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Statistical Physics with R: Ising Model with Monte Carlo
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Re: Statistical Physics with R: Ising Model with Monte Carlo
#52Earlier quoted context omitted.
Physics and Mechanics are not synonyms. The latter is a small subset of the former.
Yes, but this relation does but apply to statistical mechanics and statistical physics, they mean the same: https://en.wikipedia.org/wiki/Statistical_mechanics What is included in "statistical physics" that is not included in "statistical mechanics"?
There is a distinction. Usually statistical mechanics means the ensemble theory and partition functions that connects microscopic systems to macroscopic ones from material point of views. However, statistical physics is a bit more generic, for example complex networks may not use ensemble theory or partition functions and could use only statistics on the network, such as average neighbourhood or similar.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#53Why is this worth posting? Simulating a 1D Ising model is a homework exercise for undergrads.
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Re: Statistical Physics with R: Ising Model with Monte Carlo
#54Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
R is really not for production deployment. It lacks a lot of what made python popular, and its target users were radically different.
This is really a non issue now. R's problem back in the day was that it was really specialized in analysis and interactivity, but a lot of the general purpose stuff that made Python popular is now easily achievable in R and well-developed and maintained. RestRServe and Plumber are both excellent tools for REST APIs.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#55Earlier quoted context omitted.
Yes, but this relation does but apply to statistical mechanics and statistical physics, they mean the same: https://en.wikipedia.org/wiki/Statistical_mechanics What is included in "statistical physics" that is not included in "statistical mechanics"?
There is a distinction. Usually statistical mechanics means the ensemble theory and partition functions that connects microscopic systems to macroscopic ones from material point of views. However, statistical physics is a bit more generic, for example complex networks may not use ensemble theory or partition functions and could use only statistics on the network, such as average neighbourhood or similar.
People have also used “statistical physics” to refer to the former concept since forever. For example Landau.
“Statistical mechanics” is also used in a broad sense, just like “quantum mechanics” is often used for anything “quantum”.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#56Earlier quoted context omitted.
Physics and Mechanics are not synonyms. The latter is a small subset of the former.
Yes, but this relation does but apply to statistical mechanics and statistical physics, they mean the same: https://en.wikipedia.org/wiki/Statistical_mechanics What is included in "statistical physics" that is not included in "statistical mechanics"?
Kinetic theory stuff for one, like deposition, growth, sandpile type things. Complex networks and lots of dynamics stuff falls under statistical physics umbrella but not statistical mechanics. Stat mech's amazingly wide applicability makes it easy to think it's THE approach to approaching things statistically, but it's not. The broad encompassing approach has a name, statistical physics.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#57Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
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 wr…
I have a feeling that most data scientists using R have no need to touch any of the object systems, hard to believe that would be a deal breaker.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#58Earlier quoted context omitted.
There is a distinction. Usually statistical mechanics means the ensemble theory and partition functions that connects microscopic systems to macroscopic ones from material point of views. However, statistical physics is a bit more generic, for example complex networks may not use ensemble theory or partition functions and could use only statistics on the network, such as average neighbourhood or similar.
People have also used “statistical physics” to refer to the former concept since forever. For example Landau. “Statistical mechanics” is also used in a broad sense, just like “quantum mechanics” is often used for anything “quantum”.
What I'm getting from this discussion is that we use Statistical Physics to refer to anything covered by Statistical Physics AND Statistical Mechanics, while we use Statistical Mechanics in a narrower context, but it is also possible that some use SM loosely.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#59Earlier quoted context omitted.
I wonder how close R was to also take over the scientific computing/machine learning space, instead of Python's numpy/scipy ecosystem.
In statistical physics they still use C a lot, as far as I know.
Good observation. IsingLenzMC indeed core is written in C. R provides great C interfacing facilities.
Re: Statistical Physics with R: Ising Model with Monte Carlo
#60Earlier quoted context omitted.
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 wr…
The developing S7 object system ( https://github.com/RConsortium/S7 ) is looking fairly promising in that it combines many of the nice properties of S3 and S4 (validation, multiple dispatch, sane constructors) while still being fairly simple and straightforward to use.
Excellent news. Quite promising, but R's power is its been actually functional natively. Even binary operations are functions, `+`(x,y) would work as in x+y