Rust-CAS VS Random

I believe rust-decimal has float representation. If not Rust-CAS supports float with (via the Mpf struct) functions for addition/subtraction, multiplication/division, exponentiation and sqrts. I haven't officially released it (and won't for a while) so it's a mess of inefficient functions with no documentation but if you really want it it's functional. (I believe printing negative floats less than 1 is broken in that version)

A little computational math project, it's not my most popular library but it's certainly the largest and most capable. Planning on growing into a MacCaulay 2 style library. Not really meant as a production library though so much as a learning project and with a book/documentation for reference on computational math algorithms. (Like Geddes' book, but dumbed down and more applied)

Rust-CAS - General computational math library, has some functionality absent elsewhere. more a novelty than a highly-performant project like the others.

The general concept behind it is to have a generalized algebra library over all datatypes (square matrices,GF, Quotient rings, polynomials, algebras in the future ) and even user-defined sets and algebraic structures. This isn't something that exists in Rust as far as I know (a lot of the individual functionality doesn't even exist in crates.io like hurwitz quaternions). Macaulay2 is probably the closest example. The repository is horribly out of date, but it shows some of the general functionality.

Sure here is a an example (repository) (click "run" to see it work) contrasting the two in Rust, note that it is not fully symbolic, just the imaginary component. But the immediate advantage one can see is allowing direct computation without needing to modify the polynomial multiplication algorithm. (As noted in the source code, this is a purely theoretical advantage).

I can't help you with the specific website, but here's a trivial cli implementation of Game of Life.

I've been sitting on my hands when it comes to updating my library, but if you really want a fast test, you can use some of my research/implementation for RCPrime, with creditation of course. I'm not sure what algorithms FLINT uses, but I'm fairly certain that the RCPrime implementation is the most efficient for integers less than 2^35 (requiring 64 multiplications and only one strong fermat test) even if you implement with Montgomery exponentiation.

Here is a sample implementation along with the inverses of the first 128 primes (in hex). (Except 2, which can be easily checked by the &1 trick)

Not what one normally considers in CS, but producing a fast deterministic test for checking primality in the interval 0;2^64 with some extensions beyond. Fully constructing one to 2^128 is well beyond what is currently computable, however some progress has been made that surpasses published bounds.

Working on developing a faster and smaller primality check in the interval 0;2^64 with tentative extensions towards 2^65. While it performs satisfactorily for the intervals currently available, reducing the memory to less than other implementations is a major challenge.

See this other approach for a similar engine, that utilizes a linear bitvector to model cellular automata.

You are way overthinking it. For something like minesweeper you can just model an integer lattice, and use either a 1d vector of integers to represent the positions of the mines or a 1d bitvector and check the values in the chebyshev distance of 1 from the point. (If you use integers like in the first example, your system becomes a plane of 2^32, 2^32 dimensions and is bounded by the number of mines (64-bit integers) that can fit in your RAM)

You can look here for some slightly better ways to test for primality (ignore the different language).

RAND calls a hardware source of Johnson-Nyquist noise (basically electric static), and then performs some filtering on it to make sure that it's evenly distributed. There are faster methods, like a simple "linear" rng, but they frequently don't give as good results.