything else revolves. These appear to be a common feature of galaxies, and many others have been shown to orbit black holes as well.

Like last year, I find it a bit odd that the Nobel committee decided to lump these two prizes together. Both discoveries concern black holes, so they’re more related than last year’s laureates, but the contexts are quite different: it’s not as if Penrose predicted the black hole in the center of our galaxy. Usually the Nobel committee avoids mathematical work like Penrose’s, except when it’s tied to a particular experimental discovery. It doesn’t look like anyone has gotten a Nobel prize for discovering that black holes exist, so maybe that’s the intent of this one…but Genzel and Ghez were not the first people to find evidence of a black hole. So overall I’m confused. I’d say that Penrose deserved a Nobel Prize, and that Genzel and Ghez did as well, but I’m not sure why they needed to split one with each other.

At “Antidifferentiation and the Calculation of Feynman Amplitudes”

I was at a conference this week, called Antidifferentiation and the Calculation of Feynman Amplitudes. The conference is a hybrid kind of affair: I attended via Zoom, but there were seven or so people actually there in the room (the room in question being at DESY Zeuthen, near Berlin).

The road to this conference was a bit of a roller-coaster. It was originally scheduled for early March. When the organizers told us they were postponing it, they seemed at the time a little overcautious…until the world proved me, and all of us, wrong. They rescheduled for October, and as more European countries got their infection rates down it looked like the conference could actually happen. We booked rooms at the DESY guest house, until it turned out they needed the space to keep the DESY staff socially distanced, and we quickly switched to booking at a nearby hotel.

Then Europe’s second wave hit. Cases in Denmark started to rise, so Germany imposed a quarantine on entry from Copenhagen and I switched to remote participation. Most of the rest of the participants did too, even several in Germany. For the few still there in person they have a variety of measures to stop infection, from fixed seats in the conference room to gloves for the coffee machine.

The content has been interesting. It’s an eclectic mix of review talks and talks on recent research, all focused on different ways to integrate (or, as one of the organizers emphasized, antidifferentiate) functions in quantum field theory. I’ve learned about the history of the field, and gotten a better feeling for the bottlenecks in some LHC-relevant calculations.

This week was also the announcement of the Physics Nobel Prize. I’ll do my traditional post on it next week, but for now, congratulations to Penrose, Genzel, and Ghez!

The Multiverse You Can Visit Is Not the True Multiverse

I don’t want to be the kind of science blogger who constantly complains about science fiction, but sometimes I can’t help myself.

When I blogged about zero-point energy a few weeks back, there was a particular book that set me off. Ian McDonald’s River of Gods depicts the interactions of human and AI agents in a fragmented 2047 India. One subplot deals with a power company pursuing zero-point energy, using an imagined completion of M theory called M* theory. This post contains spoilers for that subplot.

What frustrated me about River of Gods is that the physics in it almost makes sense. It isn’t just an excuse for magic, or a standard set of tropes. Even the name “M* theory” is extremely plausible, the sort of term that could get used for technical reasons in a few papers and get accidentally stuck as the name of our fundamental theory of nature. But because so much of the presentation makes sense, it’s actively frustrating when it doesn’t.

The problem is the role the landscape of M* theory plays in the story. The string theory (or M theory) landscape is the space of all consistent vacua, a list of every consistent “default” state the world could have. In the story, one of the AIs is trying to make a portal to somewhere else in the landscape, a world of pure code where AIs can live in peace without competing with humans.

The problem is that the landscape is not actually a real place in string theory. It’s a metaphorical mathematical space, a list organized by some handy coordinates. The other vacua, the other “default states”, aren’t places you can travel to, there just other ways the world could have been.

Ok, but what about the multiverse?

There are physicists out there who like to talk about multiple worlds. Some think they’re hypothetical, others argue they must exist. Sometimes they’ll talk about the string theory landscape. But to get a multiverse out of the string theory landscape, you need something else as well.

Two options for that “something else” exist. One is called eternal inflation, the other is the many-worlds interpretation of quantum mechanics. And neither lets you travel around the multiverse.

In eternal inflation, the universe is expanding faster and faster. It’s expanding so fast that, in most places, there isn’t enough time for anything complicated to form. Occasionally, though, due to quantum randomness, a small part of the universe expands a bit more slowly: slow enough for stars, planets, and maybe life. Each small part like that is its own little “Big Bang”, potentially with a different “default” state, a different vacuum from the string landscape. If eternal inflation is true then you can get multiple worlds, but they’re very far apart, and getting farther every second: not easy to visit.

The many-worlds interpretation is a way to think about quantum mechanics. One way to think about quantum mechanics is to say that quantum states are undetermined until you measure them: a particle could be spinning left or right, Schrödinger’s cat could be alive or dead, and only when measured is their state certain. The many-worlds interpretation offers a different way: by doing away with measurement, it instead keeps the universe in the initial “undetermined” state. The universe only looks determined to us because of our place in it: our states become entangled with those of particles and cats, so that our experiences only correspond to one determined outcome, the “cat alive branch” or the “cat dead branch”. Combine this with the string landscape, and our universe might have split into different “branches” for each possible stable state, each possible vacuum. But you can’t travel to those places, your experiences are still “just on one branch”. If they weren’t, many-worlds wouldn’t be an interpretation, it would just be obviously wrong.

In River of Gods, the AI manipulates a power company into using a particle accelerator to make a bubble of a different vacuum in the landscape. Surprisingly, that isn’t impossible. Making a bubble like that is a bit like what the Large Hadron Collider does, but on a much larger scale. When the Large Hadron Collider detected a Higgs boson, it had created a small ripple in the Higgs field, a small deviation from its default state. One could imagine a bigger ripple doing more: with vastly more energy, maybe you could force the Higgs all the way to a different default, a new vacuum in its landscape of possibilities.

Doing that doesn’t create a portal to another world, though. It destroys our world.

That bubble of a different vacuum isn’t another branch of quantum many-worlds, and it isn’t a far-off big bang from eternal inflation. It’s a part of our own universe, one with a different “default state” where the particles we’re made of can’t exist. And typically, a bubble like that spreads at the speed of light.

In the story, they have a way to stabilize the bubble, stop it from growing or shrinking. That’s at least vaguely believable. But it means that their “portal to another world” is just a little bubble in the middle of a big expensive device. Maybe the AI can live there happily…until the humans pull the plug.

Or maybe they can’t stabilize it, and the bubble spreads and spreads at the speed of light destroying everything. That would certainly be another way for the AI to live without human interference. It’s a bit less peaceful than advertised, though.

Which Things Exist in Quantum Field Theory

If you ever think metaphysics is easy, learn a little quantum field theory.

Someone asked me recently about virtual particles. When talking to the public, physicists sometimes explain the behavior of quantum fields with what they call “virtual particles”. They’ll describe forces coming from virtual particles going back and forth, or a bubbling sea of virtual particles and anti-particles popping out of empty space.

The thing is, this is a metaphor. What’s more, it’s a metaphor for an approximation. As physicists, when we draw diagrams with more and more virtual particles, we’re trying to use something we know how to calculate with (particles) to understand something tougher to handle (interacting quantum fields). Virtual particles, at least as you’re probably picturing them, don’t really exist.

I don’t really blame physicists for talking like that, though. Virtual particles are a metaphor, sure, a way to talk about a particular calculation. But so is basically anything we can say about quantum field theory. In quantum field theory, it’s pretty tough to say which things “really exist”.

I’ll start with an example, neutrino oscillation.

You might have heard that there are three types of neutrinos, corresponding to the three “generations” of the Standard Model: electron-neutrinos, muon-neutrinos, and tau-neutrinos. Each is produced in particular kinds of reactions: electron-neutrinos, for example, get produced by beta-plus decay, when a proton turns into a neutron, an anti-electron, and an electron-neutrino.

Leave these neutrinos alone though, and something strange happens. Detect what you expect to be an electron-neutrino, and it might have changed into a muon-neutrino or a tau-neutrino. The neutrino oscillated.

Why does this happen?

One way to explain it is to say that electron-neutrinos, muon-neutrinos, and tau-neutrinos don’t “really exist”. Instead, what really exists are neutrinos with specific masses. These don’t have catchy names, so let’s just call them neutrino-one, neutrino-two, and neutrino-three. What we think of as electron-neutrinos, muon-neutrinos, and tau-neutrinos are each some mix (a quantum superposition) of these “really existing” neutrinos, specifically the mixes that interact nicely with electrons, muons, and tau leptons respectively. When you let them travel, it’s these neutrinos that do the traveling, and due to quantum effects that I’m not explaining here you end up with a different mix than you started with.

This probably seems like a perfectly reasonable explanation. But it shouldn’t. Because if you take one of these mass-neutrinos, and interact with an electron, or a muon, or a tau, then suddenly it behaves like a mix of the old electron-neutrinos, muon-neutrinos, and tau-neutrinos.

That’s because both explanations are trying to chop the world up in a way that can’t be done consistently. There aren’t electron-neutrinos, muon-neutrinos, and tau-neutrinos, and there aren’t neutrino-ones, neutrino-twos, and neutrino-threes. There’s a mathematical object (a vector space) that can look like either.

Whether you’re comfortable with that depends on whether you think of mathematical objects as “things that exist”. If you aren’t, you’re going to have trouble thinking about the quantum world. Maybe you want to take a step back, and say that at least “fields” should exist. But that still won’t do: we can redefine fields, add them together or even use more complicated functions, and still get the same physics. The kinds of things that exist can’t be like this. Instead you end up invoking another kind of mathematical object, equivalence classes.

If you want to be totally rigorous, you have to go a step further. You end up thinking of physics in a very bare-bones way, as the set of all observations you could perform. Instead of describing the world in terms of “these things” or “those things”, the world is a black box, and all you’re doing is finding patterns in that black box.

Is there a way around this? Maybe. But it requires thought, and serious philosophy. It’s not intuitive, it’s not easy, and it doesn’t lend itself well to 3d animations in documentaries. So in practice, whenever anyone tells you about something in physics, you can be pretty sure it’s a metaphor. Nice describable, non-mathematical things typically don’t exist.