Category Archives: Life as a Physicist

ArXiv to Leave Cornell

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Yes, I’m late to the party on this one.

A few weeks ago, arXiv.org announced that it will be leaving Cornell, the university that currently manages it, and establishing its own nonprofit.

arXiv is a crucial part of the infrastructure for physics, mathematics, computer science, and a few related fields. Researchers post papers to arXiv as what are called “preprints” before the papers are submitted to a journal. In practice, nobody ends up reading the journal versions: the arXiv is free to access, and typically reflects better what the paper’s authors want the paper to look like. So in practice, arXiv is how researchers in these fields communicate, which makes its role enormously important.

If you’re from another field, you might wonder how something like arXiv is financially sustainable. The answer is that it works better than you’d think, but not perfectly. They’ve been supported by philanthropy, in addition to Cornell, and while there have apparently been budget shortfalls and drama behind the scenes, But nonetheless, arXiv has stayed in continuous operation since 1991.

The move to an independent nonprofit is supposed to make it easier for arXiv to get philanthropic funding, which otherwise needed to be filtered through Cornell in ways that were sometimes opaque or didn’t give donors the control they wanted.

While it wasn’t mentioned in the announcements, I suspect another motivation is security. Universities are fixed in place, and that makes them easier to pressure. For an organization that wants to process scientific output in an unbiased way, the link to Cornell represented a vulnerability. It’s not a vulnerability that has mattered yet, and likely didn’t seem like it would ever matter. But it wouldn’t surprise me if they’re more worried now that someone might try to pressure Cornell in order to change how arXiv operates. For critical scientific infrastructure, it’s important to be as independent of those kinds of pressure as possible.

The Twitter of Physics

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The paper I talked about last week was frustratingly short. That’s not because the authors were trying to hide anything, or because they were lazy. It’s just that these days, that’s how the game is played.

Twitter started out with a fun gimmick: all posts had to be under 140 characters. The restriction inspired some great comedy, trying to pack as much humor as possible into a bite-sized format. Then, Twitter somehow became the place for journalists to discuss the news, tech people to discuss the industry, and politicians to discuss politics. Now, the length limit fuels conflict, an endless scroll of strong opinions without space for nuance.

Physics has something like this too.

In the 1950’s, it was hard for scientists to get the word out quickly about important results. The journal Physical Review had a trick: instead of normal papers, they’d accept breaking news in the form of letters to the editor, which they could publish more quickly than the average paper. In 1958, editor Samuel Goudsmit founded a new journal, Physical Review Letters (or PRL for short), that would publish those letters all in one place, enforcing a length limit to make them faster to process.

The new journal was a hit, and soon played host to a series of breakthrough results, as scientists chose it as a way to get their work out fast. That popularity created a problem, though. As PRL’s reputation grew, physicists started trying to publish there not because their results needed to get out fast, but because just by publishing in PRL, their papers would be associated with all of the famous breakthroughs the journal had covered. Goudsmit wrote editorials trying to slow this trend, but to no avail.

Now, PRL is arguably the most prestigious journal in physics, hosting over a quarter of Nobel prize-winning work. Its original motivation is no longer particularly relevant: the journal is not all that much faster than other journals in its area, if at all, and is substantially slower than the preprint server arXiv, which is where physicists actually read papers in practice.

The length limit has changed over the years, but not dramatically. It now sits at 3,750 words, typically allowing a five-or-six page article in tight two-column text.

If you see a physics paper on arXiv.org that fits the format, it’s almost certainly aimed at PRL, or one of the journals with similar policies that it inspired. It means the authors think their work is cool enough to hang out with a quarter of all Nobel-winning results, or at least would like it to be.

And that, in turn, means that anyone who wants to claim that prestige has to be concise. They have to leave out details (often, saving them for a later publication in a less-renowned journal). The results have to lean, by the journal’s nature, more to physicist-clickbait and a cleaned-up story than to anything their colleagues can actually replicate.

Is it fun? Yeah, I had some PRLs in my day. It’s a rush, shining up your work as far as it can go, trimming down complexities into six pages of essentials.

But I’m not sure it’s good for the field.

Most Academics Don’t Choose Their Specialty

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It’s there in every biography, and many interviews: the moment the scientist falls in love with an idea. It can be a kid watching ants in the backyard, a teen peering through a telescope, or an undergrad seeing a heart cell beat on a slide. It’s a story so common that it forms the heart of the public idea of a scientist: not just someone smart enough to understand the world, but someone passionate enough to dive in to their one particular area above all else. It’s easy to think of it as a kind of passion most people never get to experience.

And it does happen, sometimes. But it’s a lot less common than you’d think.

I first started to suspect this as a PhD student. In the US, getting accepted into a PhD program doesn’t guarantee you an advisor to work with. You have to impress a professor to get them to spend limited time and research funding on you. In practice, the result was the academic analog of the dating scene. Students looked for who they might have a chance with, based partly on interest but mostly on availability and luck and rapport, and some bounced off many potential mentors before finding one that would stick.

Then, for those who continued to postdoctoral positions, the same story happened all over again. Now, they were applying for jobs, looking for positions where they were qualified enough and might have some useful contacts, with interest into the specific research topic at best a distant third.

Working in the EU, I’ve seen the same patterns, but offset a bit. Students do a Master’s thesis, and the search for a mentor there is messy and arbitrary in similar ways. Then for a PhD, they apply for specific projects elsewhere, and as each project is its own funded position the same job search dynamics apply.

The picture only really clicked for me, though, when I started doing journalism.

Nowadays, I don’t do science, I interview people about it. The people I interview are by and large survivors: people who got through the process of applying again and again and now are sitting tight in an in-principle permanent position. They’re people with a lot of freedom to choose what to do.

And so I often ask for that reason, that passion, that scientific love at first sight moment: why do you study what you do? It’s a story that audiences love, and thus that editors love, it’s always a great way to begin a piece.

But surprisingly often, I get an unromantic answer. Why study this? Because it was available. Because in the Master’s, that professor taught the intro course. Because in college, their advisor had contacts with that lab to arrange a study project. Because that program accepted people from that country.

And I’ve noticed how even the romantic answers tend to be built on the unromantic ones. The professors who know how to weave a story, to self-promote and talk like a politician, they’ll be able to tell you about falling in love with something, sure. But if you read between the lines, you’ll notice where their anecdotes fall, how they trace a line through the same career steps that less adroit communicators admit were the real motivation.

There’s been times I’ve thought that my problem was a lack of passion, that I wasn’t in love the same way other scientists were in love. I’ve even felt guilty, that I took resources and positions from people who were. There is still some truth in that guilt, I don’t think I had the same passion for my science as most of my colleagues.

But I appreciate more now, that that passion is in part a story. We don’t choose our specialty, making some grand agentic move. Life chooses for us. And the romance comes in how you tell that story, after the fact.

How Much Academic Attrition Is Too Much?

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Have you seen “population pyramids“? They’re diagrams that show snapshots of a population, how many people there are of each age. They can give you an intuition for how a population is changing, and where the biggest hurdles are to survival.

I wonder what population pyramids would look like for academia. In each field and subfield, how many people are PhD students, postdocs, and faculty?

If every PhD student was guaranteed to become faculty, and the number of faculty stayed fixed, you could roughly estimate what this pyramid would have to look like. An estimate for the US might take an average 7-year PhD, two postdoc positions at 3 years each, followed by a 30-year career as faculty, and estimate the proportions of each stage based on proportions of each scholar’s life. So you’d have roughly one PhD student per four faculty, and one postdoc per five. In Europe, with three-year PhDs, the proportion of PhD students decreases further, and in a world where people are still doing at least two postdocs you expect significantly more postdocs than PhDs.

Of course, the world doesn’t look like that at all, because the assumptions are wrong.

The number of faculty doesn’t stay fixed, for one. When population is growing in the wider world, new universities open in new population centers, and existing universities find ways to expand. When population falls, enrollments shrink, and universities cut back.

But this is a minor perturbation compared to the much more obvious difference: most PhD students do not stay in academia. A single professor may mentor many PhDs at the same time, and potentially several postdocs. Most of those people aren’t staying.

You can imagine someone trying to fix this by fiat, setting down a fixed ratio between PhD students, postdocs, and faculty. I’ve seen partial attempts at this. When I applied for grants at the University of Copenhagen, I was told I had to budget at least half of my hires as PhD students, not postdocs, which makes me wonder if they were trying to force careers to default to one postdoc position, rather than two. More likely, they hadn’t thought about it.

Zero attrition doesn’t really make sense, anyway. Some people are genuinely better off leaving: they made a mistake when they started, or they changed over time. Sometimes new professions arise, and the best way in is from an unexpected direction. I’ve talked to people who started data science work in the early days, before there really were degrees in it, who felt a physics PhD had been the best route possible to that world. Similarly, some move into policy, or academic administration, or found a startup. And if we think there are actually criteria to choose better or worse academics (which I’m a bit skeptical of), then presumably some people are simply not good enough, and trying to filter them out earlier is irresponsible when they still don’t have enough of a track record to really judge.

How much attrition should be there is the big question, and one I don’t have an answer for. In academia, when so much of these decisions are made by just a few organizations, it seems like a question that someone should have a well-considered answer to. But so far, it’s unclear to me that anyone does.

It also makes me think, a bit, about how these population pyramids work in industry. There there is no overall control. Instead, there’s a web of incentives, many of them decades-delayed from the behavior they’re meant to influence, leaving each individual to try to predict as well as they can. If companies only hire senior engineers, no-one gets a chance to start a career, and the population of senior engineers dries up. Eventually, those companies have to settle for junior engineers. (Or, I guess, ex-academics.) It sounds like it should lead to the kind of behavior biologists model in predators and prey, wild swings in population modeled by a differential equation. But maybe there’s something that tamps down those wild swings.

A Paper With a Bluesky Account

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People make social media accounts for their pets. Why not a scientific paper?

Anthropologist Ed Hagen made a Bluesky account for his recent preprint, “Menopause averted a midlife energetic crisis with help from older children and parents: A simulation study.” The paper’s topic itself is interesting (menopause is surprisingly rare among mammals, he has a plausible account as to why), but not really the kind of thing I cover here.

Rather, it’s his motivation that’s interesting. Hagen didn’t make the account out of pure self-promotion or vanity. Instead, he’s promoting it as a novel approach to scientific publishing. Unlike Twitter, Bluesky is based on an open, decentralized protocol. Anyone can host an account compatible with Bluesky on their own computer, and anyone with the programming know-how can build a computer program that reads Bluesky posts. That means that nothing actually depends on Bluesky, in principle: the users have ultimate control.

Hagen’s idea, then, is that this could be a way to fulfill the role of scientific journals without channeling money and power to for-profit publishers. If each paper is hosted on a scientist’s own site, the papers can link to each other via following each other. Scientists on Bluesky can follow or like the paper, or comment on and discuss it, creating a way to measure interest from the scientific community and aggregate reviews, two things journals are supposed to cover.

I must admit, I’m skeptical. The interface really seems poorly-suited for this. Hagen’s paper’s account is called @menopause-preprint.edhagen.net. What happens when he publishes another paper on menopause, what will he call it? How is he planning to keep track of interactions from other scientists with an account for every single paper, won’t swapping between fifteen Bluesky accounts every morning get tedious? Or will he just do this with papers he wants to promote?

I applaud the general idea. Decentralized hosting seems like a great way to get around some of the problems of academic publishing. But this will definitely take a lot more work, if it’s ever going to be viable on a useful scale.

Still, I’ll keep an eye on it, and see if others give it a try. Stranger things have happened.

Academia Tracks Priority, Not Provenance

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A recent Correspondence piece in Nature Machine Intelligence points at an issue with using LLMs to write journal articles. LLMs are trained on enormous amounts of scholarly output, but the result is quite opaque: it is usually impossible to tell which sources influence a specific LLM-written text. That means that when a scholar uses an LLM, they may get a result that depends on another scholar’s work, without realizing it or documenting it. The ideas’ provenance gets lost, and the piece argues this is damaging, depriving scholars of credit and setting back progress.

It’s a good point. Provenance matters. If we want to prioritize funding for scholars whose ideas have the most impact, we need a way to track where ideas arise.

However, current publishing norms make essentially no effort to do this. Academic citations are not used to track provenance, and they are not typically thought of as tracking provenance. Academic citations track priority.

Priority is a central value in scholarship, with a long history. We give special respect to the first person to come up with an idea, make an observation, or do a calculation, and more specifically, the first person to formally publish it. We do this even if the person’s influence was limited, and even if the idea was rediscovered independently later on. In an academic context, being first matters.

In a paper, one is thus expected to cite the sources that have priority, that came up with an idea first. Someone who fails to do so will get citation request emails, and reviewers may request revisions to the paper to add in those missing citations.

One may also cite papers that were helpful, even if they didn’t come first. Tracking provenance in this way can be nice, a way to give direct credit to those who helped and point people to useful resources. But it isn’t mandatory in the same way. If you leave out a secondary source and your paper doesn’t use anything original to that source (like new notation), you’re much less likely to get citation request emails, or revision requests from reviewers. Provenance is just much lower priority.

In practice, academics track provenance in much less formal ways. Before citations, a paper will typically have an Acknowledgements section, where the authors thank those who made the paper possible. This includes formal thanks to funding agencies, but also informal thanks for “helpful discussions” that don’t meet the threshold of authorship.

If we cared about tracking provenance, those acknowledgements would be crucial information, an account of whose ideas directly influenced the ideas in the paper. But they’re not treated that way. No-one lists the number of times they’ve been thanked for helpful discussions on their CV, or in a grant application, no-one considers these discussions for hiring or promotion. You can’t look them up on an academic profile or easily graph them in a metascience paper. Unlike citations, unlike priority, there is essentially no attempt to measure these tracks of provenance in any organized way.

Instead, provenance is often the realm of historians or history-minded scholars, writing long after the fact. For academics, the fact that Yang and Mills published their theory first is enough, we call it Yang-Mills theory. For those studying the history, the story is murkier: it looks like Pauli came up with the idea first, and did most of the key calculations, but didn’t publish when it looked to him like the theory couldn’t describe the real world. What’s more, there is evidence suggesting that Yang knew about Pauli’s result, that he had read a letter from him on the topic, that the idea’s provenance goes back to Pauli. But Yang published, Pauli didn’t. And in the way academia has worked over the last 75 years, that claim of priority is what actually mattered.

Should we try to track provenance? Maybe. Maybe the emerging ubiquitousness of LLMs should be a wakeup call, a demand to improve our tracking of ideas, both in artificial and human neural networks. Maybe we need to demand interpretability from our research tools, to insist that we can track every conclusion back to its evidence for every method we employ, to set a civilizational technological priority on the accurate valuation of information.

What we shouldn’t do, though, is pretend that we just need to go back to what we were doing before.

Energy Is That Which Is Conserved

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In school, kids learn about different types of energy. They learn about solar energy and wind energy, nuclear energy and chemical energy, electrical energy and mechanical energy, and potential energy and kinetic energy. They learn that energy is conserved, that it can never be created or destroyed, but only change form. They learn that energy makes things happen, that you can use energy to do work, that energy is different from matter.

Some, between good teaching and good students, manage to impose order on the jumble of concepts and terms. Others end up envisioning the whole story a bit like Pokemon, with different types of some shared “stuff”.

Energy isn’t “stuff”, though. So what is it? What relates all these different types of things?

Energy is something which is conserved.

The mathematician Emmy Noether showed that, when the laws of physics are symmetrical, they come with a conserved quantity. For example, because the laws of the physics are the same from place to place, momentum is conserved. Similarly, because the laws of physics are the same from one time to another, Noether’s theorem states that there must be some quantity related to time, some number we can calculate, that is conserved, even as other things change. We call that number energy.

If energy is that simple, why are there all those types?

Energy is a number we can calculate. It’s a number we can calculate for different things. If you have a detailed description of how something in physics works, you can use that description to calculate that thing’s energy. In school, you memorize formulas like \frac{1}{2}m v^2 and m g h. These are all formulas that, with a bit more knowledge, you could calculate. They are the things that, for a something that meets the conditions, are conserved. They are things that, according to Noether’s theorem, stay the same.

Because of this, you shouldn’t think of energy as a substance, or a fuel. Energy is something we can do: we physicists, and we students of physics. We can take a physical system, and see what about it ought to be conserved. Energy is an action, a calculation, a conceptual tool that can be used to make predictions.

Most things are, in the end.

Mandatory Dumb Acronyms

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Sometimes, the world is silly for honest, happy reasons. And sometimes, it’s silly for reasons you never even considered.

Scientific projects often have acronyms, some of which are…clever, let’s say. Astronomers are famous for acronyms. Read this list, and you can find examples from 2D-FRUTTI and ABRACADABRA to WOMBAT and YORIC. Some of these aren’t even “really” acronyms, using letters other than the beginning of each word, multiple letters from a word, or both. (An egregious example from that list: VESTALE from “unVEil the darknesS of The gAlactic buLgE”.)

But here’s a pattern you’ve probably not noticed. I suggest that you should see more of these…clever…acronyms in projects in Europe, and they should show up in a wider range of fields, not just astronomy. And the reason why, is the European Research Council.

In the US, scientific grants are spread out among different government agencies. Typical grants are small, the kind of thing that lets a group share a postdoc every few years, with different types of grants covering projects of different scales.

The EU, instead, has the European Research Council, or ERC, with a flagship series of grants covering different career stages: Starting, Consolidator, and Advanced. Unlike most US grants, these are large (supporting multiple employees over several years), individual (awarded to a single principal investigator, not a collaboration) and general (the ERC uses the same framework across multiple fields, from physics to medicine to history).

That means there are a lot of medium-sized research projects in Europe that are funded by an ERC grant. And each of them are required to have an acronym.

Why? Who knows? “Acronym” is simply one of the un-skippable entries in the application forms, with a pre-set place of honor in their required grant proposal format. Nobody checks whether it’s a “real acronym”, so in practice it often isn’t, turning into some sort of catchy short name with “acronym vibes”. It, like everything else on these forms, is optimized to catch the attention of a committee of scientists who really would rather be doing something else, often discussed and refined by applicants’ mentors and sometimes even dedicated university staff.

So if you run into a scientist in Europe who proudly leads a group with a cutesy, vaguely acronym-adjacent name? And you keep running into these people?

It’s not a coincidence, and it’s not just scientists’ sense of humor. It’s the ERC.

What You’re Actually Scared of in Impostor Syndrome

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Academics tend to face a lot of impostor syndrome. Something about a job with no clear criteria for success, where you could always in principle do better and you mostly only see the cleaned-up, idealized version of others’ work, is a recipe for driving people utterly insane with fear.

The way most of us talk about that fear, it can seem like a cognitive bias, like a failure of epistemology. “Competent people think they’re less competent than they are,” the less-discussed half of the Dunning-Kruger effect.

(I’ve talked about it that way before. And, in an impostor-syndrome-inducing turn of events, I got quoted in a news piece in Nature about it.)

There’s something missing in that perspective, though. It doesn’t really get across how impostor syndrome feels. There’s something very raw about it, something that feels much more personal and urgent than an ordinary biased self-assessment.

To get at the core of it, let me ask a question: what happens to impostors?

The simple answer, the part everyone will admit to, is to say they stop getting grants, or stop getting jobs. Someone figures out they can’t do what they claim, and stops choosing them to receive limited resources. Pretty much anyone with impostor syndrome will say that they fear this: the moment that they reach too far, and the world decides they aren’t worth the money after all.

In practice, it’s not even clear that that happens. You might have people in your field who are actually thought of as impostors, on some level. People who get snarked about behind their back, people where everyone rolls their eyes when they ask a question at a conference and the question just never ends. People who are thought of as shiny storytellers without substance, who spin a tale for journalists but aren’t accomplishing anything of note. Those people…aren’t facing consequences at all, really! They keep getting the grants, they keep finding the jobs, and the ranks of people leaving for industry are instead mostly filled with those you respect.

Instead, I think what we fear when we feel impostor syndrome isn’t the obvious consequence, or even the real consequence, but something more primal. Primatologists and psychologists talk about our social brain, and the role of ostracism. They talk about baboons who piss off the alpha and get beat up and cast out of the group, how a social animal on their own risks starvation and becomes easy prey for bigger predators.

I think when we wake up in a cold sweat remembering how we had no idea what that talk was about, and were too afraid to ask, it’s a fear on that level that’s echoing around in our heads. That the grinding jags of adrenaline, the run-away-and-hide feeling of never being good enough, the desperate unsteadiness of trying to sound competent when you’re sure that you’re not and will get discovered at any moment…that’s not based on any realistic fears about what would happen if you got caught. That’s your monkey-brain, telling you a story drilled down deep by evolution.

Does that help? I’m not sure. If you manage to tell your inner monkey that it won’t get eaten by a lion if its friends stop liking it, let me know!

Publishing Isn’t Free, but SciPost Makes It Cheaper

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I’ve mentioned SciPost a few times on this blog. They’re an open journal in every sense you could think of: diamond open-access scientific publishing on an open-source platform, run with open finances. They even publish their referee reports. They’re aiming to cover not just a few subjects, but a broad swath of academia, publishing scientists’ work in the most inexpensive and principled way possible and challenging the dominance of for-profit journals.

And they’re struggling.

SciPost doesn’t charge university libraries for access, they let anyone read their articles for free. And they don’t charge authors Article Processing Charges (or APCs), they let anyone publish for free. All they do is keep track of which institutions those authors are affiliated with, calculate what fraction of their total costs comes from them, and post it in a nice searchable list on their website.

And amazingly, for the last nine years, they’ve been making that work.

SciPost encourages institutions to pay their share, mostly by encouraging authors to bug their bosses until they do. SciPost will also quite happily accept more than an institution’s share, and a few generous institutions do just that, which is what has kept them afloat so far. But since nothing compels anyone to pay, most organizations simply don’t.

From an economist’s perspective, this is that most basic of problems, the free-rider problem. People want scientific publication to be free, but it isn’t. Someone has to pay, and if you don’t force someone to do it, then the few who pay will be exploited by the many who don’t.

There’s more worth saying, though.

First, it’s worth pointing out that SciPost isn’t paying the same cost everyone else pays to publish. SciPost has a stripped-down system, without any physical journals or much in-house copyediting, based entirely on their own open-source software. As a result, they pay about 500 euros per article. Compare this to the fees negotiated by particle physics’ SCOAP3 agreement, which average to closer to 1000 euros, and realize that those fees are on the low end: for-profit journals tend to make their APCs higher in order to, well, make a profit.

(By the way, while it’s tempting to think of for-profit journals as greedy, I think it’s better to think of them as not cost-effective. Profit is an expense, like the interest on a loan: a payment to investors in exchange for capital used to set up the business. The thing is, online journals don’t seem to need that kind of capital, especially when they’re based on code written by academics in their spare time. So they can operate more cheaply as nonprofits.)

So when an author publishes in SciPost instead of a journal with APCs, they’re saving someone money, typically their institution or their grant. This would happen even if their institution paid their share of SciPost’s costs. (But then they would pay something rather than nothing, hence free-rider problem.)

If an author instead would have published in a closed-access journal, the kind where you have to pay to read the articles and university libraries pay through the nose to get access? Then you don’t save any money at all, your library still has to pay for the journal. You only save money if everybody at the institution stops using the journal. This one is instead a collective action problem.

Collective action problems are hard, and don’t often have obvious solutions. Free-rider problems do suggest an obvious solution: why not just charge?

In SciPost’s case, there are philosophical commitments involved. Their desire to attribute costs transparently and equally means dividing a journal’s cost among all its authors’ institutions, a cost only fully determined at the end of the year, which doesn’t make for an easy invoice.

More to the point, though, charging to publish is directly against what the Open Access movement is about.

That takes some unpacking, because of course, someone does have to pay. It probably seems weird to argue that institutions shouldn’t have to pay charges to publish papers…instead, they should pay to publish papers.

SciPost itself doesn’t go into detail about this, but despite how weird it sounds when put like I just did, there is a difference. Charging a fee to publish means that anyone who publishes needs to pay a fee. If you’re working in a developing country on a shoestring budget, too bad, you have to pay the fee. If you’re an amateur mathematician who works in a truck stop and just puzzled through something amazing, too bad, you have to pay the fee.

Instead of charging a fee, SciPost asks for support. I have to think that part of the reason is that they want some free riders. There are some people who would absolutely not be able to participate in science without free riding, and we want their input nonetheless. That means to support them, others need to give more. It means organizations need to think about SciPost not as just another fee, but as a way they can support the scientific process as a whole.

That’s how other things work, like the arXiv. They get support from big universities and organizations and philanthropists, not from literally everyone. It seems a bit weird to do that for a single scientific journal among many, though, which I suspect is part of why institutions are reluctant to do it. But for a journal that can save money like SciPost, maybe it’s worth it.