As for every astronomer next to a pool, it is impossible for me not to notice the similarity between the light patterns that refraction creates on the bottom of the pool, and the image of the cosmic web produced by cosmological simulations.
The similarity is not by chance, but there are deep connections between the two!
This is a visualisation of this first stage with a simple #Julialang N-body solver of mine.
There is no gravity force in the entire simulation - particle just "cluster" and produce a cosmic web pattern, because of the initial correlation of their displacement and velocity vectors
Introduction time! Hello fediscience members! I'm a new member in this instance, but I'm not new in the fediverse. I migrated from fosstodon.org to this instance. There's nothing wrong, I just needed a place where I can post in English and Spanish. I'm an Assistant Professor at CSU Stan. I usually post about #Rstats, #Quarto , #Linux, #juliaLang, #python, #psychology, #bayesian, #aging, #dementia, #mentalHealth, and other topics that I find interesting in #science.
Other "new" nice renderings of the growth of simulated clusters of galaxies by my former student Matteo Angelinelli, who kindly left all these gems in an hard disc!
I'm Leif ("life") and I do research into clouds an their effect on Earth's weather and climate using fluid dynamics simulations and machine learning.
I'm particularly interested in making better predictions about our planet's future weather and climate. Love all things science, technology and jazzy 🎶 🎵 🌍 🌎 🌏 🛰️ 💻
📢 Finally out the recording of the #JuliaCon 2023 talk we presented at MIT this July!
So grateful for the opportunity to present our package at such a wonderfully organized global conference with so many brilliant #JuliaLang users and developers!
At first, I was a bit skeptical of the new Modular's #Mojo language.
Having no binaries available (only a playground), and a long history of #Python contenders such as #PyPy or Pyston that never achieved full compatibility... was a huge turnoff.
The amount of Python compilers that never reach 100% compatibility is almost hilarious.
Having seen the tremendous amount of effort behind #Julialang, and how little is its community compared to Python's... adds on top of that.
While googling about Bayesian statistics, I found this awesome resource - Julia for Economists Bootcamp by Cameron Pfiffer. The course was recorded as part of Julia's sessions at Stanford's GSB. The course covers the following topics:
✅ Julia basics
✅ Parallelization
✅ Optimization and Automatic Differentiation
✅ High-performance Julia
✅ Computational Bayesian statistics
Is it very straightforward to run Julia code on GPU? Does it need special CUDA rewrites to work?
I do a lot of value function iteration for dynamic programming problems (I need global characterizations, approx around steady state doesn't work). Has anyone done this much in Julia? How's your experience been?
@mo8it@mose
Just watched the talk. My problem with the conclusion is, that Julia has the same problems as Python and is a bit harder to program and learn. Why should anyone bother using #julialang. On the other hand there are huge applications written in #python. So I assume, people don't care, or mix the languages.