Science policy update/outlook, early November edition

We live in interesting times.  A few recent articles and points to consider:

• From a week ago, the New York Times has a long-form journalism piece about "How Trump is Dismantling America's Scientific Research Machine".  Nothing in there will be surprising to regular readers of this blog, but it's important that it's all written down in one place.  I was not a fan of this quote: "Under Mr. Trump, the federal government is still spending roughly as much on research — about $200 billion this year — as the administrations that came before."  This is only true for some values of "true":  Appropriations were essentially flat because Congress pushed back on the presidential budget recommendation, and even then there have been massive delays in funding and in some cases (NSF!) suppressed spending below appropriations. Further, I found this quote both accurate and frustrating:  "“Science is the long game,” said Marcia McNutt, who was president of the National Academy of Sciences, the country’s top scientific advisory body, until this summer. “By the time we no longer win any Nobel Prizes, we will have lost the capacity to ever recover.”" I agree with the substance of the quote.  The frustration is with the fact that Dr. McNutt did not make a more public, spirited defense of the nation's science ecosystem when she was president of the NAS.  I also continue not to like statements like "[T]he goal of Genesis is to double the productivity of America’s science industry within a decade" made by Dario Gil and accepted uncritically, without any discussion on how "productivity" is or should be defined.  
• Cole Donovan has an interesting article considering the claim by Peter Thiel and his intellectual followers (including the presidential science advisor) that scientific breakthroughs have slowed down and that the rigid, inefficient university research ecosystem is to blame.  Leaving aside whether there is actually a slowdown, if the overwhelming majority of US spending on research (basic and otherwise) is actually coming from industry, then why is it reasonable to blame universities for an alleged slackening of the pace of breakthrough discovery?
• Speaking of Thiel, this article about the presidential science advisor was certainly interesting.  You don't see too many policy articles that refer to institutions "being flayed alive".
• By the way, NSF lost two more people who were acting in leadership positions.  There is still no National Science Board and no apparent move to appoint one.  Also, PCAST, while existing on paper, has not met since it was reconstituted seven months ago, cancelled its November meeting, and seems to have no meetings planned.  
• The election outcomes in the US are a massive shake-up of Congress.  From the perspective of science funding, things should at least not get worse.  A non-doormat Congress should actually push back against executive branch efforts to deliberately flout appropriations.  Change is difficult, though, when agency leadership all report to the president.  As the AIP points out, the Magic Eightball says "Reply hazy, try again".   Similarly, The Hill makes the always insightful case that what happens now depends on what decisions are made.   The NY Times describes a more optimistic outlook.
• Even before the election, there was a move in the works to (re)create a Congressional Office of Technology, which seems like a good idea (like when I suggested it eight years ago).

As for my local political environment, truly the stars at night are big and bright here at the moment!  No one party should have sole power for decades at a time.  I thought that Sen. Elect Talarico stood a good chance, but I was utterly shocked by the governor, lt. governor, railroad commissioner, agriculture commissioner, school board, etc. all changing hands.  Honestly, three days on and I still half expect to learn that this is an alternate universe where the Dodgers still play in Ebbets Field, Nixon is on the half-dollar, and zeppelins are common modes of air transportation.

AI as a teaching tool, brief thoughts in Nov 2026

Leaving aside AI for research at the moment, as anyone with a pulse knows at this point, we are in a period of rapid change in terms of AI tools and specifically their role in higher education.  

There is an arms race among universities about what tools should be made available to students.  There are equity of access issues here - wealthy students are likely to pay out of pocket for more expensive subscriptions, regardless of what universities provide.  Princeton announced that it's providing everyone with chatGPT subscriptions (the equivalent of the $20/mo GPT 6 Astra).  Cornell is doing something similar, including Claude.   This is likely just the beginning, as the major AI firms want to hook customers for life provide a great opportunity to many users, and prestigious universities don't want to risk being perceived as inadequate relative to their peers.

In the meantime, it's honestly not clear if undergraduate students even want this.  This WSJ article talks about how demand is through the roof at Harvard for a reading-intensive humanities course.  The reaction from some students at Princeton to being given GPT subscriptions is not exactly a ringing endorsement.

There is no question that these tools, when used correctly, can be powerful tools to develop educational materials.  A nice example that has gone a bit viral in the last week is this site, by Nathan Liow, an undergraduate CS major at UT Austin.  He's been using Claude Opus 5.5 to create interactive visuals to go with the notes he took from his AP courses, leading to some very clean demonstrations for calculus, statistics, and physics.  Without these tools, it would be a huge investment of effort to create these kinds of visualizations. 

We must figure out the ways that AI capabilities can help learning, rather than removing all of the "intellectual friction" needed to build up analytical skills, critical thinking, and knowledge.

Separately:  Tomorrow is Election Day in the US.  If you are eligible, please vote!  The only way representative government can work remotely effectively is if the electorate stands up and votes.  (Corollary: Anyone who pins their political strategy on suppressing voter turnout does not believe in representative government.)

Brief science items, end of October edition

Here are a few sciencey things I've been meaning to mention, while real life has been very busy.

• 

  Density of states for the first two 2D subbands

  Here is a cute html5 demo I made about densities of states, quickly coded with the help of gemini.  In statistical mechanics and solid state physics, it can be very helpful to try to count up the number of states (perhaps these are allowed electronic states, like electrons confined to a box or a lattice; perhaps these are electromagnetic modes in a cavity, as in the blackbody radiation problem; perhaps these are standing acoustic waves, as in the Debye vibrational heat capacity problem).  Imposing boundary conditions on the waves in our system picks out discrete allowed values of wavelengths (or equivalently \(\mathbf{k}\)-vectors).  Given those, "zoom out" so that we treat \(\mathbf{k}\) as a continuous variable, and toss in a dispersion relation that relates energy \(\epsilon\) to \(\mathbf{k}\), and you can find a density of states \(g(\epsilon) d\epsilon\), which tells you how many energy levels there are per unit energy between energies \(\epsilon\) and \(\epsilon + d\epsilon\).  For nonrelativistic electrons, with \(\epsilon \sim k^{2}\), in purely 1 spatial dimension \(g(\epsilon) \sim 1/\sqrt{\epsilon}\):  energy levels get farther and farther apart as you go up in energy, a result familiar from the particle-in-a-box.  Add in more 1D channels, and the total \(g\) looks like a sum of these 1D contributions.  Work in 2D, and you find that \(g(\epsilon) ~\)constant, independent of energy.  Work in 3D, and you find that \(g(\epsilon) \sim \sqrt{\epsilon}\).  This little applet lets you play with this, actually calculating the energies of the first 50000 states in a box whose dimensions you control.  You can see how the energy levels are distributed, and how that compares to the analytic expectations from above.   
  
• In the same spirit as this, here is a neat site that I hadn't seen until now, all about cameras and lenses, complete with interactive demonstrations.  This is just one of a wonderful collection of similar conceptual demos.  Seriously, these are great.  
• I also wanted to point out this very nice memorial tribute to Tony Leggett, who was an extremely nice, gracious person as well as an outstanding scientist.  Its publication coincided with a conference at UIUC in his honor.
• Belatedly, but in the same spirit, I've been wanting for some time to introduce my readers to Arianna Rosenbluth, a remarkable undergraduate alumna from Rice's physics department (NYT obituary here).  She deserves to be better known.  After her undergrad days, when incidentally she was the youth fencing champion of Houston (no gender distinction - she beat everyone, and qualified for the '44 and '48 Olympics, but didn't attend), she was a grad student of van Vleck at Harvard, in the group at the same time as Phil Anderson and Thomas Kuhn.  She was greatly responsible for the development of what became known as the Metropolis algorithm.  Back when I was department chair I was fortunate enough to correspond a tiny bit with her through her son, which was great.   

AI for "peer" review

I hope to write more about some new papers in the literature soon, as well as providing links to some pretty cool physics-related content.  First, though, I want to say something about this preprint, which has people talking.  The article says, in the case of an ensemble of social sciences papers, anyway, that AI-based review is better, in nearly every quantifiable way, than human peer review.  This question of AI for reviewing papers and proposals has been in the air for a bit now, as in this article in Science, this editorial at Nature Nano, and the fact that the present administration has been using AI tools to "review" grants for content that allegedly goes against executive orders.

I'm an associate editor at a journal, and I see a large volume of papers and reviews.  (Note that this post reflects my personal views, not an official take by the journal or its publisher.)  It is 100% clear that some reviewers are using AI tools to prepare their reviews, despite clear statements that this is not ok.  There is a distinct format that AI reviews take.  After a summary paragraph, usually there are five specific bullet points, one or two of which tend to zero in on some particular detail or peculiarity in wording of the paper in a way that humans probably wouldn't.  Often the phrasing is somewhat aggressive, with a bit of a "gotcha" tone.  Of course, in any given case, I can't prove AI was used, but if you read enough of these, they stand out.  To be clear:  I'm not talking about people who use AI to clean up grammar.  I'm talking about people feeding articles to an AI tool and asking it to spit out a review.

The point of peer review, whether it's for grants or articles, is to get the informed views of the relevant scholarly community about the work.  We want to know what actual practitioners think of the results and their presentation.  Purely AI reviews just do not serve this purpose.

Moreover, there are serious confidentiality issues at stake.  Sure, many scientists use preprint archives these days to put up prepublication work, but plenty still do not, especially for very hot topics where people are worried about being scooped.  Running submitted manuscripts or grant proposals through AI tools that can then scrape the content into their training sets is a fundamental violation of the confidentiality of the process.  Imagine someone uploads your manuscript about a machine learning search for a new high temperature superconductor to Gemini to generate a review, and then amazingly SandboxAQ later scoops you on this.  (Not accusing google of anything here, just a hypothetical example.  Feel free to say GPT and Mattergen.)  The math community already worries about this stuff.

So:  If you are asked to review a paper or a grant proposal, bear in mind (1) the people doing the asking actually want your feedback, and (2) taking confidential documents and allowing them to be scraped by AI companies is bad.

Update:  This paper is highly relevant, showing very interesting consistency issues with LLMs as reviewers.

Materials-related postdoctoral opportunity at Rice, 2026-2027 edition

See here.

The Rice Advanced Materials Research Institute has launched its 2026-2027 competition for prestigious postdoctoral fellowships - see here:  https://rami.rice.edu/rami-postdoctoral-fellowship-program for details.  The actual application link is here.

If you are interested and meet the criteria, I'd be happy to talk.  I have some ideas that lean into the materials for electronics direction, and other possibilities are welcome.  

Science policy/funding updates, early October edition

This post is a bit later than I'd wanted, due to a combination of work and wanting to be in the right frame of mind to write about what's new in science policy (directly and adjacent matters) and funding.

• The NSF did underspend their federal appropriation for FY26 by more than 20%, obligating only $6.37B out of more than $8B budgeted.   In terms of numbers of awards, they made 2410 fewer awards in FY26 than in FY25, and about 5000 fewer awards than typical in FY21-24.  
• This includes the almost complete evisceration of the Social, Behavioral, and Economic Sciences directorate.  As that Science news article points out, SBE has until now funded about 2/3 of all US research in the social sciences (including linguistics and archeology).  The presidential budget request has been calling for SBE's elimination for the last two years.  Congress has rejected that in its budgeting, but seemingly OMB has gotten its way regardless.  
• There are more NSF X-Labs topics on the way, and a webinar next week to talk more about the "AI for Physical Systems" one.  
• NSF has also created a "metascience" office and released a statement about collaborating with the UK on this.  I've given my take on metascience before - the idea of seriously studying which types and mechanisms of research funding and programs give the "best" "results" is good in principle, but extraordinarily difficult in practice.  The idea that sound conclusions can be drawn in just a few years is absurd.  
• On the unambiguously positive side (gotta take the win when there is one), the NSF did announce the surprise support of the National Math Stars effort. 
• NSF also announced the first of their new Grand Challenge programs, rumored to be a possible destination of (some of?) the unspent funding from the top point above.  No real information about them yet, though the Quantum+X one has a webpage where you can sign up for updates.  Given the description ("Whether you're a researcher at a university, a startup, or an established company, this prize challenge is your chance to help define the next era of quantum technology."), it's hard not to wonder if this is another conscious effort to have NSF be a funding vehicle for industry/business rather than longer-term research.
• These announcements happened in part at the "Science: A New Golden Age Summit" (link to White House release about this.).  The National Medal of Science was presented to various tech leaders (not scientists).  If any of my readers attended this event, I'd be very curious about a first-hand account.
• DOE has announced the Genesis Mission Graduate Fellowship program.  The idea is a 4-year PhD with "cocompetencies" between a discipline and AI, with required extended internships at DOE labs/user facilities and industrial partners. The actual call is here, with a LOI due on 9 November and a preproposal deadline of 23 November. 
• For those of you who are PIs in condensed matter physics, the new DOE notice of funding opportunities (pdf) is out.  Pay close attention to the condensed matter physics program, as its focus has shifted.  
• Similarly, the new Air Force Office of Scientific Research BAA is out, and as with DOE, the focus of the condensed matter program has shifted.  Both DOE and AFOSR are now explicitly very interested in quantum geometry.  

On the more general research landscape:

• It's pretty clear that no matter what happens in the upcoming US elections, the next two years at least are likely to be comparatively bleak for federal support of science and engineering research.  Fundamentally, regardless of what OSTP says and despite glossy announcements of new programs, it sure seems like the executive branch (OMB) still wants to curtail federal support for research, and there is not much that even an opposed Congress alone can do in the near term.
• The number of STEM PhDs entering the job market in 5-ish years is going to be 25% down or more, because funding uncertainty has led to two consecutive years of double-digit decreases in admissions.  Remember, only 10% or less of STEM PhDs go into academia, so this demographic drop is going to be largely felt by industry.  I remain surprised by the apparent apathy about this.  If I thought my technical workforce applicant pool for some jobs might decline by double digits, I'd at least have some concern.
• Perhaps industry is collectively assuming that AI will somehow make up for this.  OpenAI released 722 preprints out there this week with results in math and mathematical physics.  This is simultaneously impressive and awful, and much has been written about it.  See here for an article and here for a weekly digest, from Quanta.  Peter Woit is hosting an interesting discussion, and points to a collection of comments about this.
• The US administration also announced a rule change that would impose a $70000 charge for "curricular practical training" (the mechanism that allows international students on F1 visas to have internships during their time as students) and a total of $100000 in fees for "occupational practical training" (the mechanism for international students to be allowed to work in the US for a period after completing their studies).  The actual proposed rule change is here, and people can submit public comments here until November 9.  Personally, I think that this rule change is yet another component of a seeming concerted effort to make the US unattractive as a destination for international scholars, a strategy that is incredibly self-defeating for the country.  (Sure looks like a lot of the "yes, kill OPT" comments are verbatim copy/paste of the same text.  Seems like someone has seen prior public commenting efforts on other controversial rule changes and decided to mobilize.)  Like the prior proposed duration of status changes for F1 and J visas (injunction discussed here), there are likely to be multiple big lawsuits filed over this.  

Whew.  This was a lot.  It's hard to maintain my customary equanimity when the pace of disruptive news is this rapid.  I will hopefully write more about some cool science soon.

The arXiv - where it's been and where it's going

Back in the ancient mists of time, scientists and mathematicians would circulate preprints of their articles among friends and colleagues via the postal service, as a courtesy, to get feedback and to try to make sure people in the community were aware of their forthcoming work.  As the wikipedia entry says, with the advent of widespread LaTeX and the development of the web, Paul Ginsparg (then at LANL) put together an html-based site for electronic sharing of preprints, initially at xxx.lanl.gov (back before "xxx" in URLs was the kind of thing filtered and blocked by employers).   In 2001 he moved to Cornell, and by then the lab was perhaps relieved to see the site, rebranded as the arXiv, shift to Cornell's library/repository infrastructure.   PIs my age remember (fondly? maybe?) the old days of the arXiv, when Prof. Ginsparg's rather dry sense of humor pervaded the site.  The skull-and-crossbones logo.  The "help"/FAQ pages that basically said, "if you can't figure out how to .tar.gz all of your necessary LaTeX files, and you can't figure out how to make your .eps figures small, maybe you should reconsider whether you're smart enough to be sharing your ideas here".  The arXiv was for preprints, without peer review (though interesting follow-on sites like Scirate now exist for organized commenting on the articles).

From these modest beginnings, the arXiv has grown enormously, including imitators/spin-offs such as chemrxiv and biorXiv and socarXiv.  The arXiv has recently become an independent nonprofit, hired a CEO, secured multiyear philanthropic support, and hosts over 3 million articles.  It's been interesting seeing some level of complaints online about some of these steps, but when the audience is so large, not everyone is going to be happy.  Rapid growth has been a major issue - see here for a graph of monthly submissions:

The exponential rise (except for a slight pandemic-correlated shoulder) has been problematic, especially recently.  One hallmark of the arXiv over the years has been its ability to function with comparatively minimal need for "moderation".  Early on, one consequence of the minimalistic help and moderate technical entry barrier was that it was unusual for fringe/pseudoscience to make its way onto the server.  (Hence the establishment of viXra.)  With the ease of cranking out properly formatted readable manuscripts using AI, clearly the arXiv has been struggling.  If 10-15% of submissions need some kind of human intervention or review, the support needs are rapidly outpacing the limited count of support staff.  There can be substantial backlogs.  To help deal with this, the arXiv recently updated its policies regarding AI-generated content (and AI cannot be a co-author, because the AI tools cannot take responsibility for content), and most recently has had to limit submission rates to two papers per month per submitting author.  These moves, too, have drawn some criticism (e.g. here).  Personally, I think the operators of the arXiv face an incredibly challenging environment and are doing the best they can - the idea that they are making moves because they are establishment sticks in the mud who don't understand the New Way of Doing Science is just wrong-headed.

It's completely unclear where all this is heading.  Exponential growth in nature signals instability and does not continue forever. If proponents of very heavily AI-driven research want to establish a repository specifically for that work, that's up to them.  [It is very on brand for the hard core AI advocates to argue that the arXiv is somehow morally obligated to host everything (regardless of hardware or personnel costs) so that future AI tools can read everything (a repository growing too quickly for human researchers to keep up) and summarize it.]

One overarching point that should come up in any arXiv discussion: The arXiv has become a global repository for an enormous amount of human knowledge, without charging anyone publication fees.  This should make interested parties think reallllllly hard about economic models of for-profit publishers. 

Annual Nobel speculation thread

 

It's that time of year yet again.  The physics Nobel will be announced next Tuesday, and the chemistry prize on Wednesday.  Who will it be this time?  Please speculate in the comments.  As is my annual futile tradition, I will put forward that the physics prize could be Aharonov and Berry for geometric phases in physics (even though Pancharatnam is intellectually in there and died in 1969).  This is a long shot, as always, especially since last year's prize for “for the discovery of macroscopic quantum mechanical tunnelling and energy quantisation in an electric circuit” was condensed matter related.  Perhaps optical metamaterials, with Yablonovitch, Smith, and Pendry?  (Though that's another one where picking just three names is challenging.)  Astro-related is likely due, so perhaps something CMBR related?

Brief science items - September 2026 edition

Several science items of interest from recent weeks.  As always, apologies for missing some, which I'm sure to have done.

• A month ago, Premi Chandra, Piers Coleman, and Clare Yu published a really nice memorial biography of Phil Anderson, one of the great scientists and characters of 20th century physics.
• A few days ago Dam Son, an outstanding condensed matter theorist at U Chicago, posted a paper on his site that resolves a math issue that had been lingering related to a well-known paper from back in the heyday of anyon superconductivity.  The authors had always been afraid that their approach accidentally violated a sum rule.  It turns out, the authors had just misplaced a factor of 1/2, and their approach was actually exactly right.  The really novel bit here is that the paper is written as if it is single-authored by Claude, and acknowledges Dr. Son for prompts that led to the result.  See here for an interesting twitter thread on this via Sankar Das Sarma.  
• Tangentially related, Anthropic and Matt von Hippel achieved a new result, a 9-loop perturbation theory calculation based on N=4 super Yang-Mills theory.  These kinds of mathematically virtuosic calculations are exactly the sort of task that AI tools to which are extremely well suited now.  
• Three weeks ago, a neat paper appeared in Science Advances.  These folks used quantum interference of a Bose-Einstein condensate to test the equivalence principle in a quantum system.  The basic idea is, you take an ultracold atomic gas in a well-defined quantum state.  You split it and toss one component of it upward, while you hold the other component of it fixed in the lab frame. (This work is a descendent of this approach, which was happening in the lab above mine in back when I was in grad school.) The upward-thrown component accumulates quantum phase as it rises in the lab gravitational field, slows to a stop, and comes back down.  There is a specific amount of phase difference between the two components predicted by the equivalence principle (which says that inertial mass and gravitational mass should be exactly the same), and that's what the authors find.
• A couple of weeks ago, this paper appeared (shoutout to the first author, who is a Rice undergrad alum).   The authors fabricated a nanomechanical resonator made out of LiNbO3 and coupled it to a qubit to act as a measurement device.  Remarkably, through the qubit they are able to see transitions between individual vibrational quantum numbers in this many-atom mechanical resonator.  This is quite impressive, and it opens up many possibilities for transduction between different quantum degrees of freedom.  

More soon.

The NSF memo - why is it so concerning to many?

Last week the NSF issued a new memorandum describing the changes that they plan to make in agency programs and operations to implement the Golden Age of Science ideas advocated by the White House Office of Science and Technology Policy.  It has been reported (Science, Nature) that many scientists are concerned about what is in the memo.  The first words of the Science article: “For many U.S. scientists funded by the National Science Foundation (NSF), the agency they know and loved died on 10 September.”  I will try to lay out why some people feel that way.

The memo outlines changes to operations that will fundamentally alter the character of the agency.  Generally most of the ideas are not a priori bad if the agency were in an environment with greater resources, when experimentation with alternative funding schemes and evaluations was not a less-than-zero-sum proposition.  Instead, these ideas are being put forward at a time when the NSF is underspending (for no obvious reason by the non-technical people in leadership roles) its appropriation for FY26 by around 18%.  This self-imposed budget austerity takes a bad situation (great uncertainty for everyone, drastically reduced staffing, delayed/eliminated/consolidated programs) and makes it considerably worse.    Now this memo outlines plans to take resources away from historically core programs and redirect them to new, untested initiatives, and to do so in ways that don’t always seem internally consistent.   

The memo talks about trying to fund certain investigators for longer periods (e.g. five-year awards) with minimal goal direction (so that PIs are free to explore where ever the spirit moves them – across all of NSF’s portfolio, or only in chosen administration priority areas?), but there is no adequate discussion of how those people will be chosen.  At the same time, there is talk of “golden tickets”, where individual reviewers in an already stripped-down review process can earmark some proposals for elevation, again with little explanation of how this will work.  Without careful safeguards, this combination seems problematic, and the assertion that this will lead to higher risk/higher reward research unsupported.   The memo also talks about short-duration, small budget awards for really risky proof-of-concept ideas.  This isn’t crazy and the EAGER program has been good, but the idea that the key to enabling success in high-risk research is to reduce the budget and the timeline doesn’t make much sense to me.    

There is a through-line that the agency is trying to treat workforce development as separate and distinct from funding research projects.  As the Science article says, “Traditionally, most graduate students and postdocs are funded through a research grant to their adviser or lab chief. But that will no longer be the case. Instead, the memo says, ‘Talent development funding opportunities may be coordinated with [research]-focused activities, as appropriate, but will be distinct and goal-oriented efforts.’”  The memo mentions nurturing talent through the NSF Graduate Research Fellowship program and proudly talks about how this was just renewed.  What it doesn’t tell you is that it was renewed at a considerably lower level than in previous years, which seems completely at odds with the claim of bolstering the program.  Similarly, the memo talks about expanding access to shared infrastructure like cleanrooms, etc., but stated targeted funding levels of programs like the NQNI are no higher now than they were 12 years ago, not even accounting for inflation. (I assume they will actually make NQNI awards.)  If NSF leadership keeps slashing their own budget, in defiance of congressional appropriations, it won’t matter what their priorities are. 

Lastly, let’s talk about “metascience”, the comparative study of different research funding models and practices, with the goal of a “self-improving NSF”.   Again, the essential idea of doing careful studies of alternate funding mechanisms and research team structures and practices to improve research outcomes (not a trivial matter to define) is not bad.  Doing this well is hard, because of several obvious reasons:  How do you define successful research – by scholarly impact, by patents/economic impact, by production of educated scientists, some weighted average of these?  On what timescale do you do this evaluation?  The Einstein-Podolsky-Rosen paper was hardly cited for decades, and it is now arguably one of the most influential papers of the last hundred years, with enormous impact on quantum science and technology.  How do you have sufficiently large samples and sufficiently long constant overall conditions to get reasonable statistics?   There are strong practitioners of metascience out there, but when the memo says “These efforts ultimately serve a concrete ambition for NSF to double the scientific productivity and impact generated by each federal research dollar by 2036”, how can one take that seriously?   No definitions of productivity or impact, and an implication that there will be optimization and major programmatic changes within less than two cycles of the much-vaunted five-year grants?   The word “ambition” is doing all the work in that sentence.  

Oh, and while all this is going on, the agency (among others) has now eliminated language from its integrity policy that used to say that political interference in grants and operations is bad.  I’m sure that’s nothing to worry about.

There is tremendous uncertainty in funding from multiple agencies these days, and this has resulted in many universities cutting back on doctoral admissions in the sciences and engineering.  This guarantees that there will be fewer PhD recipients in a few years across these disciplines.  The large majority of PhDs in these areas do not go into academia and instead have formed the base of technical knowhow across diverse sectors of the US and global economy for decades.  Cutting the supply like this will definitely have long-term consequences beyond just the halls of academia, affecting US competitiveness in ways that will take years to unravel.  Adding to this uncertainty is not helpful to anyone.

These are among the reasons why many find it hard to read that memo in the context of everything going on and feel optimistic that the proposed changes in NSF operations and direction will lead to a golden era for research.

 

Science communication - importance, insights

This past week we launched SCOPE, a new center for science communication and public engagement.  We marked the occasion with a fun symposium, as well as a Science Café event the preceding evening and a public science openhouse yesterday.  The symposium was very enjoyable, with a panel that comprised Kelly Weinersmith (known for many things, including an outstanding podcast and popular science books such as this Hugo-award-winner), Peter Hotez (tireless champion of vaccine development and pushing back on disinformation), Eric Berger (space editor for Ars Technica, founder of spacecityweather and theeyewall, two excellent sites for no-hype weather information), and Briana Rapini (one of The Amoeba Sisters, creators of a youtube channel with 2.9M+ followers).

You might have picked up from my 21 years of blogging that I think science communication is of great importance.  We've learned amazing things about how the world works, and I think we'd all be better off if more people knew about them and about the process of learning and discovery.  If there is public investment in research, then it's incumbent upon researchers to make sure that the public has the opportunity to learn about the fruits of those labors.  When the government, NGOs, and corporations make policies and strategic decisions that involve or depend on technical knowledge, we need to do our best to help those be informed decisions.   Once upon a time, Congress had a research office to help their staff and office holders understand technological issues.  It was killed in 1995 as "wasteful" and allegedly partisan. <sarcasm> thank goodness no technology-oriented issues have come up before the US government since then.</sarcasm>  (I am very tired of victim-blaming that presents mistrust of science or partisan razing of the research ecosystem as somehow the direct fault of scientists who failed in the communication mission.  Communication could have been better about many things, but complex societal forces are, in fact, complex, and there are many deep-seated reasons behind where we are right now.)

There were a few key points that came out of the panel above and from related discussions at the symposium.

• Know your audience and put yourself in their place.  What would you want to hear?
• Respect your audience.  You can avoid jargon without condescension.
• Ascribed to my colleague Neal Lane:  "The general public expects that you're smart.  They want to see if you're human."
• Listen to your audience.  Ascribed to Will Rogers:  "Never pass up a chance to shut up."
• If you're hesitant to do your public-facing project (writing, podcast, videos, etc.) because it's not flawless, just push through and do it.  The way to get good at this is through practice, not perfectionism.

There is a real dilemma out there about the degree to which practicing scientists can and should put effort into science communication.  Very few people in the US can name a single active scientist.  Among scientists and engineers, there is still sometimes an attitude of "Why are you spending your time on this?  If you are, you must not be a serious researcher."  It is true that, if you're a faculty member teaching and running a research program, you have to carve out time to do this, and those efforts are historically not well rewarded by many evaluation schemes.  Yet, I still think it's important, and programs like those run by SCOPE are hopefully going to help those who have an interest in science communication develop their skills and get valuable experiences.

Negative thermal expansion

Some interesting science results recently, but I wanted to talk about one a little off the beaten path.  Most people have some exposure to the concept of thermal expansion, the idea that solids tend to increase in size as temperature is increased.  This is why people suggest running a stuck (metal) lid on a glass jar under hot water to make it easier to open - the idea is that the metal expands more with increasing temperature than the glass.  This is why there are flexible joints between sections of concrete road, rather than trying to cast the road in one giant section.  Thermal expansion of the pavement would otherwise buckle the roadway.  

Vibrating H2 molecule, electron density
from DFT, by Dr. Or Cohen.

Where does thermal expansion originate?  In a toy model, we can think of the bound atoms in a solid like balls and springs.  The springs in this case model forces between the atoms that result from the electrons involved in the chemical bonds that hold the solid together.  (We usually think of the nuclei as slow and the electrons as fast, so you can consider the nuclear positions, somehow solving for the electron density given those positions, and figuring out the net force on the nuclei.  There is a whole subfield now in shortcutting these calculations with machine learning.)  In an ideal harmonic oscillator, the potential energy is perfectly symmetric around its minimum position.  Giving the oscillator larger and larger amounts of kinetic energy therefore does not change the time average separation of the atoms. 

When dealing with interatomic potentials, though, the potential is anharmonic - the effective spring is softer in extension than compression.  Another way to put it:  at small separations, the "steric interactions" caused by the Pauli principle give the "hard core repulsion" that tends to keep atoms from overlapping.  As a result, the potential looks like the cartoon (red dashed parabola = harmonic approximation that is good near the equilibrium position).  Now, if you give the atoms more kinetic energy, their time-average separation gets larger.  This is the conventional origin of the usual positive thermal expansion.  (Fun historical note.  In 1910, Lindemann, Churchill's friend ("the prof") and science advisor during WWII, put forward what is now called the Lindemann melting criterion: monatomic solids melt roughly when the root mean square thermal vibration displacement is about 10% of the interatomic distance.  This paper is hard to find online, btw.  Lindemann, Frederick A. "Über die berechnung molekularer eigenfrequenzen" Phys. Z 11, 609-612 (1910).),

Interestingly, some materials have negative thermal expansion - as temperature is increased, the materials shrink!  How does that work?  It seems to fly directly counter to intuitive expectations.  Negative thermal expansion often involves materials with lots of open volume in their structure, built out of rigid subunits (e.g. tetrahedra or octahedra of atoms).  As temperature increases, the subunits can deform a bit and also can rotate in ways that allow them to pack more efficiently.  An example of a material like this is zirconium tungstate.   That brings me to this article in JACS, which reports colossal negative thermal expansion in a metal organic framework compound, with a fractional change in volume of around -0.0006 per Kelvin near around 50 degrees C.  This negative thermal expansion coefficient is six times larger than the previous record, and seems to result from distortion of Zr6/oxygen tetrahedra.  Pretty neat, and these kinds of motifs could lead to materials with more designer thermal structural properties.

NSF, spending, and the end of the fiscal year

We are less than one month away from the end of the federal fiscal year, and traditionally there are internal deadlines for agencies to allocate their final spending by around September 9. Right now, the NSF is on track to issue about 4000 fewer (!!) awards in FY26 than it did annually back in FY21-FY24, and 2000 fewer than it did in the incredibly tumultuous FY25 (with its government shutdowns and mass cutbacks in agency personnel). This is dire, if like me you are a supporter of the agency and its vital role in the US research ecosystem.  

Perhaps even more distressing, the NSF is on track to underspend its FY26 budget appropriation (congressionally approved, presidentially signed) by between $1.25-1.5B, or 15-18%. This is essentially unprecedented - in the past, the NSF has always spent ~ 99% of its appropriation in a given fiscal year. Some large portion of this is from the mid-FY clawbacks that were reported in Science and Nature, supposedly squirreled away to support an as-yet unannounced OSTP "grand challenges" program.  

While technically the funds don't go away at the end of September, this kind of underspending raises the possibility of a pocket rescission. OMB and the executive branch have been pushing for massive cuts to the agency; Congress has disagreed. It sure looks like all the "see, don't worry, Congress didn't allow big cuts to the NSF" palliative statements don't hold up very well to scrutiny, if the majority party is content to just give up Article I power to the executive branch. 

In this period of complete flood-the-zone craziness, the mainstream news media seemingly doesn't have the bandwidth or interest to report on this; they seem to have judged that it's too obscure, it doesn't play in Peoria, the public doesn't really care. This kind of disruption will have ripple effects that last for many years and affect US scientific and economic competitiveness, and it's happening without much notice.

This week's news about an agreement between NIH and DOD to funnel NIH funds for infectious disease to DOD (or, in the official statement, to work together on projects of mutual interest), is at least getting some public attention.  Agencies agreeing to pass around at minimum hundreds of millions of dollars outside congressional oversight or what the appropriations acts say is another example of an Article I crisis, when the majority party basically hands over what are supposed to be congressional powers to executive branch.

(An additional sciencey blog post coming soon!)

Lab safety - seriously, be careful out there

This past week was a genuinely horrific reminder of the importance of lab safety, especially in the realm of hazardous chemicals.  

First, a graduate student at Hokkaido University was killed due to some kind of large-scale exposure to hydrofluoric acid.  For those who don't know, HF is used at some rate in semiconductor-related work, because it's a way to etch SiO\(_2\) from silicon surfaces and leave a hydrogen-terminated surface.  (Usually this is done using buffered oxide etch, which is less concentrated than the pure acid but still must be handled with great care and appropriate personal protective equipment.)  Accidental exposure to small amounts of HF is not always immediately obvious, because it is not that aggressive in damaging human skin (unlike, say, nitric or sulfuric acid).  Rather, it attacks the calcium in bones (as well as screwing up many other biological processes).  The topical treatment is calcium gluconate gel, which can help by being a much more readily accessible source of calcium ions to bind with the fluoride ions.  There are no real details out yet about how someone had a massive amount of HF splash on their head/face, but that sure sounds like a terrible case of poor storage and handling practices.  

Then it came out that this past Wednesday a doctoral student at MIT had been exposed to dimethyl mercury.  Here is a reddit discussion thread in r/mit, and here is another one on r/chemistry.  Apologies for the reddit links, but there doesn't seem to be any news reporting about this yet.  From the MIT announcement in those threads, it was in building 18, and decontamination of the space is ongoing.  Any scientist of my generation knows about dimethylmercury because of the horrifying death of Dartmouth chemistry professor Karen Wetterhahn in 1997.  She was exposed to tiny drops of this stuff, which diffused through her latex gloves (which she did not realize at the time).  Prior to her death, people still occasionally used dimethylmercury as a standard in NMR measurements.  Organic mercury compounds are widely recognized as incredibly dangerous because tiny amounts can lead to mercury crossing the blood-brain barrier, leading to terrible neurological systems and death.  Once mercury is into organic tissues, it is very difficult to chelate the metal ions.  Again, there is a shortage of official information about this incident, but MIT's announcement made it clear that any synthesis or use of this compound is not permitted and was unauthorized.  

Update:  the latest from MIT’s emergency response page raises the possibility that there may not have been any exposure or dimethylmercury present.  Fingers crossed that this turns out to be a false alarm.

Update 2:  The always excellent Derek Lowe with a further discussion of what seems now to have (thankfully, hopefully) been a false alarm.

To students reading this:  PLEASE be careful in the lab.  Know the hazards of what you're doing, and use appropriate procedures and protective equipment.  If you ever have questions about safety, for goodness' sake please ask.  Your PI and your environmental health and safety team would far rather have you ask questions and be cautious then to do something dangerous.  No PI should ever make students feel like thinking about safety is unnecessary or overly cautious, and no PI should ever be hesitant about supplying or letting students purchase PPE.  

Recent superconductivity results + open positions at Rice

Much as I feel like I should write about the latest developments in US science policy, instead I want to point out two exciting recent superconductivity results.  Below I will also append a couple of other items, including open positions at Rice.

• 

  After Fig. 2b from here

  In this paper, researchers demonstrated high temperature superconductivity in a monolayer of Bi\(_2\)Sr\(_2\)CuO\(_{6+\delta}\) (Bi-2201).  The monolayer contains just a single CuO\(_2\) plane, and remarkably, the superconducting transition is only suppressed about 10% from the bulk value of around 35 K.  The authors were able to explore the phase diagram by tuning the oxygen content in situ, using vacuum annealing to drive out oxygen and ozone exposure to (seemingly gently) put it back in.  This allows them to examine a large swath of temperature/doping/magnetic field parameter space, showing evidence of critical scaling of the resistance near the transition as well as an anomalous metallic state.  There's a lot to digest here.  The mapped out zero-field phase diagram in a single device (shown here) is extremely impressive.  Studies like this can hopefully give new insights into what physics is truly essential to achieve high temperature superconductivity.
• In this paper, investigators placed exfoliated NbSe\(_2\) encapsulated by hBN in a split-ring resonator cavity, and they observed enhanced critical temperature (by 0.15 K out of 6.53 K, or an increase of 2.3%), critical field, and critical current when the resonance frequency of the cavity is such that it apparently couples to superconducting fluctuations in the material on the spatial scale of the cavity.  There is a ton of interest in using electromagnetic cavities to modify the properties of quantum materials - see this review.  As far as I know, this is the first time that coupling to the vacuum mode of a cavity has actually enhanced superconducting properties.  Exciting times.

It's worth noting that both of these papers come out of groups in China - Changgan Zeng at USTC and Yuanbo Zhang at Fudan.   

In other news:

• 
  The NSF is going to make about half the number of awards this year as it did in The Before Times (2021-2024), according to this news article in Nature.  Figure 1 (shown here) is striking.  The claim is that the NSF leadership is taking clawed-back FY26 funding of around $1B and saving it for some as-yet unspecified, unannounced OSTP "grand challenges" project.  
  
• NSF also announced "new" funding opportunities here.  As described in that article linked above, these are not exactly new - it's essentially a reorganization/rebranding of much of the NSF's portfolio now that they've eliminated divisions and retired older funding solicitations.  Noteworthy is that the amount of funding mentioned in these solicitations is all considerably lower than what the aggregate of the older solicitations used to have.  As a non-expert, it looks a lot like these solicitations are being prepared as if the presidential budget requested funding levels (you know, the ones that want to cut NSF by more than half) are the baseline.

Meanwhile, at Rice we have some faculty searches underway:

• The Rice Advanced Materials Institute is searching for an assistant professor with an expertise in computational materials (including AI/ML).  See here.
• Our chemistry department is searching for an assistant professor position with an emphasis including physical chemistry.  See here. 
• There will also be an AMO physics position posted shortly - I'll update with the link when that becomes available. Update:  See here.

Finally, Nano Letters is having a seed grant competition for grad students.  It's not much money, but it is good experience and can inspire graduate student creativity. (Full disclosure: I'm an associate editor for the journal.)

NSF - public comment, APS feedback opportunity

In case you weren't aware, in addition to the OMB proposed rule changes which just concluded their public comment period, the NSF has put forward proposed changes in their proposal procedures for public comment, and the last day for feedback is August 24.  The proposal and award policies and procedures guide (PAPPG) is to be replaced with the revised document called the "Guide for Financial Assistance" (GFA).

The proposed revised document is here: https://www.regulations.gov/document/NSF-2026-OTR-0001-0003 

The place to file a comment is here: https://www.regulations.gov/docket/NSF-2026-OTR-0001/document?withinCommentPeriod=true

The place read already-filed comments is here: https://www.regulations.gov/docket/NSF-2026-OTR-0001/comments

The Federation of American Societies for Experimental Biology has a brief summary of the proposed changes here.  There are a number of (IMO) problematic issues with the would-be revisions, not the least of which is they presumptively assume that the OMB changes are going into effect, including the very controversial ones that would allow termination of awards at any time, for any reason (including not aligning with presidential priorities), with no appeal.  It's a good idea to be aware of what's being proposed and to take advantage of the opportunity to provide feedback.  

Update:  The APS has also put together a guide to the proposed changes.

Speaking of feedback, the American Physical Society is doing a broad survey (beyond just physicists) asking for input about up to three things that people think the NSF does well and up to three things that the NSF should do differently.  It's open to everyone, and the response spaces are brief (500 char ea.). Again, if this is something that matters to you, I encourage you to contribute - it's quick.  

Reproducibility in materials research, and an anecdote

Yesterday I attended the 40th annual summer research colloquium of the Smalley-Curl Institute at Rice, a fun internal conference that provides a great opportunity for undergrads (including visitors), graduate students, and a few postdocs to present their work.  The keynote speaker was our EVPR, Prof. David Sholl, who gave a very informative talk about reproducibility in the chemical engineering/materials literature.  We hear a lot these days about crises of reproducibility in scientific research, and Prof. Sholl rightly points out that in some fields the expectation of reproducible results is high - no one would spend $1B on a chemical engineering plant if they weren't very sure that the catalytic processes were going to work as expected at scale.  Keys to reproducibility include, unsurprisingly, repeated results and independent replication.  One metaresult that was interesting is this paper, looking at the literature on metal-organic frameworks and how often there are published replications of syntheses; not as often as you would think or want!  

A truly surprising (to me, anyway) result is this one.  The Brunauer–Emmett–Teller (BET) (yes, that Teller) method is a long-established technique that uses gas adsorption measurements to infer the surface area of porous materials.  Many research groups were given identical raw adsorption isotherms and asked to calculate the specific surface areas, resulting in a surprisingly large spread of results (Fig 1 of the paper).  Clearly not everyone had the same analysis procedures even for a technique developed in the 1930s!

Some take-away lessons from this are encapsulated here, in an article titled "Five easy ways to make your research more reproducible".  Good stuff.  The talk raised a number of questions relevant to our present era of huge enthusiasm about AI-based materials research and "self-driving" labs.  If the AI models are all trained on the literature, and the literature is not representative of complete and reproducible procedures, that's a problem.  

One personal anecdote about reproducibility and its challenges in materials synthesis.  Twenty years ago (!), I was working with a colleague who had a postdoc who was synthesizing Fe3O4 (magnetite) nanoparticles via wet chemistry methods (see here). We did some fun electronic transport experiments bridging very closely spaced electrodes with such nanoparticles, and we saw some very dramatic hysteretic response kick in as \(T\) was reduced below about 120 K.  That's the temperature of the Verwey transition in magnetite, where the material enters a more insulating low temperature phase.  Basically all of the devices we made with that batch of nanoparticles showed this phenomenon.  Then the postdoc took up a faculty position and a senior grad student came in and took over the synthesis, and for several months, subsequent batches of nanoparticles just didn't seem to show the effect.  The key issue is oxygen stoichiometry.  Get a little oxygen rich, and you form nanoparticles that include some \(\gamma\)-Fe2O3, which doesn't have the Verwey physics and in nanoparticle form looks really similar in x-ray diffraction to the desired magnetite.  Anyway, we started working with a collaborator who could grow epitaxial Fe3O4 films, and in those devices the electronic effect was there all the time.  All this led to this publication and subsequent papers, and I still think it's a cool set of results about a nonequilibrium transition in a correlated material.  In the end, after several months the chemistry grad student did get back to making nanoparticle batches that showed the transition. It turns out that at some point he had changed the length of a piece of tubing in the gas manifold, and unexpectedly that had altered the reaction kinetics just a little.  Changing it back got the synthesis to be reliable again.  This is an example of how finicky materials synthesis can be!

PhDs - how long a doctorate should take, and a new pilot program

I think it's safe to say that most people who've considered the issue think that a doctoral degree in the sciences and engineering in the US often takes too long.  

How long?  According to the latest data (see here, Table 1-12), the median time to degree in the physical sciences, for example, is 5.7 years after starting the program, while in all of engineering it's 5.3 years.  

Too long for what?  Well, life, basically.  Any decision to go to grad school is inherently a trade-off with opportunity costs.  Graduate stipends remain low compared to expected wages in entry-level (bachelors degree-qualified) positions in the sciences and engineering in industry.  The long duration of doctoral programs is certainly a powerful disincentive for many who might be interested but are under financial pressures.  Family considerations are also a major factor.  From the perspective of basically any career path, thanks to the time value of money and ideas of seniority, it's better to get going earlier if you have the qualifications for the particular job.  Companies would rather hire younger (cheaper) people.

So, there are already strong reasons to think about shortening doctoral programs.  Now, with the proposed change in duration of status of student visas (rule here, with plenty of editorializing; legal challenges very likely forthcoming in September) to four years, there is additional pressure. 

Why do US programs take so long?  Don't they give PhDs in three years in the UK and Europe?  In the UK and Europe, a student enters a doctoral program after already pursuing and receiving a masters degree, with grad level coursework taking place there.  Thus they go directly into research.  In the US, in contrast, it is far more common for students to go directly into the doctoral program.  Likewise, in the US, it is far more common for funding for students to go through PI-written research proposals, while in the UK, the students come funded, so to speak.  

Enter a new pilot program from NSF, the UIDP [University Industry Demonstrated Partnership] Industry-Integrated PhD Scholars Program (I-PhD). The idea is to shorten the doctorate to four years, with at least one of those years on-site at a company.  As the announcement says, "Students' first year of funding will be provided by their universities, with the remaining years covered by NSF. Industry partners will provide matching commitments to cover at least one year of practical experience conducting dissertation research at a company site. Students will be co-advised by academic and industry mentors, equipping them with critical skills for their future careers."  The initial plan is $47M over five years, and there will be a webinar (see here) next week about this.   (Up front, I do want to disagree with the framing that existing PhD programs are geared exclusively for academic careers.  It's well established that the fraction of PhDs in the sciences and engineering who go on to become faculty is low, and most go into industry.  Faculty PIs know this.  Students know this.  The problem solving and analytical skills taught in doctoral programs remain highly valued outside academia, at least until AI replaces us all.)

This is certainly a very interesting pilot program.  There are rumors that the DOE Genesis Mission is going to put something extremely similar in place as well.   The implementation details will be enormously important.  (For example:  Who is eligible?  Who handles the coordination between industry and the university - that is, who does the match-making and how?   At the department-company level and at the particular academic/industrial advisor level?   How will intellectual property be handled?  Publications?  Project design? If there are economic challenges, how committed are the companies?)  Given that this is a form of NSF fellowship, it seems highly likely that it will only be open to US citizens and permanent residents.  Obviously, not every discipline is well-suited to this, in terms of there being a ready supply of companies set to buy in.  Still, it is absolutely worth seeing how this works.

Update:  Thanks to one of my colleagues for pointing out the fine print, which is here.  In brief, as expected this is only open to US citizens and permanent residents.  No indirect costs allowed.  There is a $16K cost-of-education piece that looks like a substitute for grad tuition.  The intellectual property issues have to be ironed out between the university and the company before the start.  Perhaps not unexpectedly, this is most likely to work well for programs and PIs who already have close collaborations with particular companies.  Engineering disciplines are most likely to fit well here, it seems, while basic research farther away from applications will have more challenges.  (Question:  will finance companies or AI materials companies be interested in supporting theorist/computational scientists through this mechanism?)

Papers and news items

First, some science, clearing out a number of papers and articles that I've been collecting for some time in my far-too-numerous browser tabs:

• I've written before (here) about dimensional analysis and similarity, techniques commonly used in the engineering world that can seem quasi-miraculous at times.  This paper gets into why this approach works, and different categories of physical similarity.  I'd mentioned it when the book came out, but this kind of thinking is also a key component of Anthony Zee's Fly by Night Physics.
• This review article is about fundamental limits in photonics and electromagnetics.  This is a very handy review that I'm going to point my students toward.
• On a lighter note, a colleague pointed me to this collection of (AI-generated) songs related to thermodynamics.    
• Speaking of thermodynamics, here is a recent paper about the thermodynamic description of wealth inequality (treating the flow of money in a physics formalism - see here for a prior discussion.).  Edging closer....  
• There was a nice post on substack about Wojciech Zurek's approach to decoherence in quantum mechanics (quantum darwinism).   Cleanly written.  
• Along these lines, this paper is a survey/guide to issues in quantum foundations and interpretations of quantum mechanics.
• Lastly, Jim Freericks has a new quantum mechanics textbook out (for free!), with the challenging idea of making the subject accessible without calculus or differential equations.  (I'm jealous.  My textbook's UK publisher would not let me use Steve Martin's quote for a chapter epigraph, but Prof. Freericks was able to do it - well played.)

And more news/policy-related items:

• The presidential science advisor and head of OSTP, Michael Kratsios, appeared before the House science committee this week, timed to be coincident with the release of OSTP's new report, "Science: A New Golden Age".  A lot has already been written by many people about this report, which contains a number of actual proposals, some good and others of varying degrees of vagueness/underwear gnomes-level magical thinking.  Two pretty good (in my view) takes on this are this article in ars technica and this policy piece by Cole Donovan (former OSTPer).  It's important to remember:  This is a policy document, not something that has automatic impact, no matter how the Wall Street Journal frames its reporting on this.  (Hint:  This document alone does not somehow grant the president the authority or ability to redirect $200B in research funding.  Maybe their reporting on this would be better if they hadn't laid off all their science reporters.)  It's important to pay attention to what is said here, without giving it more oxygen than it deserves.  It's also unclear whether anything OSTP is saying and doing is aligned with what OMB is doing.  Declaring a new golden age of science while simultaneously proposing large cuts in all the science agencies is not exactly a sign of coherence.  Derek Lowe at Science has it right, essentially.  Nature reports that the mid-year budget clawbacks from NSF are apparently going toward some OSTP grand challenge initiative, something about which Kratsios denied all knowledge when talking to the House committee.  
• Holden Thorpe also raises a key point, that universities need to get their collective act together, have a plan about the future of research, and act on it, rather than scrambling for remaining scraps while trying hard not to be seen.  The AAU is important, but hoping that the AAU will accomplish difficult tasks without individual institutions having to take a public stand is unlikely to be successful as strategy.  Organizations like SUFS, UCS, and FAS are pushing the agenda; universities need to decide how they want to play this.
• The first round of DOE Genesis Mission awards were announced this week in DC as well.  
• SpaceX had a pretty successful test flight of their huge rocket, culminating with unexpectedly soft-landing the second stage ("Starship") in the Indian Ocean.  If they really can get this working at the level of reliability and reusability they've done with the Falcon 9, it truly would be game-changing for large-scale payload to orbit.  (Data centers in space still make no sense btw.)
• This week was also a big one in the world of mathematics, with an AI tool (Claude Fable) being used to find a counterexample to the previously outstanding Jacobian Conjecture.  Here is a write-up by Fields medalist Terence Tao, and here is a discussion among other mathematicians.  That wasn't alone.  Here (link to x) is a counterexample being found to a conjecture in graph theory, and it approaches "proof by intimidation" - the human basically harasses and bullies the AI tool into the solution without contributing any intellectual argument.  It seems like it's only a matter of time before some major theoretical physics result gets generated by these tools, though it's important to note that many physics problems are NP-hard/just not integrable.  AI tools are impressive, especially since they're trained on the entire corpus of technical literature, but they are not miraculous:  Claude can't somehow factor large numbers efficiently, or exactly solve the many-electron interacting Hamiltonian for the Hubbard model, because those are truly difficult problems.  Update:  Here are Terence Tao’s slides about AI and the future of mathematics.  As usual, these are excellent.