William Gilpin
@wgilpin.bsky.social
asst prof at UT Austin physics interested in chaos, fluids, & biophysics.
https://www.wgilpin.com/
Pinned
William Gilpin
@wgilpin.bsky.social
· May 22
We present Panda: a foundation model for nonlinear dynamics pretrained on 20,000 chaotic ODE discovered via evolutionary search. Panda zero-shot forecasts unseen ODE best-in-class, and can forecast PDE despite having never seen them during training (1/8)
arxiv.org/abs/2505.13755
arxiv.org/abs/2505.13755
Reposted by William Gilpin
Texas Science
@texasscience.bsky.social
· Aug 21
Three College of Natural Sciences Faculty Win NSF CAREER Awards
3 UT faculty in computer science and physics won an NSF award recognizing their potential to serve as academic role models.
cns.utexas.edu
Kudos to Edoardo Baldini, William Gilpin & Daehyeok Kim on earning Faculty Early Career Development Program (CAREER) Awards from the National Science Foundation!
#NSF #CAREERAwards #EarlyCareerDevelopment #TexasScience @wgilpin.bsky.social @utphysics.bsky.social
cns.utexas.edu/news/accolad...
#NSF #CAREERAwards #EarlyCareerDevelopment #TexasScience @wgilpin.bsky.social @utphysics.bsky.social
cns.utexas.edu/news/accolad...
Reposted by William Gilpin
Eddie Lee
@spintheory.bsky.social
· Jul 8
Innovation-exnovation dynamics on trees and trusses
Innovation and its complement exnovation describe the progression of realized possibilities from the past to the future, and the process depends on the structure of the underlying graph. For example, ...
arxiv.org
I'm excited to say that one of the most exploratory and thought-provoking papers I've worked on in recent years was just accepted at Physical Review Research.
Preprint here: arxiv.org/abs/2502.21072
#physics #innovation 🧪🦋 @apsphysics.bsky.social
Preprint here: arxiv.org/abs/2502.21072
#physics #innovation 🧪🦋 @apsphysics.bsky.social
William Gilpin
@wgilpin.bsky.social
· Jun 17
hi david, thank you very much :)
William Gilpin
@wgilpin.bsky.social
· Jun 16
Optimization hardness constrains ecological transients
Author summary Distinct species can serve overlapping functions in complex ecosystems. For example, multiple cyanobacteria species within a microbial mat might serve to fix nitrogen. Here, we show mat...
doi.org
Paper: doi.org/10.1371/jour...
Code: github.com/williamgilpi...
Explanatory Website & Code demo: williamgilpin.github.io/illotka/demo...
Code: github.com/williamgilpi...
Explanatory Website & Code demo: williamgilpin.github.io/illotka/demo...
William Gilpin
@wgilpin.bsky.social
· Jun 16
This work was inspired by amazing recent work on transients by the dynamical systems community: Analogue KSAT solvers, slowdowns in gradient descent during neural network training, and chimera states in coupled oscillators. (12/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
For the Lotka-Volterra case, optimal coordinates are the right singular vectors of the species interaction matrix. You can experimentally estimate these with O(N) operations using Krylov-style methods: perturb the ecosystem, and see how it reacts. (11/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
This variation influences how we reduce the dimensionality of biological time series. With non-reciprocal interactions (like predator prey), PCA won’t always separate timescales. The optimal dimensionality-reducing variables (“ecomodes”) should precondition the linear problem (10/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
As a consequence of ill-conditioning, large ecosystems become excitable: small changes cause huge differences in how they approach equilibrium. Using the FLI, a metric invented by astrophysicists to study planetary orbits, we see caustics indicating variation in solve path (9/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
How would hard optimization problems arise in nature? I used genetic algorithms to evolve ecosystems towards supporting more biodiversity, and they became more ill-conditioned—and thus more prone to supertransients. (8/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
So ill-conditioning isn’t just something numerical analysts care about. It’s a physical property that measures computational complexity, which translates to super long equilibration times in large biological networks with trophic overlap (7/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
More precisely: the expected equilibration time of a random Lotka-Volterra system scales with the condition number of the species interaction matrix. The scaling matches the expected scaling of the solvers that your computer uses to do linear regression (6/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
We can think of ecological dynamics as an analogue constraint satisfaction problem. As the problem becomes more ill-conditioned, the ODEs describing the system take longer to “solve” the problem of who survives and who goes extinct (5/N)
William Gilpin
@wgilpin.bsky.social
· Jun 16
But is equilibrium even relevant? In high dimensions, stable fixed points might not be reachable in finite time. Supertransients due to unstable solutions that trap dynamics for increasingly long durations. E.g, pipe turbulence is supertransient (laminar flow is globally stable) (4/N)