Category Archives: Life as a Physicist

Building the Railroad to Rigor

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As a kid who watched far too much educational television, I dimly remember learning about the USA’s first transcontinental railroad. Somehow, parts of the story stuck with me. Two companies built the railroad from different directions, one from California and the other from the middle of the country, aiming for a mountain in between. Despite the US Civil War happening around this time, the two companies built through, in the end racing to where the final tracks were laid with a golden spike.

I’m a theoretical physicist, so of course I don’t build railroads. Instead, I build new mathematical methods, ways to check our theories of particle physics faster and more efficiently. Still, something of that picture resonates with me.

You might think someone who develops new mathematical methods would be a mathematician, not a physicist. But while there are mathematicians who work on the problems I work on, their goals are a bit different. They care about rigor, about stating only things they can carefully prove. As such, they often need to work with simplified examples, “toy models” well-suited to the kinds of theorems they can build.

Physicists can be a bit messier. We don’t always insist on the same rigor the mathematicians do. This makes our results less reliable, but it makes our “toy models” a fair amount less “toy”. Our goal is to try to tackle questions closer to the actual real world.

What happens when physicists and mathematicians work on the same problem?

If the physicists worked alone, they might build and build, and end up with an answer that isn’t actually true. The mathematicians, keeping rigor in mind, would be safe in the truth of what they built, but might not end up anywhere near the physicists’ real-world goals.

Together, though, physicists and mathematicians can build towards each other. The physicists can keep their eyes on the mathematicians, correcting when they notice something might go wrong and building more and more rigor into their approach. The mathematicians can keep their eyes on the physicists, building more and more complex applications of their rigorous approaches to get closer and closer to the real world. Eventually, like the transcontinental railroad, the two groups meet: the mathematicians prove a rigorous version of the physicists’ approach, or the physicists adopt the mathematicians’ ideas and apply them to their own theories.

A sort of conference photo

In practice, it isn’t just two teams, physicists and mathematicians, building towards each other. Different physicists themselves work with different levels of rigor, aiming to understand different problems in different theories, and the mathematicians do the same. Each of us is building our own track, watching the other tracks build towards us on the horizon. Eventually, we’ll meet, and science will chug along over what we’ve built.

At Geometries and Special Functions for Physics and Mathematics in Bonn

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I’m at a workshop this week. It’s part of a series of “Bethe Forums”, cozy little conferences run by the Bethe Center for Theoretical Physics in Bonn.

You can tell it’s an institute for theoretical physics because they have one of these, but not a “doing room”

The workshop’s title, “Geometries and Special Functions for Physics and Mathematics”, covers a wide range of topics. There are talks on Calabi-Yau manifolds, elliptic (and hyper-elliptic) polylogarithms, and cluster algebras and cluster polylogarithms. Some of the talks are by mathematicians, others by physicists.

In addition to the talks, this conference added a fun innovative element, “my favorite problem sessions”. The idea is that a speaker spends fifteen minutes introducing their “favorite problem”, then the audience spends fifteen minutes discussing it. Some treated these sessions roughly like short talks describing their work, with the open directions at the end framed as their favorite problem. Others aimed broader, trying to describe a general problem and motivate interest in people of other sub-fields.

This was a particularly fun conference for me, because the seemingly distinct topics all connect in one way or another to my own favorite problem. In our “favorite theory” of N=4 super Yang-Mills, we can describe our calculations in terms of an “alphabet” of pieces that let us figure out predictions almost “by guesswork”. These alphabets, at least in the cases we know how to handle, turn out to correspond to mathematical structures called cluster algebras. If we look at interactions of six or seven particles, these cluster algebras are a powerful guide. For eight or nine, they still seem to matter, but are much harder to use.

For ten particles, though, things get stranger. That’s because ten particles is precisely where elliptic curves, and their related elliptic polylogarithms, show up. Things then get yet more strange, and with twelve particles or more we start seeing Calabi-Yau manifolds magically show up in our calculations.

We don’t know what an “alphabet” should look like for these Calabi-Yau manifolds (but I’m working on it). Because of that, we don’t know how these cluster algebras should appear.

In my view, any explanation for the role of cluster algebras in our calculations has to extend to these cases, to elliptic polylogarithms and Calabi-Yau manifolds. Without knowing how to frame an alphabet for these things, we won’t be able to solve the lingering mysteries that fill our field.

Because of that, “my favorite problem” is one of my biggest motivations, the question that drives a large chunk of what I do. It’s what’s made this conference so much fun, and so stimulating: almost every talk had something I wanted to learn.

Visiting CERN

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So, would you believe I’ve never visited CERN before?

I was at CERN for a few days this week, visiting friends and collaborators and giving an impromptu talk. Surprisingly, this is the first time I’ve been, a bit of an embarrassing admission for someone who’s ostensibly a particle physicist.

Despite that, CERN felt oddly familiar. The maze of industrial buildings and winding roads, the security gates and cards (and work-arounds for when you arrive outside of card-issuing hours, assisted by friendly security guards), the constant construction and remodeling, all of it reminded me of the times I visited SLAC during my PhD. This makes a lot of sense, of course: one accelerator is at least somewhat like another. But besides a visit to Fermilab for a conference several years ago, I haven’t been in many other places like that since then.

(One thing that might have also been true of SLAC and Fermilab but I never noticed: CERN buildings not only have evacuation instructions for the building in case of a fire, but also evacuation instructions for the whole site.)

CERN is a bit less “pretty” than SLAC on average, without the nice grassy area in the middle or the California sun that goes with it. It makes up for it with what seems like more in terms of outreach resources, including a big wooden dome of a mini-museum sponsored by Rolex, and a larger visitor center still under construction.

The outside, including a sculpture depicting the history of science with the Higgs boson discovery on the “cutting edge”
The inside. Bubbles on the ground contain either touchscreens or small objects (detectors, papers, a blackboard with the string theory genus expansion for some reason). Bubbles in the air were too high for me to check.

CERN hosts a variety of theoretical physicists doing various different types of work. I was hosted by the “QCD group”, but the string theorists just down the hall include a few people I know as well. The lounge had a few cardboard signs hidden under the table, leftovers of CERN’s famous yearly Christmas play directed by John Ellis.

It’s been a fun, if brief, visit. I’ll likely get to see a bit more this summer, when they host Amplitudes 2023. Until then, it was fun reconnecting with that “accelerator feel”.

All About the Collab

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Sometimes, some scientists work alone. But mostly, scientists collaborate. We team up, getting more done together than we could alone.

Over the years, I’ve realized that theoretical physicists like me collaborate in a bit of a weird way, compared to other scientists. Most scientists do experiments, and those experiments require labs. Each lab typically has one principal investigator, or “PI”, who hires most of the other people in that lab. For any given project, scientists from the lab will be organized into particular roles. Some will be involved in the planning, some not. Some will do particular tests, gather data, manage lab animals, or do statistics. The whole experiment is at least roughly planned out from the beginning, and everyone has their own responsibility, to the extent that journals will sometimes ask scientists to list everyone’s roles when they publish papers. In this system, it’s rare for scientists from two different labs to collaborate. Usually it happens for a reason: a lab needs a statistician for a particularly subtle calculation, or one lab must process a sample so another lab can analyze it.

In contrast, theoretical physicists don’t have labs. Our collaborators sometimes come from the same university, but often they’re from a different one, frequently even in a different country. The way we collaborate is less like other scientists, and more like artists.

Sometimes, theoretical physicists have collaborations with dedicated roles and a detailed plan. This can happen when there is a specific calculation that needs to be done, that really needs to be done right. Some of the calculations that go into making predictions at the LHC are done in this way. I haven’t been in a collaboration like that (though in retrospect one collaborator may have had something like that in mind).

Instead, most of the collaborations I’ve been in have been more informal. They tend to start with a conversation. We chat by the coffee machine, or after a talk, anywhere there’s a blackboard nearby. It starts with “I’ve noticed something odd”, or “here’s something I don’t understand”. Then, we jam. We go back and forth, doing our thing and building on each other. Sometimes this happens in person, a barrage of questions and doubts until we hammer out something solid. Sometimes we go back to our offices, to calculate and look up references. Coming back the next day, we compare results: what did you manage to show? Did you get what I did? If not, why?

I make this sound spontaneous, but it isn’t completely. That starting conversation can be totally unplanned, but usually one of the scientists involved is trying to make it happen. There’s a different way you talk when you’re trying to start a collaboration, compared to when you just want to talk. If you’re looking for a collaboration, you go into more detail. If the other person is on the same wavelength, you start using “we” instead of “I”, or you start suggesting plans of action: “you could do X, while I do Y”. If you just want someone’s opinion, or just want to show off, then your conversation is less detailed, and less personal.

This is easiest to do with our co-workers, but we do it with people from other universities too. Sometimes this happens at conferences, more often during short visits for seminars. I’ve been on almost every end of this. As a visitor, I’ve arrived to find my hosts with a project in mind. As a host, I’ve invited a visitor with the goal of getting them involved in a collaboration, and I’ve received a visitor who came with their own collaboration idea.

After an initial flurry of work, we’ll have a rough idea of whether the project is viable. If it is, things get a bit more organized, and we sort out what needs to be done and a rough idea of who will do it. While the early stages really benefit from being done in person, this part is easier to do remotely. The calculations get longer but the concepts are clear, so each of us can work by ourselves, emailing when we make progress. If we get confused again, we can always schedule a Zoom to sort things out.

Once things are close (but often not quite done), it’s time to start writing the paper. In the past, I used Dropbox for this: my collaborators shared a folder with a draft, and we’d pass “control” back and forth as we wrote and edited. Now, I’m more likely to use something built for this purpose. Git is a tool used by programmers to collaborate on code. It lets you roll back edits you don’t like, and merge edits from two people to make sure they’re consistent. For other collaborations I use Overleaf, an online interface for the document-writing language LaTeX that lets multiple people edit in real-time. Either way, this part is also more or less organized, with a lot of “can you write this section?” that can shift around depending on how busy people end up being.

Finally, everything comes together. The edits stabilize, everyone agrees that the paper is good (or at least, that any dissatisfaction they have is too minor to be worth arguing over). We send it to a few trusted friends, then a few days later up on the arXiv it goes.

Then, the cycle begins again. If the ideas are still clear enough, the same collaboration might keep going, planning follow-up work and follow-up papers. We meet new people, or meet up with old ones, and establish new collaborations as we go. Our fortunes ebb and flow based on the conversations we have, the merits of our ideas and the strengths of our jams. Sometimes there’s more, sometimes less, but it keeps bubbling up if you let it.

The Many Varieties of Journal Club

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Across disciplines, one tradition seems to unite all academics: the journal club. In a journal club, we gather together to discuss papers in academic journals. Typically, one person reads the paper in depth in advance, and comes prepared with a short presentation, then everyone else asks questions. Everywhere I’ve worked has either had, or aspired to have, a journal club, and every academic I’ve talked to recognizes the concept.

Beyond that universal skeleton, though, are a lot of variable details. Each place seems to interpret journal clubs just a bit differently. Sometimes a lot differently.

For example, who participates in journal clubs? In some places, journal clubs are a student thing, organized by PhD or Master’s students to get more experience with their new field. Some even have journal clubs as formal courses, for credit and everything. In other places, journal clubs are for everyone, from students up through the older professors.

What kind of papers? Some read old classic papers, knowing that without an excuse we’d never take the time to read them and would miss valuable insights. Some instead focus on the latest results, as a way to keep up with progress in the field.

Some variation is less intentional. Academics are busy, so it can be hard to find a volunteer to prepare a presentation on a paper every week. This leads journal clubs to cut corners, in once again a variety of ways. A journal club focused on the latest papers can sometimes only find volunteers interested in presenting their own work (which we usually already have a presentation prepared for). Sometimes this goes a step further, and the journal club becomes a kind of weekly seminar: a venue for younger visitors to talk about their work that’s less formal than a normal talk. Sometimes, instead of topic, the corner cut is preparation: people still discuss new papers, but instead of preparing a presentation they just come and discuss on the fly. This gets dangerous, because after a certain point people may stop reading the papers altogether, hoping that someone else will come having read it to explain it!

Journal clubs are tricky. Academics are curious, but we’re also busy and lazy. We know it would be good for us to discuss, to keep up with new papers or read the old classics… but actually getting organized, that’s another matter!

When Your Research Is a Cool Toy

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Merry Newtonmas, everyone!

In the US, PhD students start without an advisor. As they finish their courses, different research groups make their pitch, trying to get them to join. Some promise interesting puzzles and engaging mysteries, others talk about the importance of their work, how it can help society or understand the universe.

Thinking back to my PhD, there is one pitch I remember to this day. The pitch was from the computational astrophysics group, and the message was a simple one: “we blow up stars”.

Obviously, these guys didn’t literally blow up stars: they simulated supernovas. They weren’t trying to make some weird metaphysical argument, they didn’t believe their simulation was somehow the real thing. The point they were making, instead, was emotional: blowing up stars feels cool.

Scientists can be motivated by curiosity, fame, or altruism, and these are familiar things. But an equally important motivation is a sense of play. If your job is to build tiny cars for rats, some of your motivation has to be the sheer joy of building tiny cars for rats. If you simulate supernovas, then part of your motivation can be the same as my nephew hurling stuffed animals down the stairs: that joyful moment when you yell “kaboom!”

Probably, your motivation shouldn’t just be to play with a cool toy. You need some of those “serious” scientific motivations as well. But for those of you blessed with a job where you get to say “kaboom”, you have that extra powerful reason to get up in the morning. And for those of you just starting a scientific career, may you have some cool toys under your Newtonmas tree!

Confidence and Friendliness in Science

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I’ve seen three kinds of scientific cultures.

First, there are folks who are positive about almost everyone. Ask them about someone else’s lab, even a competitor, and they’ll be polite at worst, and often downright excited. Anyone they know, they’ll tell you how cool the work they’re doing is, how it’s important and valuable and worth doing. They might tell you they prefer a different approach, but they’ll almost never bash someone’s work.

I’ve heard this comes out of American culture, and I can kind of see it. There’s an attitude in the US that everything needs to be described as positively as possible. This is especially true in a work context. Negativity is essentially a death sentence, doled out extremely rarely: if you explicitly say someone or their work is bad, you’re trying to get them fired. You don’t do that unless someone really really deserves it.

That style of scientific culture is growing, but it isn’t universal. There’s still a big cultural group that is totally ok with negativity: as long as it’s directed at other people, anyway.

This scientific culture prides itself on “telling it like it is”. They’ll happily tell you about how everything everyone else is doing is bullshit. Sometimes, they claim their ideas are the only ways forward. Others will have a small number of other people who they trust, who have gained their respect in one way or another. This sort of culture is most stereotypically associated with Russians: a “Russian-style” seminar, for example, is one where the speaker is aggressively questioned for hours.

It may sound like those are the only two options, but there is a third. While “American-style” scientists don’t criticize anyone, and “Russian-style” scientists criticize everyone else, there are also scientists who criticize almost everyone, including themselves.

With a light touch, this culture can be one of the best. There can be a real focus on “epistemic humility”, on always being clear of how much we still don’t know.

However, it can be worryingly easy to spill past that light touch, into something toxic. When the criticism goes past humility and into a lack of confidence in your own work, you risk falling into a black hole, where nothing is going well and nobody has a way out. This kind of culture can spread, filling a workplace and infecting anyone who spends too long there with the conviction that nothing will ever measure up again.

If you can’t manage that light skeptical touch, then your options are American-style or Russian-style. I don’t think either is obviously better. Both have their blind spots: the Americans can let bad ideas slide to avoid rocking the boat, while the Russians can be blind to their own flaws, confident that because everyone else seems wrong they don’t need to challenge their own worldview.

You have one more option, though. Now that you know this, you can recognize each for what it is: not the one true view of the world, but just one culture’s approach to the truth. If you can do that, you can pick up each culture as you need, switching between them as you meet different communities and encounter different things. If you stay aware, you can avoid fighting over culture and discourse, and use your energy on what matters: the science.

Visiting the IAS

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I’m at the Institute for Advanced Study, or IAS, this week.

There isn’t a conference going on, but if you looked at the visitor list you’d be forgiven for thinking there was. We have talks in my subfield almost every day this week, two professors from my subfield here on sabbatical, and extra visitors on top of that.

The IAS is a bit of an odd place. Partly, that’s due to its physical isolation: tucked away in the woods behind Princeton, a half-hour’s walk from the nearest restaurant, it’s supposed to be a place for contemplation away from the hustle and bustle of the world.

Since the last time I visited they’ve added a futuristic new building, seen here out of my office window. The building is most notable for one wild promise: someday, they will serve dinner there.

Mostly, though, the weirdness of the IAS is due to the kind of institution it is.

Within a given country, most universities are pretty similar. Each may emphasize different teaching styles, and the US has a distinction between public and private, but (neglecting scammy for-profit universities), there are some commonalities of structure: both how they’re organized, and how they’re funded. Even between countries, different university systems have quite a bit of overlap.

The IAS, though, is not a university. It’s an independent institute. Neighboring Princeton supplies it with PhD students, but otherwise the IAS runs, and funds, itself.

There are a few other places like that around the world. The Perimeter Institute in Canada is also independent, and also borrows students from a neighboring university. CERN pools resources from several countries across Europe and beyond, Nordita from just the Nordic countries. Generalizing further, many countries have some sort of national labs or other nation-wide systems, from US Department of Energy labs like SLAC to Germany’s Max Planck Institutes.

And while universities share a lot in common, non-university institutes can be very different. Some are closely tied to a university, located inside university buildings with members with university affiliations. Others sit at a greater remove, less linked to a university or not linked at all. Some have their own funding, investments or endowments or donations, while others are mostly funded by governments, or groups of governments. I’ve heard that the IAS gets about 10% of its budget from the government, while Perimeter gets its everyday operating expenses entirely from the Canadian government and uses donations for infrastructure and the like.

So ultimately, the IAS is weird because every organization like it is weird. There are a few templates, and systems, but by and large each independent research organization is different. Understanding one doesn’t necessarily help at understanding another.

Fields and Scale

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I am a theoretical particle physicist, and every morning I check the arXiv.

arXiv.org is a type of website called a preprint server. It’s where we post papers before they are submitted to (and printed by) a journal. In practice, everything in our field shows up on arXiv, publicly accessible, before it appears anywhere else. There’s no peer review process on arXiv, the journals still handle that, but in our field peer review doesn’t often notice substantive errors. So in practice, we almost never read the journals: we just check arXiv.

And so every day, I check the arXiv. I go to the section on my sub-field, and I click on a link that lists all of the papers that were new that day. I skim the titles, and if I see an interesting paper I’ll read the abstract, and maybe download the full thing. Checking as I’m writing this, there were ten papers posted in my field, and another twenty “cross-lists” were posted in other fields but additionally classified in mine.

Other fields use arXiv: mathematicians and computer scientists and even economists use it in roughly the same way physicists do. For biology and medicine, though, there are different, newer sites: bioRxiv and medRxiv.

One thing you may notice is the different capitalization. When physicists write arXiv, the “X” is capitalized. In the logo, it looks like a Greek letter chi, thus saying “archive”. The biologists and medical researchers capitalize the R instead. The logo still has an X that looks like a chi, but positioned with the R it looks like the Rx of medical prescriptions.

Something I noticed, but you might not, was the lack of a handy link to see new papers. You can search medRxiv and bioRxiv, and filter by date. But there’s no link that directly takes you to the newest papers. That suggests that biologists aren’t using bioRxiv like we use arXiv, and checking the new papers every day.

I was curious if this had to do with the scale of the field. I have the impression that physics and mathematics are smaller fields than biology, and that much less physics and mathematics research goes on than medical research. Certainly, theoretical particle physics is a small field. So I might have expected arXiv to be smaller than bioRxiv and medRxiv, and I certainly would expect fewer papers in my sub-field than papers in a medium-sized subfield of biology.

On the other hand, arXiv in my field is universal. In biology, bioRxiv and medRxiv are still quite controversial. More and more people are using them, but not every journal accepts papers posted to a preprint server. Many people still don’t use these services. So I might have expected bioRxiv and medRxiv to be smaller.

Checking now, neither answer is quite right. I looked between November 1 and November 2, and asked each site how many papers were uploaded between those dates. arXiv had the most, 604 papers. bioRxiv had roughly half that many, 348. medRxiv had 97.

arXiv represents multiple fields, bioRxiv is “just” biology. Specializing, on that day arXiv had 235 physics papers, 135 mathematics papers, and 250 computer science papers. So each individual field has fewer papers than biology in this period.

Specializing even further, I can look at a subfield. My subfield, which is fairly small, had 20 papers between those dates. Cell biology, which I would expect to be quite a big subfield, had 33.

Overall, the numbers were weirdly comparable, with medRxiv unexpectedly small compared to both arXiv and bioRxiv. I’m not sure whether there are more biologists than physicists, but I’m pretty sure there should be more cell biologists than theoretical particle physicists. This suggests that many still aren’t using bioRxiv. It makes me wonder: will bioRxiv grow dramatically in future? Are the people running it ready for if it does?

No, PhD Students Are Not Just Cheap Labor

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Here’s a back-of-the-envelope calculation:

In 2019, there were 83,050 unionized graduate students in the US. Let’s assume these are mostly PhD students, since other graduate students are not usually university employees. I can’t find an estimate of the total number of PhD students in the US, but in 2019, 55,614 of them graduated. In 2020, the average US doctorate took 7.5 years to complete. That implies that 83,050/(55,614 x 7.5) = about one-fifth of PhD students in the US are part of a union.

That makes PhD student unions common, but not the majority. It means they’re not unheard of and strange, but a typical university still isn’t unionized. It’s the sweet spot for controversy. It leads to a lot of dumb tweets.

I saw one such dumb tweet recently, from a professor arguing that PhD students shouldn’t unionize. The argument was that if PhD students were paid more, then professors would prefer to hire postdocs, researchers who already have a doctoral degree.

(I won’t link to the tweet, in part because this person is probably being harassed enough already.)

I don’t know how things work in this professor’s field. But the implication, that professors primarily take on PhD students because they’re cheaper, not only doesn’t match my experience: it also just doesn’t make very much sense.

Imagine a neighborhood where the children form a union. They decide to demand a higher allowance, and to persuade any new children in the neighborhood to follow their lead.

Now imagine a couple in that neighborhood, deciding whether to have a child. Do you think that they might look at the fees the “children’s union” charges, and decide to hire an adult to do their chores instead?

Maybe there’s a price where they’d do that. If neighborhood children demanded thousands of dollars in allowance, maybe the young couple would decide that it’s too expensive to have a child. But a small shift is unlikely to change things very much: people have kids for many reasons, and those reasons don’t usually include cheap labor.

The reasons professors take on PhD students are similar to the reasons parents decide to have children. Some people have children because they want a legacy, something of theirs that survives to the next generation. For professors, PhD students are our legacy, our chance to raise someone on our ideas and see how they build on them. Some people have children because they love the act of child-raising: helping someone grow and learn about the world. The professors who take on students like taking on students: teaching is fun, after all.

That doesn’t mean there won’t be cases “on the margin”, where a professor finds they can’t afford a student they previously could. (And to be fair to the tweet I’m criticizing, they did even use the word “marginal”.) But they would have to be in a very tight funding situation, with very little flexibility.

And even for situations like that, long-term, I’m not sure anything would change.

I did my PhD in the US. I was part of a union, and in part because of that (though mostly because I was in a physics department), I was paid relatively decently for a PhD student. Relatively decently is still not that great, though. This was the US, where universities still maintain the fiction that PhD students only work 20 hours a week and pay proportionate to that, and where salaries in a university can change dramatically from student to postdoc to professor.

One thing I learned during my PhD is that despite our low-ish salaries, we cost our professors about as much as postdocs did. The reason why is tuition: PhD students don’t pay their own tuition, but that tuition still exists, and is paid by the professors who hire those students out of their grants. A PhD salary plus a PhD tuition ended up roughly equal to a postdoc salary.

Now, I’m working in a very different system. In a Danish university, wages are very flat. As a postdoc, a nice EU grant put me at almost the same salary as the professors. As a professor, my salary is pretty close to that of one of the better-paying schoolteacher jobs.

At the same time, tuition is much less relevant. Undergraduates don’t pay tuition at all, so PhD tuition isn’t based on theirs. Instead, it’s meant to cover costs of the PhD program as a whole.

I’ve filled out grants here in Denmark, so I know how much PhD students cost, and how much postdocs cost. And since the situation is so different, you might expect a difference here too.

There isn’t one. Hiring a PhD student, salary plus tuition, costs about as much as hiring a postdoc.

Two very different systems, with what seem to be very different rules, end up with the same equation. PhD students and postdocs cost about as much as each other, even if every assumption that you think would affect the outcome turns out completely different.

This is why I expect that, even if PhD students get paid substantially more, they still won’t end up that out of whack with postdocs. There appears to be an iron law of academic administration keeping these two numbers in line, one that holds across nations and cultures and systems. The proportion of unionized PhD students in the US will keep working its way upwards, and I don’t expect it to have any effect on whether professors take on PhDs.