#SimulatedUniverses
two clusters of galaxies form and merge into a larger one; here we track both the evolving gas density (left) as well as the relativistic electron content injected by all their galaxies (right).
Really sorry for the spam, but I'm hosting a #data event soon and I need to fill a bowl with data jokes. I have few but need MANY more. Here's an example of what I'm looking for:
"A query walks into a bar, sees two tables and goes 'can I join these'?"
🙏 PLEASE collective hive-mind of the fediverse, give me your best!
Today's swirling electrons:
initially located in the halos of galaxies, finally accreted and mixing in a cluster undergoing a merger, and leading to the formation of a (mega) radio halo.
ENZO simulation + #JuliaLang processing, visualisation with SAO Ds9
Using a raster image as orbit trap to plot a Julia set. The animation illustrates how the fractal structure is changed, as the area of the orbit trap is varying. #fractal#Juliaset#Julialang#image
#SimulatedUniverses
Fresh new visualisation (using #JuliaLang + SAO Ds9) of the evolution of a new massive cluster of galaxies, from z=30 to z=0, simulated with ENZO-MHD (+"my" cosmic rays). The mass is huge (~2e15Msol) and these clusters can only form in very large cosmic volumes, so the whole procedure requires to use aggressive adaptive mesh refinement to cover all necessary range of scales (the size of this "zoom" box is 25Mpc and the max resolution is 15kpc).
Uso mucho el paquete Unitful.jl para utilizar unidades en #julialang. Si además utilizáis Latexify.jl para que los resultados y cálculos queden bonitos, es imprescindible usar también UnitfulLatexify.jl para que las unidades queden bien.
#ChatGPT performs better on #Julialang than #Python (and #Rstats) for Large Language Model (#LLM) Code Generation. Why? This blog post shares recent the research and adds a bit of details into where I found LLMs and new language learning having issues.
Here‘s another interesting #julialang, #python, #rstats comparison: „count the number of vowels in a string“. #julia uses an anonymous function as an argument to count(), #python iterates over the string using list comprehension, #rstats does the same but in a vectorized way
El paquete de #julialang clapeyron.jl (*) es una pasada para hacer cálculos con funciones de estado para fluidos. Un montón, pero muchos muchos, de modelos disponibles para poder calcular Cp, Cv, U, G y mucho más.
Escribir ecuaciones en #LaTeX es bastante pesado. Afortunadamente está el paquete para #Julialang#Latexify.jl. Escribes la fórmula y la transforma en LaTeX de manera muy arreglada. Por ejemplo:
julia> using Latexify
julia> @latexify L = z/(f_hln(10))(10^((T_2-T_ref)/z)-10^((T_1-T_ref)/z))
I love graphs from dynamical systems theory and analytical mechanics.
I love those curves in phase space etc.
That makes me want to understand them better.
I have discovered the book "Structure and Interpretation of Classical Mechanics", that teaches mathematical physics and the #programminglanguage#scheme but it looks quite annoying to work in Scheme with my 💻.
So, are there similar books/courses/resources with similar means to an end? Maybe in easier to use programming languages? Like #julialang#julialanguage
@rml yeah, I don't think I can go through the book SICM without coding in Scheme or similar... But I was curious also about other things, see for example "Nonlinear Dynamics" (Datseris, Parlitz) with #julialang.
This would probably be easier for me, coming from Python over all else, and with some experience in R and MATLAB from the bioengineering years. Also, I want to study Julia regardless.
But I understand I could use Clojure in JupyterLab/Notebooks, and if running Clojure+SICMUtils reading SICM is actually all I need, I might go for it.
If instead I need to learn lots of other basics in the programming language and installing all tools, I must postpone it to god knows when :/
Do you have any suggestions or tips? Consider I know nothing beyond the names I quoted
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!
📢 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.