Learning and AI/LLMs - Why do we need to know or teach anything anymore?

The fall semester is about to begin at my university, and I'm going to be teaching undergraduate statistical and thermal physics.  This is a course I've taught before, last full term in 2019, and the mass availability of large language models and generative AI tools have changed the world in the interim.  We've all seen the headlines and articles about how some of these systems can be very good at solving traditional homework and exam problems.  Many of these tools are capable of summarizing written material and writing essays that are very readable.  Higher education is wrestling with the essential question:  What is the right working relationship between students, teachers, and these tools, one that benefits and actually educates students (both about subject matter and the use of these tools)?  Personalized individual AI tutoring seems like it could be great for teaching huge numbers of people.  Conversely, if all we are doing is teaching students to copy-paste assignments into the homework-answer-machine, clearly we are failing students at multiple levels.  

The quote in the image here (from Kathy Hepinstall Parks) is one that I came across this week that originates in the FAQ from a writers workshop.  For my purposes I could paraphrase:  Why should we learn physics (or any other science or engineering discipline) when a machine already knows the formalism and the answers?  On some level, this has been a serious question since the real advent of search engines.  The sum total of human knowledge is available at a few keystrokes.  Teaching students just rote recall of facts is approaching pointless (though proficiency can be hugely important in some circumstances - I want a doctor who can diagnose and treat ailments without having to google a list of my symptoms.).

My answer to this question is layered.  First, I would argue that beyond factual content we are teaching students how to think and reason.  This is and I believe will remain important, even in an era when AI tools are more capable and reliable than at present.  I like to think that there is some net good in training your brain to work hard, to reason your way through complicated problems (in the case of physics, formulating and then solving and testing models of reality).  It's hard for me to believe that this is poor long-term strategy.  Second, while maybe not as evocative as the way creative expression is described in the quote, there is real accomplishment (in your soul?) in actually learning something yourself.  A huge number of people are better at playing music than I am, but that doesn't mean it wasn't worthwhile to me to play the trumpet growing up.  Overworked as referencing Feynman is, the pleasure of finding things out is real.  

AI/LLMs can be great tools for teachers.  There are several applet-style demos that I've put off making for years because of how long it would take for me to code them up nicely.  With these modern capabilities, I've been able to make some of these now, in far less time than it would otherwise have taken, and students will get the chance to play with them.  Still, the creativity involved in what demos to make and how they should look and act was mine, based on knowledge and experience.  People still have a lot to bring to the process, and I don't think that's going to change for a very long time.

20 years of Nanoscale Views, + a couple of things to read

Amazingly, this blog has now been around for more than twenty years (!) - see this first post for reference from June of 2005, when I had much less gray hair and there were a lot more science blogs.  Thanks to all of you for sticking around. Back then, when I debuted my writing to my loyal readers (all five of them at the time), I never thought I'd keep this up.  Some info, including stats according to blogger:

• Total views: 8.3M
• Most views in one day, this past May 31, with 272K
• Top two most-viewed posts are this one from 2023 with a comment thread about Ranga Dias, and this one from 2009 titled "What is a plasmon?"
• Just a reminder that I have collected a bunch of condensed matter terms and concept posts here.
• I've also written some career-related posts, like a guide to faculty job searches, advice on choosing a graduate school, needs-to-be-updated advice on postdoc positions, etc.
• Some personal favorite posts, some of which I wish had gotten more notice, include the physics of drying your hands, the physics of why whiskey stones aren't as good as ice to cool your drink, materials and condensed matter in science fiction, the physics of vibranium, the physics of beskar, the physics of ornithopters, and why curving your pizza slice keeps if from flopping over.  I'm also happy with why soft matter is hard, which was a well-viewed post.
• I also like to point out my essay about J. Henrik Schön, because I worry that people have forgotten about that episode.

Real life has intruded quite a bit into my writing time the last couple of years, but I hope to keep doing this for a while longer.  I also still hope one day to find the right time and approach to write a popular book about the physics of materials, why they are amazing, and why our understanding of this physics, limited as it is, is still an astonishing intellectual achievement. 

Two other things to read that I came across this week:

• This post about Maxwell's Demon from the Skull in the Stars blog (which has been around nearly as long as mine!) is an excellent and informative piece of writing.  I'm definitely pointing my statistical and thermal physics undergraduate class to this next month.
• Ross McKenzie has a very nice looking review article up on the arXiv about emergence. I haven't read it yet, but I have no doubt that it will be well-written and thought-provoking.

Brief items - Static electricity, quantum geometry, Hubbard model, + news

It's been a busy time that has cut into my blogging, but I wanted to point out some links from the past couple of weeks.

• 
  Physics Today has a cover article this past issue about what is colloquially known as static electricity, but what is more technically described as triboelectricity, the transfer of charge between materials by rubbing.  I just wrote about this six months ago, and the detailed mechanisms remain poorly understood.  Large surface charge densities (like \(10^{12}\) electronic charges per square cm) can be created this way on insulators, leading to potential differences large enough to jump a spark from your finger to the door handle.  This can also lead to static electric fields near surfaces that are not small and can reveal local variations in material properties.
  
• That leads right into this paper (which I learned about from here) about the extreme shapes of the heads of a family of insects called treehoppers.  These little crawlies have head and body shapes that often have cuspy, pointy bits that stick out - spines, horns, etc.  As we learn early on about electrostatics, elongated and pointy shapes tend to lead to large local electric fields and field gradients.  The argument of this paper is that the spiky body and cranial morphology can help these insects better sense electric field distributions, and this makes it easier for them to find their way and avoid predators. 
• This manuscript on the arXiv this week is a particularly nice, pedagogical review article (formatted for Rev Mod Phys) about quantum geometry and Berry curvature in condensed matter systems.  I haven't had the chance to read it through, but I think this will end up being very impactful and a true resource for students to learn about these topics.
• Another very pretty recent preprint is this one, which examines the electronic phase diagram of twisted bilayers of WSe2, with a relative twist angle of 4.6°.  Much attention has been paid to the idea that moiré lattices can be in a regime seemingly well described by a Hubbard-like model, with an on-site Coulomb repulsion energy \(U\) and an electronic bandwidth \(W\).  This paper shows an exceptionally clean example of this, where disorder seems to be very weak, electron temperatures are quite cold, and phase diagrams are revealed that look remarkably like the phenomena seen in the cuprate superconductors (superconducting "domes" as a function of charge density adjacent to antiferromagnetic insulating states, and with "strange metal" linear-in-\(T\) resistance in the normal state near the superconducting charge density).  Results like this make me more optimistic about overcoming some of the major challenges in using twisted van der Waals materials as simulators of hard-to-solve hamilitonians.

I was all set to post this earlier today, with no awful news for once about science in the US that I felt compelled to discuss, but I got sidetracked by real work.  Then, late this afternoon, this executive order about federal grants was released.  

I can't sugar coat it - it's awful.  Ignoring a large volume of inflammatory rhetoric, it contains this gem, for instance:  "The grant review process itself also undermines the interests of American taxpayers."   It essentially tries to bar any new calls for proposals until a new (and problematic) process is put in place at every agency (see Sect. 3(c)).  Also, it says "All else being equal, preference for discretionary awards should be given to institutions with lower indirect cost rates."  Now, indirect cost rates are set by negotiations between institutions and the government.   Places that only do very small volumes of research have low rates, so get ready for MIT to get fewer grants and Slippery Rock University to get more.  The only certainty is that the nation's lawyers are going to have a field day with all the suits that will come out of this.

Research experience for teachers - why NSF education funds matter

The beginning of a RET poster session

Research Experience for Teachers (RET) programs are an example of the kind of programs that the National Science Foundation funds which are focused on K12 (and broader) education. This summer I hosted a high school physics teacher in my lab for 6 weeks, where he worked on a brief project, with one of my doctoral students helping out in a mentoring role.  Just yesterday was the big poster session for all of the participants in the program, and it was very enjoyable to talk with a whole cadre of high school science teachers from across the greater Houston area about their projects and their experiences.  

Readers may be more familiar with the sibling Research Experience for Undergraduates (REU) programs, which give undergraduate students the chance to work for 10 weeks or so in a lab that is very likely not at their home institution.  REUs are a great way for students interested in research to get broad exposure to new topics, meet people and acquire new skills, and for some, figure out whether they like research (and maybe which topics are exciting to them).  The educational goal of REUs is clear:  providing direct research experience to interested undergrads, ideally while advancing a research project and for some small fraction of students resulting in an eventual publication.  

RET programs are different:  They are intended as professional development.  The teachers are exposed to new topics, hopefully a fun research environment, and they are encouraged to think carefully about how they can take the concepts they learn and translate those for the classroom.  I am very much not an expert in education research, but there is evidence (see here, for example) that teachers who participate in these programs get a great deal of satisfaction and have lower attrition from teaching professions.  (Note that it's hard to do statistics well on questions like that, since the population of teachers that seek out opportunities like this may be a special subset of the total population of teachers.)  An idea that makes sense to me:  Enhancing the motivation and job satisfaction of a teacher can have a larger cumulative impact on educating students than an individual research project for a single student.

It would be a great shame if RET and REU programs are victims of large-scale cuts at NSF.  The NSF is the only science agency with education as part of its mission (at least historically).  All the more reason to try to persuade appropriators to not follow the draconian presidential budget request for the agency.

The latest on US science funding

The US House and Senate appropriations subcommittees have now completed their markups on the bills relevant to the FY26 appropriations for NSF, NASA, and NIST.  The AAAS has an interactive dashboard with current information here if you want to click and look at all the science-related agencies.   Other agencies still need to go through the Senate subcommittees. 

Just a reminder of how this is supposed to work.  The House and Senate mark up their own versions of the detailed appropriations bills.  In principle these are passed by each chamber (with the Senate versions for practical purposes requiring 60/100 votes of support because of the filibuster).  Then a conference committee hashes out the differences between the bills, and the conference version of the bills is then voted on by each chamber (again, needing 60/100 votes to pass in the Senate).  Finally, the president signs the spending bills.  In the fantasy land of Schoolhouse Rock, which largely described events until the 1990s, these annual spending bills are supposed to be passed in time for the start of the new fiscal year on October 1.  In practice, Congress has been deeply dysfunctional for years, and there have been a lot of continuing resolutions, late budgets, and mammoth omnibus spending bills.  

To summarize:

• NSF - House recommendation = $6.997B (a 20.7% cut from FY25), Senate = $9B (a 2% increase from FY25).  These are in sharp contrast to the presidential budget request (PBR) of a 55.8% cut.
• NASA - House = flat from FY25, Senate = $24.9B (0.2% increase).  
• NIST - House = $1.28B (10.6% increase from FY25), Senate = $1.6B (38.3% increase from FY25)
• NOAA - House = $5.7B (28.3% increase from FY25), Senate = $6.1B (36.3% increase from FY25)

DOE has gone through the House, where the Office of Science is recommending a 1.9% increase, in contrast to a 13.9% cut in the PBR.  

If you are eligible and able to do so, please keep pushing.  As I wrote a few days ago, this is a long-term project, since appropriations happen every year.  As long as you're making your opinions known, it's good to push on representatives and senators that they need to hold the agency leadership accountable to actually spend what congress appropriates. 

A science post soon....

US science funding - now time to push on the House appropriators

Some not-actively-discouraging news out of Washington DC yesterday:  The Senate appropriations committee is doing its markups of the various funding bills (which all technically originated in the House), and it appears that they have pushed to keep the funding for NASA and NSF (which are bundled in the same bill with the Department of Justice for no obvious reason) at FY24 levels.  See here as well.  

This is not yet a done deal within the Senate, but it's better than many alternatives.  If you are a US citizen or permanent resident and one of your senators is on the appropriations committee, please consider calling them to reinforce how devastating massive budget cuts to these agencies would be.  I am told that feedback to any other senators is also valuable, but appropriators are particularly important here.

The House appropriations committee has not yet met to mark up their versions.  They had been scheduled to do so earlier this week but punted it for an unknown time.  Their relevant subcommittee membership is here.  Again, if you are a constituent of one of these representatives, your calls would be particularly important, though it doesn't hurt for anyone to make their views heard to their representative.  If the House version aligns with the presidential budget request, then a compromise between the two might still lead to 30% cuts to NSF and NASA, which would (IMO) still be catastrophic for the agencies and US science and competitiveness.

This is a marathon, not a sprint.  There are still many looming difficulties - staffing cuts are well underway.   Spending of already appropriated funds at agencies like NSF is way down, leading to the possibility that the executive branch may just order (or not-order-but-effectively-order) agencies not to spend and then claw back the funds.  This year and in future years they could decide to underspend appropriations knowing that any legal resistance will take years and cost a fortune to work its way through the courts.  This appropriations battle is also an annual affair - even if the cuts are forestalled for now (it is unlikely that the executive would veto all the spending bills over science agency cuts), this would have to happen again next year, and so on.

Still, right now, there is an opportunity to push against funding cuts.  Failing to try would be a surrender.

(Obligatory notice:  yes, I know that there are large-scale budgetary challenges facing the US; I don't think destroying government investment in science and engineering research is an intelligent set of spending cuts.)

New updates + tetrahedra, tunneling times, and more

Here are a number of items from the past week or so that I think readers of this blog might find interesting:

• Essentially all the news pertaining to the US federal funding of science continues to be awful.  This article from Science summarizes the situation well, as does this from The Guardian and this editorial in the Washington Post. I do like the idea of a science fair of cancelled grants as a way to try to get alleged bipartisan appropriator notice of just how bad the consequences would be of the proposed cuts.  
• On a more uplifting note, mathematicians have empirically demonstrated a conjecture originally made by John Conway, that it is possible to make a tetrahedral pyramid that, under gravity, has only one stable orientation.  Quanta has a nice piece on this with a cool animated gif, and here is the actual preprint about it.  It's all about mass distributions and moments of inertia about edges.  As others have pointed out including the authors, this could be quite useful for situations like recent lunar lander attempts that seem to have a difficult time not topping over.
• A paper last week in Nature uses photons and a microcavity to try to test how long it takes photons to tunnel through a classically forbidden region.  In this setup, it is mathematically legit to model the photons as if they have an effective mass, and one can model the barrier they need to traverse in terms of an effective potential energy.  Classically, if the kinetic energy of the particle of interest is less than the potential energy of the barrier, the particle is forbidden inside the barrier.  I've posted about the issue of tunneling time repeatedly over the years (see here for a 2020 post containing links), because I think it's a fascinating problem both conceptually and as a puzzle for experimentalists (how does one truly do a fair test of this?).  The take-away from this paper is, the more classically forbidden the motion, the faster the deduced tunneling time.  This has been seen in other experiments testing this idea.  A key element of novelty in the new paper is the claim that the present experiment seems (according to the authors) to not be reasonably modeled by Bohmian mechanics.  I'd need to read this in more depth to better understand it, as I had thought that Bohmian mechanics applied to problems like this is generally indistinguishable in predictions from conventional quantum mechanics, basically by design.
• In other non-condensed matter news, there is an interstellar comet transiting the solar system right now.  This is very cool - it's only the third such object detected by humans, but to be fair we've only really been looking for a few years.  This suggests that moderately sized hunks of material are likely passing through from interstellar space all the time, and the Vera C. Rubin Observatory will detect a boatload of them.  My inner science fiction fan is hoping that the object changes its orbit at perihelion by mysterious means.  

This week is crunch time for a final push on US congressional appropriators to try to influence science agency budgets in FY26.  I urge you to reach out if this matters to you.  Likewise, I think it's more than reasonable to ask congress why the NSF is getting kicked out of its headquarters with no plan for an alternative agency location, so that the HUD secretary can have a palatial second home in that building.

Science slow down - not a simple question

I participated in a program about 15 years ago that looked at science and technology challenges faced by a subset of the US government. I came away thinking that such problems fall into three broad categories.

1. Actual science and engineering challenges, which require foundational research and creativity to solve.
2. Technology that may be fervently desired but is incompatible with the laws of nature, economic reality, or both. 
3. Alleged science and engineering problems that are really human/sociology issues.

Part of science and engineering education and training is giving people the skills to recognize which problems belong to which categories.  Confusing these can strongly shape the perception of whether science and engineering research is making progress. 

There has been a lot of discussion in the last few years about whether scientific progress (however that is measured) has slowed down or stagnated.  For example, see here:

https://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/ 

https://news.uchicago.edu/scientific-progress-slowing-james-evans

https://www.forbes.com/sites/roberthart/2023/01/04/where-are-all-the-scientific-breakthroughs-forget-ai-nuclear-fusion-and-mrna-vaccines-advances-in-science-and-tech-have-slowed-major-study-says/

https://theweek.com/science/world-losing-scientific-innovation-research

A lot of the recent talk is prompted by this 2023 study, which argues that despite the world having many more researchers than ever before (behold population growth) and more global investment in research, somehow "disruptive" innovations are coming less often, or are fewer and farther between these days.  (Whether this is an accurate assessment is not a simple matter to resolve; more on this below.)

There is a whole tech bro culture that buys into this, however.  For example, see this interview from last week in the New York Times with Peter Thiel, which points out that Thiel has been complaining about this for a decade and a half.  

On some level, I get it emotionally.  The unbounded future spun in a lot of science fiction seems very far away.  Where is my flying car?  Where is my jet pack?  Where is my moon base?  Where are my fusion power plants, my antigravity machine, my tractor beams, my faster-than-light drive?  Why does the world today somehow not seem that different than the world of 1985, while the world of 1985 seems very different than that of 1945?

Some of the folks that buy into this think that science is deeply broken somehow - that we've screwed something up, because we are not getting the future they think we were "promised".  Some of these people have this as an internal justification underpinning the dismantling of the NSF, the NIH, basically a huge swath of the research ecosystem in the US.  These same people would likely say that I am part of the problem, and that I can't be objective about this because the whole research ecosystem as it currently exists is a groupthink self-reinforcing spiral of mediocrity.  

Science and engineering are inherently human ventures, and I think a lot of these concerns have an emotional component.  My take at the moment is this:

1. Genuinely transformational breakthroughs are rare.  They often require a combination of novel insights, previously unavailable technological capabilities, and luck.  They don't come on a schedule.  
2. There is no hard and fast rule that guarantees continuous exponential technological progress.  Indeed, in real life, exponential growth regimes never last. The 19th and 20th centuries were special.   If we think of research as a quest for understanding, it's inherently hierarchal.  Civilizational collapses aside, you can only discover how electricity works once.   You can only discover the germ theory of disease, the nature of the immune system, and vaccination once (though in the US we appear to be trying really hard to test that by forgetting everything).  You can only discover quantum mechanics once, and doing so doesn't imply that there will be an ongoing (infinite?) chain of discoveries of similar magnitude.
3. People are bad at accurately perceiving rare events and their consequences, just like people have a serious problem evaluating risk or telling the difference between correlation and causation.  We can't always recognize breakthroughs when they happen.  Sure, I don't have a flying car.  I do have a device in my pocket that weighs only a few ounces, gives me near-instantaneous access to the sum total of human knowledge, let's me video call people around the world, can monitor aspects of my fitness, and makes it possible for me to watch sweet videos about dogs.  The argument that we don't have transformative, enormously disruptive breakthroughs as often as we used to or as often as we "should" is in my view based quite a bit on perception.
4. Personally, I think we still have a lot more to learn about the natural world.  AI tools will undoubtedly be helpful in making progress in many areas, but I think it is definitely premature to argue that the vast majority of future advances will come from artificial superintelligences and thus we can go ahead and abandon the strategies that got us the remarkable achievements of the last few decades.
5. I think some of the loudest complainers (Thiel, for example) about perceived slowing advancement are software people.  People who come from the software development world don't always appreciate that physical infrastructure and understanding are hard, and that there are not always clever or even brute-force ways to get to an end goal.  Solving foundational problems in molecular biology or quantum information hardware or  photonics or materials is not the same as software development.  (The tech folks generally know this on an intellectual level, but I don't think all of them really understand it in their guts.  That's why so many of them seem to ignore real world physical constraints when talking about AI.).  Trying to apply software development inspired approaches to science and engineering research isn't bad as a component of a many-pronged strategy, but alone it may not give the desired results - as warned in part by this piece in Science this week.  

More frequent breakthroughs in our understanding and capabilities would be wonderful.  I don't think dynamiting the US research ecosystem is the way to get us there, and hoping that we can dismantle everything because AI will somehow herald a new golden age seems premature at best.

Cryogenic CMOS - a key need for solid state quantum information processing

The basis for much of modern electronics is a set of silicon technologies called CMOS, which stands for complementary metal oxide semiconductor devices and processes.  "Complementary" means using semiconductors (typically silicon) that is locally chemically doped so that you can have both n-type (carriers are negatively charged electrons in the conduction band) and p-type (carriers are positively charged holes in the valence band) material on the same substrate.  With field-effect transistors (using oxide gate dielectrics), you can make very compact, comparatively low power devices like inverters and logic gates.  

There are multiple different approaches to try to implement quantum information processing in solid state platforms, with the idea that the scaling lessons of microelectronics (in terms of device density and reliability) can be applied.  I think that essentially all of these avenues require cryogenic operating conditions; all superconducting qubits need ultracold conditions for both superconductivity and to minimize extraneous quasiparticles and other decoherence sources.  Semiconductor-based quantum dots (Intel's favorite) similarly need thermal perturbations and decoherence to be minimized.  The wealth of solid state quantum computing research is the driver for the historically enormous (to me, anyway) growth of dilution refrigerator manufacturing (see my last point here).

So you eventually want to have thousands of error-corrected logical qubits at sub-Kelvin temperatures, which may involve millions of physical qubits at sub-Kelvin temperatures, all of which need to be controlled.  Despite the absolute experimental fearlessness of people like John Martinis, you are not going to get this to work by running a million wires from room temperature into your dil fridge.  

Fig. 1 from here.

The alternative people in this area have converged upon is to create serious CMOS control circuitry that can work at 4 K or below, so that a lot of the wiring does not need to go from the qubits all the way to room temperature.  The materials and device engineering challenges in doing this are substantial!  Power dissipation really needs to be minimized, and material properties to work at cryogenic conditions are not the same as those optimized for room temperature.  There have been major advances in this - examples include Google in 2019, Intel in 2021, IBM in 2024, and this week, folks at the University of Syndney in New South Wales, supported by Diraq and Emergence Quantum.  (updated/corrected)

In this most recent work, the aspect that I find most impressive is that the CMOS electronics are essentially a serious logic-based control board operating at milliKelvin temperatures right next to the chip with the qubits (in this case, spins-in-quantum-dots).  I'm rather blown away that this works and with sufficiently low power dissipation that the fridge is happy.  This is very impressive, and there is likely a very serious future in store for cryogenic CMOS.

Brief items - fresh perspectives, some news bits

As usual, I hope to write more about particular physics topics soon, but in the meantime I wanted to share a sampling of news items:

• First, it's a pleasure to see new long-form writing about condensed matter subjects, in an era where science blogging has unquestionably shrunk compared to its heyday.  The new Quantum Matters substack by Justin Wilson (and William Shelton) looks like it will be a fun place to visit often.
• Similar in spirit, I've also just learned about the Knowmads podcast (here on youtube), put out by Prachi Garella and Bhavay Tyagi, two doctoral students at the University of Houston.  Fun Interviews with interesting scientists about their science and how they get it done.  
• There have been some additional news bits relevant to the present research funding/university-govt relations mess.  Earlier this week, 200 business leaders published an open letter about how the slashing support for university research will seriously harm US economic competitiveness.  More of this, please.  I continue to be surprised by how quiet technology-related, pharma, and finance companies are being, at least in public.  Crushing US science and engineering university research will lead to serious personnel and IP shortages down the line, definitely poor for US standing.  Again, now is the time to push back on legislators about cuts mooted in the presidential budget request.  
• The would-be 15% indirect cost rate at NSF has been found to be illegal, in a summary court judgment released yesterday.  (Brief article here, pdf of the ruling here.)
• Along these lines, there are continued efforts for proposals about how to reform/alter indirect cost rates in a far less draconian manner.  These are backed by collective organizations like the AAU and COGR.  If you're interested in this, please go here, read the ideas, and give some feedback.  (Note for future reference:  the Joint Associations Group (JAG) may want to re-think their acronym.  In local slang where I grew up, the word "jag" does not have pleasant connotations.)
• The punitive attempt to prevent Harvard from taking international students has also been stopped for now in the courts. 

So you want to build a science/engineering laboratory building

A very quick summary of some non-negative news developments:

• The NSF awarded 500 more graduate fellowships this week, bringing the total for this year up to 1500.  (Apologies for the X link.)  This is still 25% lower than last year's number, and of course far below the original CHIPS and Science act target of 3000, but it's better than the alternative.  I think we can now all agree that the supposed large-scale bipartisan support for the CHIPS and Science act was illusory.
• There seems to be some initial signs of pushback on the senate side regarding the proposed massive science funding cuts.  Again, now is the time to make views known to legislators - I am told by multiple people with experience in this arena that it really can matter.
• There was a statement earlier this week that apparently the US won't be going after Chinese student visas.  This would carry more weight if it didn't look like US leadership was wandering ergodically through all possible things to say with no actual plan or memory.

On to the main topic of this post.  Thanks to my professional age (older than dirt) and my experience (overseeing shared research infrastructure; being involved in a couple of building design and construction projects; and working on PI lab designs and build-outs), I have some key advice and lessons learned for anyone designing a new big science/engineering research building.  This list is by no means complete, and I invite readers to add their insights in the comments.  While it seems likely that many universities will be curtailing big capital construction projects in the near term because of financial uncertainty, I hope this may still come in handy to someone.  

• Any big laboratory building should have a dedicated loading dock with central receiving.  If you're spending $100M-200M on a building, this is not something that you should "value engineer" away.  The long term goal is a building that operates well for the PIs and is easy to maintain, and you're going to need to be able to bring in big crates for lab and service equipment.  You should have a freight elevator adjacent to the dock.  
• You should also think hard about what kind of equipment will have to be moved in and out of the building when designing hallways, floor layouts, and door widths.  You don't want to have to take out walls, doorframes, or windows, or to need a crane to hoist equipment into upper floors because it can't get around corners.
• Think hard about process gasses and storage tanks at the beginning.  Will PIs need to have gas cylinders and liquid nitrogen and argon tanks brought in and out in high volumes all the time, with all the attendant safety concerns?  Would you be better off getting LN2 or LAr tanks even though campus architects will say they are unsightly?  
• Likewise, consider whether you should have building-wide service for "lab vacuum", N2 gas, compressed air, DI water, etc.  If not and PIs have those needs, you should plan ahead to deal with this.
• Gas cylinder and chemical storage - do you have enough on-site storage space for empty cylinders and back-up supply cylinders?  If this is a very chemistry-heavy building, think hard about safety and storing solvents. 
• Make sure you design for adequate exhaust capacity for fume hoods.  Someone will always want to add more hoods.  While all things are possible with huge expenditures, it's better to make sure you have capacity to spare, because adding hoods beyond the initial capacity would likely require a huge redo of the building HVAC systems.
• Speaking of HVAC, think really hard about controls and monitoring.  Are you going to have labs that need tight requirements on temperature and humidity?  When you set these up, put have enough sensors of the right types in the right places, and make sure that your system is designed to work even when the outside air conditions are at their seasonal extremes (hot and humid in the summer, cold and dry in the winter).  Also, consider having a vestibule (air lock) for the main building entrance - you'd rather not scoop a bunch of hot, humid air (or freezing, super-dry air) into the building every time a student opens the door.
• Still on HVAC, make sure that power outages and restarts don't lead to weird situations like having the whole building at negative pressure relative to the outside, or duct work bulging or collapsing.
• Still on HVAC, actually think about where the condensate drains for the fan units will overflow if they get plugged up or overwhelmed.  You really don't want water spilling all over a rack of networking equipment in an IT closet.  Trust me.
• Chilled water:  Whether it's the process chilled water for the air conditioning, or the secondary chilled water for lab equipment, make sure that the loop is built correctly.   Incompatible metals (e.g., some genius throws in a cast iron fitting somewhere, or joints between dissimilar metals) can lead to years and years of problems down the line.  Make sure lines are flushed and monitored for cleanliness, and have filters in each lab that can be checked and maintained easily.
• Electrical - design with future needs in mind.  If possible, it's a good idea to have PI labs with their own isolation transformers, to try to mitigate inter-lab electrical noise issues.  Make sure your electrical contractors understand the idea of having "clean" vs. "dirty" power and can set up the grounding accordingly while still being in code.
• Still on electrical, consider building-wide surge protection, and think about emergency power capacity.  For those who don't know, emergency power is usually a motor-generator that kicks in after a few seconds to make sure that emergency lighting and critical systems (including lab exhaust) keep going.
• Ceiling heights, duct work, etc. - It's not unusual for some PIs to have tall pieces of equipment.  Think about how you will accommodate these.  Pits in the floors of basement labs?  5 meter slab-to-slab spacing?  Think also about how ductwork and conduits are routed.  You don't want someone to tell you that installation of a new apparatus is going to cost a bonus $100K because shifting a duct sideways by half a meter will require a complete HVAC redesign.
• Think about the balance between lab space and office space/student seating.  No one likes giant cubicle farm student seating, but it does have capacity.  In these days of zoom and remote access to experiments, the way students and postdocs use offices is evolving, which makes planning difficult.  Health and safety folks would definitely prefer not to have personnel effectively headquartered directly in lab spaces.  Seriously, though, when programming a building, you need to think about how many people per PI lab space will need places to sit.  I have yet to see a building initially designed with enough seating to handle all the personnel needs if every PI lab were fully occupied and at a high level of research activity. 
• Think about maintenance down the line.  Every major building system has some lifespan.  If a big air handler fails, is it accessible and serviceable, or would that require taking out walls or cutting equipment into pieces and disrupting the entire building?  Do you want to set up a situation where you may have to do this every decade?  (Asking for a friend.)
• Entering the realm of fantasy, use your vast power and influence to get your organization to emphasize preventative maintenance at an appropriate level, consistently over the years.  Universities (and national labs and industrial labs) love "deferred maintenance" because kicking the can down the road can make a possible cost issue now into someone else's problem later.  Saving money in the short term can be very tempting.  It's also often easier and more glamorous to raise money for the new J. Smith Laboratory for Physical Sciences than it is to raise money to replace the HVAC system in the old D. Jones Engineering Building.  Avoid this temptation, or one day (inevitably when times are tight) your university will notice that it has $300M in deferred maintenance needs.

I may update this list as more items occur to me, but please feel free to add input/ideas.

A precision measurement science mystery - new physics or incomplete calculations?

Again, as a distraction from persistently concerning news, here is a science mystery of which I was previously unaware.

The role of approximations in physics is something that very often comes as a shock to new students.  There is this cultural expectation out there that because physics is all about quantitative understanding of physical phenomena, and the typical way we teach math and science in K12 education, we should be able to get exact solutions to many of our attempts to model nature mathematically.   In practice, though, constructing physics theories is almost always about approximations, either in the formulation of the model itself (e.g. let's consider the motion of an electron about the proton in the hydrogen atom by treating the proton as infinitely massive and of negligible size) or in solving the mathematics (e.g., we can't write an exact analytical solution of the problem when including relativity, but we can do an order-by-order expansion in powers of \(p/mc\)).  Theorists have a very clear understanding of what means to say that an approximation is "well controlled" - you know on both physical and mathematical grounds that a series expansion actually converges, for example.  

Some problems are simpler than others, just by virtue of having a very limited number of particles and degrees of freedom, and some problems also lend themselves to high precision measurements.  The hydrogen atom problem is an example of both features.  Just two spin-1/2 particles (if we approximate the proton as a lumped object) and readily accessible to optical spectroscopy to measure the energy levels for comparison with theory.  We can do perturbative treatments to account for other effects of relativity, spin-orbit coupling, interactions with nuclear spin, and quantum electrodynamic corrections (here and here).  A hallmark of atomic physics is the remarkable precision and accuracy of these calculations when compared with experiment.  (The \(g\)-factor of the electron is experimentally known to a part in \(10^{10}\) and matches calculations out to fifth order in \(\alpha = e^2/(4 \pi \epsilon_{0}\hbar c)\).).  

The helium atom is a bit more complicated, having two electrons and a more complicated nucleus, but over the last hundred years we've learned a lot about how to do both calculations and spectroscopy.   As explained here, there is a problem.  It is possible to put helium into an excited metastable triplet state with one electron in the \(1s\) orbital, the other electron in the \(2s\) orbital, and their spins in a triplet configuration.  Then one can measure the ionization energy of that system - the minimum energy required to kick an electron out of the atom and off to infinity.  This energy can be calculated to seventh order in \(\alpha\), and the theorists think that they're accounting for everything, including the finite (but tiny) size of the nucleus.  The issue:  The calculation and the experiment differ by about 2 nano-eV.  That may not sound like a big deal, but the experimental uncertainty is supposed to be a little over 0.08 nano-eV, and the uncertainty in the calculation is estimated to be 0.4 nano-eV.  This works out to something like a 9\(\sigma\) discrepancy.  Most recently, a quantitatively very similar discrepancy shows up in the case of measurements performed in 3He rather than 4He.  

This is pretty weird.  Historically, it would seem that the most likely answer is a problem with either the measurements (though that seems doubtful, since precision spectroscopy is such a well-developed set of techniques), the calculation (though that also seems weird, since the relevant physics seems well known), or both.  The exciting possibility is that somehow there is new physics at work that we don't understand, but that's a long shot.  Still, something fun to consider (as my colleagues (and I) try to push back on the dismantling of US scientific research.)

Pushing back on US science cuts: Now is a critical time

Every week has brought more news about actions that, either as a collateral effect or a deliberate goal, will deeply damage science and engineering research in the US.  Put aside for a moment the tremendously important issue of student visas (where there seems to be a policy of strategic vagueness, to maximize the implicit threat that there may be selective actions).  Put aside the statement from a Justice Department official that there is a general plan is to "bring these universities to their knees", on the pretext that this is somehow about civil rights.  

The detailed version of the presidential budget request for FY26 is now out (pdf here for the NSF portion).  If enacted, it would be deeply damaging to science and engineering research in the US and the pipeline of trained students who support the technology sector.  Taking NSF first:  The topline NSF budget would be cut from $8.34B to $3.28B.  Engineering would be cut by 75%, Math and Physical Science by 66.8%.  The anticipated agency-wide success rate for grants would nominally drop below 7%, though that is misleading (basically taking the present average success rate and cutting it by 2/3, while some programs are already more competitive than others.).  In practice, many programs already have future-year obligations, and any remaining funds will have to go there, meaning that many programs would likely have no awards at all in the coming fiscal year.  The NSF's CAREER program (that agency's flagship young investigator program) would go away  This plan would also close one of the LIGO observatories (see previous link).  (This would be an extra bonus level of stupid, since LIGO's ability to do science relies on having two facilities, to avoid false positives and to identify event locations in the sky.  You might as well say that you'll keep an accelerator running but not the detector.)  Here is the table that I think hits hardest, dollars aside:

The number of people involved in NSF activities would drop by 240,000.  The graduate research fellowship program would be cut by more than half.  The NSF research training grant program (another vector for grad fellowships) would be eliminated.  

The situation at NIH and NASA is at least as bleak.  See here for a discussion from Joshua Weitz at Maryland which includes this plot: 

This proposed dismantling of US research and especially the pipeline of students who support the technology sector (including medical research, computer science, AI, the semiconductor industry, chemistry and chemical engineering, the energy industry) is astonishing in absolute terms.  It also does not square with the claim of some of our elected officials and high tech CEOs to worry about US competitiveness in science and engineering.  (These proposed cuts are not about fiscal responsibility; just the amount added in the proposed DOD budget dwarfs these cuts by more than a factor of 3.)

If you are a US citizen and think this is the wrong direction, now is the time to talk to your representatives in Congress. In the past, Congress has ignored presidential budget requests for big cuts.  The American Physical Society, for example, has tools to help with this.  Contacting legislators by phone is also made easy these days.  From the standpoint of public outreach, Cornell has an effort backing large-scale writing of editorials and letters to the editor.

Quick survey - machine shops and maker spaces

Recent events are very dire for research at US universities, and I will write further about those, but first a quick unrelated survey for those at such institutions.  Back in the day, it was common for physics and some other (mechanical engineering?) departments to have machine shops with professional staff.  In the last 15-20 years, there has been a huge growth in maker-spaces on campuses to modernize and augment those capabilities, though often maker-spaces are aimed at undergraduate design courses rather than doing work to support sponsored research projects (and grad students, postdocs, etc.).  At the same time, it is now easier than ever (modulo tariffs) to upload CAD drawings to a website and get a shop in another country to ship finished parts to you.

Quick questions:   Does your university have a traditional or maker-space-augmented machine shop available to support sponsored research?  If so, who administers this - a department, a college/school, the office of research?  Does the shop charge competitive rates relative to outside vendors?  Are grad students trained to do work themselves, and are there professional machinists - how does that mix work?

Thanks for your responses.  Feel free to email me if you'd prefer to discuss offline.

How badly has NSF funding already been effectively cut?

This NY Times feature lets you see how each piece of NSF's funding has been reduced this year relative to the normalized average spanning in the last decade.  Note: this fiscal year, thanks to the continuing resolution, the actual agency budget has not actually been cut like this. They are just not spending congressionally appropriated agency funds.  The agency, fearing/assuming that its budget will get hammered next fiscal year, does not want to start awards that it won't be able to fund in out-years. The result is that this is effectively obeying in advance the presidential budget request for FY26.  (And it's highly likely that some will point to unspent funds later in the year and use that as a justification for cuts, when in fact it's anticipation of possible cuts that has led to unspent funds.  I'm sure the Germans have a polysyllabic word for this.  In English, "Catch-22" is close.)

I encourage you to click the link and go to the article where the graphic is interactive (if it works in your location - not sure about whether the link works internationally).  The different colored regions are approximately each of the NSF directorates (in their old organizational structure).  Each subsection is a particular program.  

Seems like whoever designed the graphic was a fan of Tufte, and the scaling of the shaded areas does quantitatively reflect funding changes.  However, most people have a tough time estimating relative areas of irregular polygons.  Award funding in physics (the left-most section of the middle region) is down 85% relative to past years.  Math is down 72%.  Chemistry is down 57%.  Materials is down 63%.  Earth sciences is down 80%.  Polar programs (you know, those folks who run all the amazing experiments in Antarctica) is down 88%.  

I know my readers are likely tired of me harping on NSF, but it's both important and a comparatively transparent example of what is also happening at other agencies.  If you are a US citizen and think that this is the wrong path, then push on your congressional delegation about the upcoming budget. 

A science anecdote palate cleanser

Apologies for slow posting.  Real life has been very intense, and I also was rather concerned when one of my readers mentioned last weekend that these days my blog was like concentrated doom-scrolling.  I will have more to say about the present university research crisis later, but first I wanted to give a hopefully diverting example of the kind of problem-solving and following-your-nose that crops up in research.

Recently in my lab we have had a need to measure very small changes in electrical resistance of some devices, at the level of a few milliOhms out of kiloOhms - parts in \(10^6\).  One of my students put together a special kind of resistance bridge to do this, and it works very well.  Note to interested readers: if you want to do this, make sure that you use components with very low temperature coefficients of their properties (e.g., resistors with a very small \(dR/dT\)), because otherwise your bridge becomes an extremely effective thermometer for your lab.  It’s kind of cool to be able to see the lab temperature drift around by milliKelvins, but it's not great for measuring your sample of interest.

There are a few ways to measure resistance.  The simplest is the two-terminal approach, where you drive currents through and measure voltages across your device with the same two wires.  This is easy, but it means that the voltage you measure includes contributions from the contacts those wires make with the device.  A better alternative is the four-terminal method, where you use separate wires to supply/collect the current.  

Anyway, in the course of doing some measurements of a particular device's resistance as a function of magnetic field at low temperatures, we saw something weird.  Below some rather low temperatures, when we measured in a 2-terminal arrangement, we saw a jump up in resistance by around 20 milliOhms (out of a couple of kOhms) as magnetic field was swept up from zero, and a small amount of resistance hysteresis with magnetic field sweep that vanished above maybe 0.25 T.  This vanished completely in a 4-terminal arrangement, and also disappeared above about 3.4 K.  What was this?  Turns out that I think we accidentally rediscovered the superconducting transition in indium.  While our contact pads on our sample mount looked clean to the unaided eye, they had previously had indium on there.  The magic temperature is very close to the bulk \(T_{c}\) for indium.

For one post, rather than dwelling on the terrible news about the US science ecosystem, does anyone out there have other, similar fun experimental anecdotes?  Glitches that turned out to be something surprising?  Please share in the comments.

Updates, thoughts about industrial support of university research

Lots of news in the last few days regarding federal funding of university research:

• NSF has now frozen all funding for new and continuing awards.  This is not good; just how bad it is depends on the definition of "until further notice".  
• Here is an open letter from the NSF employees union to the basically-silent-so-far National Science Board, asking for the NSB to support the agency.
• Here is a grass roots SaveNSF website with good information and suggestions for action - please take a look.
• NSF also wants to cap indirect cost rates at 15% for higher ed institutions for new awards.  This will almost certainly generate a law suit from the AAU and others.  
• Speaking of the AAU, last week there was a hearing in the Massachusetts district court regarding the lawsuits about the DOE setting indirect cost rates to 15% for active and new awards.  There had already been a temporary restraining order in place nominally stopping the change; the hearing resulted in that order being extended "until a further order is issued resolving the request for a temporary injunction."  (See here, the entry for April 29.)
• In the meantime, the presidential budget request has come out, and if enacted it would be devastating to the science agencies.  Proposed cuts include 55% to NSF, 40% to NIH, 33% to USGS, 25% to NOAA, etc.   If these cuts went through, we are taking about more than $35B, at a rough eyeball estimate. 
• And here is a letter from former NSF directors and NSB chairs to the appropriators in Congress, asking them to ignore that budget request and continue to support government sponsored science and engineering research.

Unsurprisingly, during these times there is a lot of talk about the need for universities to diversify their research portfolios - that is, expanding non-federally-supported ways to continue generating new knowledge, training the next generation of the technically literate workforce, and producing IP and entrepreneurial startup companies.  (Let's take it as read that it would be economically and societally desirable to continue these things, for the purposes of this post.)

Philanthropy is great, and foundations do fantastic work in supporting university research, philanthropy can't come close to making up for sharp drawdowns of federal support.  The numbers just don't work.  The endowment of the Moore Foundation, for example, is around $10B, implying an annual payout of $500M or so, which is great but around 1.4% of the cuts being envisioned.  

Industry seems like the only non-governmental possibility that could in principle muster the resources that could make a large-scale difference.   Consider the estimated profits (not revenues) of different industrial sectors.  The US semiconductor market had revenues last year of around $500B with an annualized net margin of around 17%, giving $85B/yr of profit.  US aerospace and defense similarly have an annual profit of around $70B.  The financial/banking sector, which has historically benefitted greatly from PhD-trained quants, has an annual net income of $250B.  I haven't even listed numbers for the energy and medical sectors, because those are challenging to parse (but large). 

All of those industries have been helped greatly by university research, directly and indirectly.  It's the source of trained people.  It's the source of initial work that is too long-term for corporations to be able to support without short-time-horizon shareholders getting annoyed.  It's the source of many startup companies that sometimes grow and other times get gobbled up by bigger fish. 

Encouraging greater industrial sponsorship of university research is a key challenge.  The value proposition must be made clear to both the companies and universities.  The market is unforgiving and exerts pressure to worry about the short term not the long term.  Given how Congress is functioning, it does not look like there are going to be changes to the tax code put in place that could incentivize long term investment.  

Cracking this and meaningfully growing the scale of industrial support for university research could be enormously impactful.  Something to ponder.

NSF, quo vadis?

There is a lot going on.  Today, some words about NSF.

Yesterday Sethuraman Panchanathan, the director of the National Science Foundation, resigned 16 months before the end of his six year term.  The relevant Science article raises the possibility that this is because, as an executive branch appointee, he would effectively have to endorse the upcoming presidential budget request, which is rumored to be a 55% cut to the agency budget (from around $9B/yr to $4B/yr) and a 50% reduction in agency staffing.  (Note:  actual appropriations are set by Congress, which has ignored presidential budget requests in the past.)  This comes at the end of a week when all new awards were halted at the agency while non-agency personnel conducted "a second review" of all grants, and many active grants have been terminated.  Bear in mind, awards this year from NSF are already down 50% over last year, even without official budget cuts.  Update:  Here is Nature's reporting from earlier today.

The NSF has been absolutely critical to a long list of scientific and technological advances over the last 70 years (see here while it's still up).  As mentioned previously, government support of basic research has a great return on investment for the national economy, and it's a tiny fraction of government spending.  Less than three years ago, the CHIPS & Science Act was passed with supposed bipartisan support in Congress, authorizing the doubling of the NSF budget.  Last summer I posted in frustration that this support seemed to be an illusion when it came to actual funding.  

People can have disagreements about the "right" level of government support for science in times of fiscal challenges, but as far as I can tell, no one (including and especially Congress so far) voted for the dismantling of the NSF.  If you think the present trajectory is wrong, contact your legislators and make your voices heard. 

A Grand Bargain and its chaotic dissolution

After World War II, under the influence (direct and indirect) of people like Vannevar Bush, a "grand bargain" was effectively struck between the US government and the nation's universities.  The war had demonstrated how important science and engineering research could be, through the Manhattan Project and the development of radar, among other things.  University researchers had effectively and sometimes literally been conscripted into the war effort.  In the postwar period, with more citizens than ever going to college because of the GI Bill, universities went through a period of rapid growth, and the government began funding research at universities on the large scale.  This was a way of accomplishing multiple goals.  This funding got hundreds of scientists and engineers to work on projects that agencies and the academic community itself (through peer review) thought would be important but perhaps were of such long-term or indirect economic impact that industry would be unlikely to support them.  It trained the next generation of researchers and of the technically skilled workforce.  It accomplished this as a complement to national laboratories and direct federal agency work.

After Sputnik, there was an enormous ramp-up of investment.  This figure (see here for an interactive version) shows different contributions to investment in research and development in the US from 1953 through 2021:

Figure from NSF report on US R&D investment 

A couple of days ago, the New York Times published a related figure, showing the growth in dollars of total federal funds sent to US universities, but I think this is a more meaningful graph (hat tip to Prof. Elizabeth Popp Berman at Michigan for her discussion of this).  In 2021, federal investment in research (the large majority of which is happening at universities) as a percentage of GDP was at its lowest level since 1953, and it was sinking further even before this year (for those worried about US competitiveness....  Also, industry does a lot more D than they do long-term R.). There are many studies by economists showing that federal investment in research has a large return (for example, here is one by the Federal Reserve Bank of Dallas saying that returns to the US economy on federal research expenditures are between 150% and 300%).  Remember, these funds are not just given to universities - they are in the form of grants and contracts, for which specific work is done and reported.   These investments also helped make US higher education the envy of much of the world and led to education of international students as a tremendous effective export business for the country.

Of course, like any system created organically by people, there are problems.  Universities are complicated and full of (ugh) academics.  Higher education is too expensive.  Compliance bureaucracy can be onerous.  Any deliberative process like peer review trades efficiency for collective expertise but also the hazards of group-think.  At the same time, the relationship between federally sponsored research and universities has led to an enormous amount of economic, technological, and medical benefit over the last 70 years.

Right now it looks like this whole apparatus is being radically altered, if not dismantled in part or in whole.  Moreover, this is not happening as a result of a debate or discussion about the proper role and scale of federal spending at universities, or an in-depth look at the flaws and benefits of the historically developed research ecosystem.  It's happening because "elections have consequences", and I'd be willing to bet that very very few people in the electorate cast their votes even secondarily because of this topic.   Sincere people can have differing opinions about these issues, but decisions of such consequence and magnitude should not be taken lightly or incidentally.  

(I am turning off comments on this one b/c I don't have time right now to pay close attention.  Take it as read that some people would comment that US spending must be cut back and that this is a consequence.)

Talk about "The Direct Democracy of Matter"

The Scientia Institute at Rice sponsors series of public lectures annually, centered around a theme.  The intent is to get a wide variety of perspectives spanning across the humanities, social sciences, arts, sciences, and engineering, presented in an accessible way.  The youtube channel with recordings of recent talks is here.

This past year, the theme was "democracy" in its broadest sense.  I was honored to be invited last year to contribute a talk, which I gave this past Tuesday, following a presentation by my CS colleague Rodrigo Ferreira about whether AI has politics.  Below I've embedded the video, with the start time set where I begin (27:00, so you can rewind to see Rodrigo).  

Which (macroscopic) states of matter to we see?  The ones that "win the popular vote" of the microscopic configurations.

US science situation updates and what's on deck

Many things have been happening in and around US science.  This is a non-exhaustive list of recent developments and links:

• There have been very large scale personnel cuts across HHS, FDA, CDC, NIH - see here.  This includes groups like the people who monitor lead in drinking water.  
• There is reporting about the upcoming presidential budget requests about NASA and NOAA.  The requested cuts are very deep.  To quote Eric Berger's article linked above, for the science part of NASA, "Among the proposals were: A two-thirds cut to astrophysics, down to $487 million; a greater than two-thirds cut to heliophysics, down to $455 million; a greater than 50 percent cut to Earth science, down to $1.033 billion; and a 30 percent cut to Planetary science, down to $1.929 billion."  The proposed cuts to NOAA are similarly deep, seeking to end climate study in the agency, as Science puts it. The full presidential budget request, including NSF, DOE, NIST, etc. is still to come.  Remember, Congress in the past has often essentially ignored presidential budget requests.  It is unclear if the will exists to do so now. 
• Speaking of NSF, the graduate research fellowship program award announcements for this year came out this past week.  The agency awarded slightly under half as many of these prestigious 3-year fellowships as in each of the last 15 years.  I can only presume that this is because the agency is deeply concerned about its budgets for the next couple of fiscal years.
• Grants are being frozen at several top private universities - these include Columbia (new cancellations), the University of Pennsylvania (here), Harvard (here), Northwestern and Cornell (here), and Princeton (here).  There are various law suits filed about all of these.  Princeton and Harvard have been borrowing money (issuing bonds) to partly deal with the disruption as litigation continues.  The president of Princeton has been more vocal than many about this.
• There has been a surge in visa revocations and unannounced student status changes in SEVIS for international students in the US.  To say that this is unsettling is an enormous understatement.  See here for a limited discussion.  There seems to be deep reluctance for universities to speak out about this, presumably from the worry that saying the wrong thing will end up placing their international students and scholars at greater exposure.
• On Friday evening, the US Department of Energy put out a "policy flash", stating that indirect cost rates on its grants would be cut immediately to 15%.  This sounds familiar.  Legal challenges are undoubtedly beginning.  
• Added bonus:  According to the Washington Post, DOGE (whatever they say they are this week) is now in control of grants.gov, the website that posts funding opportunities.  As the article says, "Now the responsibility of posting these grant opportunities is poised to rest with DOGE — and if its employees delay those postings or stop them altogether, 'it could effectively shut down federal-grant making,' said one federal official who spoke on the condition of anonymity to describe internal operations."  

None of this is good news for the future of science and engineering research in the US.  If you are a US voter and you think that university-based research is important, I encourage you to contact your legislators and make your opinions heard.  

(As I have put in my profile, what I write here are my personal opinions; I am not in any way speaking for my employer.  That should be obvious, but it never hurts to state it explicitly.)

Update:  NSF has "disestablished" the advisory committees associated with its directorates (except the recently created TIP directorate).  Coverage here in Science.   This is not good, and I worry that it bodes ill for large cutbacks.

Update 4/18:  NSF is now terminating active grants, having "updated" their "priorities".