Associate Professor @UCSanDiego, Cosmologist and Particle Theorist

Joined February 2019
This December, I will be trying another experiment: Each day I will post 1 under-appreciated paper/result (my definition/no rules). I will also be posting my choices on blue sky (dangreen.bsky.social). I am curious to see which site has more interesting feedback/discussion
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Reminder: most fields of basic science are driven by experiments and a key limiting factor is $$$ for equipment, materials, etc. AI companies have no incentive to pay for this kind of work (that's why it doesn't happen in industrial labs already).
This quoted post is unavailable.
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If I'm wrong, and AI companies decide to fund, eg, a 100 TeV collider, that would be great news for science and scientists. But this kind of work won't help them train models / make money, so it would be entirely philanthropic. The progress is math does not make this more likely.
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Why is it important to learn math? So that you can see a huge outlier like this one and realize it needs more explanation before publishing @nytimes * Duke's number is the median of 17 people, i.e. it's determined by 9 salaries (you might even be able to interview all of them)
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Daniel Green retweeted
Geopolitical Cousins dropped... a bit of a swerve! @JacobShap and I had our "Science Cousin" -- Cousin @nu_phases - come on to talk AI, innovation, importance of science, etc. He tried his best not to blow our brains with fancy schmancy big words. geopolitical-cousins.captiva…
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1. This should have never been a "field of physics". If a paper is so obvious 100 people write it in 24 hours, then it wasn't worth writing it in the first place. 2. Apparently not everyone knows what ambulance chasing means (I had to explain this term to students last week)
Ambulance chasing will be the first field of physics to be fully automated.
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There is a single common problem facing academia: People that claim to be experts trying to convince the world that learning/knowledge is unnecessary The world will not be a better place if: - Everyone gets a degree and no one knows anything - AI can think but humans cannot
I thought the tweet below must be omitting some critical context or paraphrasing the text ungenerously. But no, the NYT actually published an op-ed that claims the University of California hasn't sacrificed excellence even though it admits students who struggle with basic math.
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If AI is great at finding mathematical counter-examples, where are all new theories physics that contradict conventional thinking we were promised? Wouldn't AI have already produced a theory that replaces dark matter and dark energy already? Or a new approach to quantum gravity?
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Apparently, all these revolutionary ideas are on the internet but haven't been developed because of physics gate-keepers. If that is really true, throwing a few thousand agents at these problems should be generating loads of new self-consistent theories that are allowed by data.
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Daniel Green retweeted
College admissions is broken. It can be fixed. Liberals should own this cause, not cede it to the imbeciles who believe Trump lowered drug prices “by 1600%” washingtonpost.com/opinions/…
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Want to understand how we got to a point where a large fraction of UCSD students struggled with 7+2=6+[] (1st grade level)? Just look at the proposed solutions You can't make up 12 years of math with a few "evidence based" courses. Eliminating calculus is just accepting failure
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This is such an absurd claim it's actually pretty funny. A few years ago I went over 31 examples of breakthroughs from the past 40 years (excluding Nobel prizes) xitter.cf/nu_phases/status/15983… But 50+ years really opens up some all time great results:
Replying to @Hassaan_PHY
It's a fact that the foundations of physics have been stuck for 50+ years, everyone with half a brain can see that. The only "counterargument" against this are physicists who complain that writing a lot of papers is sorta progress.
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Inflation (1981): Guth lays the foundation for every theory of structure formation journals.aps.org/prd/abstrac… Later Linde, Albrecht and Steinhardt later improve the model to the point it makes a number of non-trivial predictions (many now verified)
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Quantum Computing (~'80): The idea that there are things that can be calculated faster on a quantum computer than a classical one has profoundly changed the relationship between the theory of computation and fundamental physics semanticscholar.org/paper/Th… link.springer.com/article/10…
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Science's Breakthrough of the Year 2025 is a failure of science reporting: (1) Installing solar power is neither science nor a breakthrough. (2) Rubin is a runner-up for being built? Scientific progress requires discoveries in the real word, not just meeting construction goals
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This kind of grade inflation hurts science. It is too common to declare something a breakthrough just for being popular. Science's breakthroughs have previously been very good and focused on real progress. It's sad to see them fall into the same trap. science.org/content/article/…
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