Statistical Physics with R: Ising Model with Monte Carlo
12 comments
·September 19, 2025northlondoner
R ecosystem provides amazing reproducible research ecosystem, even for statistical physics.
Qem
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
teruakohatu
I love and use R, but it never became the dominant ML in part because it has three (or more) different object systems and many libraries sort of use their own style.
This makes it seem a bit disjointed, in a way that other languages don’t.
The R community should have anointed one object system and made tidyverse a core part of R.
All that said, R is fantastic and the depth of libraries is extensive. Libs are often written by the original researchers that develop the method. At some academic institutions an R package is counted as a paper.
mvieira38
Agree 100% on tidyverse becoming part of the standard library. Some of the language's greatest libraries (like Hyndman's forecasting stuff) basically assume you're using tidyverse already
mamami
It was never close. Its synthax is unintuitive and painful to learn as a science undergrad. If it hadn't been python it would have been another language.
3abiton
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
shoo
R was developed for and by statisticians, for better and worse. I used R a little bit 15-20 years ago, what I remember was that quite a few libraries and function interfaces seemed to be designed to be convenient for interactive use, but if you tried to use them in an automated script, e.g. some analysis you wanted to scale up and repeat 10,000 times while bootstrap sampling or hyperparameter sweeping or what have you, those same library and interface design choices involved bizarre edge cases where functions would sometimes do something completely different (perhaps changing the return type) when invoked with slightly different arguments. All these automation hostile edge causes were annoying to discover and then work around.
larrydag
Very close. In fact you could still say that it still is competing with Python for users. There is still an active community of developers.
shiandow
In statistical physics they still use C a lot, as far as I know.
mhog_hn
One general purpose web framework away
rjdj377dhabsn
I disagree. R is just not a very nice language.
It has some really great statistical and data science packages that were well ahead of the competition 10-15 years ago. The web frameworks were good enough for dashboards and what most people were using R for.
But if you wanted to write fast and elegant nom-vectorized code, R is really lacking. I left it for Julia for that reason.
If you're interested in HMC, we showed how to apply it to the Ising model in https://arxiv.org/abs/1912.03278 with code available in https://github.com/HISKP-LQCD/ising_hmc