| Crates.io | quizx |
| lib.rs | quizx |
| version | 0.3.0 |
| created_at | 2025-05-04 13:59:39.945458+00 |
| updated_at | 2025-06-12 18:56:56.892857+00 |
| description | Quantum Circuit Optimisation and Compilation using the ZX-calculus |
| homepage | https://github.com/zxcalc/quizx |
| repository | |
| max_upload_size | |
| id | 1659663 |
| size | 595,678 |
PyZX is a Python library for quantum circuit optimisation and compiling using the ZX-calculus. It's great for hacking, learning, and trying things out in Jupyter notebooks. However, it's written to maximise clarity and fun, not performance.
This is a port of some of the core functionality of PyZX to the Rust programming language. This is a modern systems programming language, which enables writing software that is very fast and memory efficient.
Check the Rust Changelog for the latest updates.
As a very anecdotal example of the performance difference, the program spider_chain builds a chain of 1 million green spiders and fuses them all. In PyZX, you can fuse all the spiders in a ZX-diagram as follows:
from pyzx.basicrules import *
success = True
while success:
success = any(fuse(g, g.edge_s(e), g.edge_t(e)) for e in g.edges())
In QuiZX, the Rust code is slightly more verbose, but similar in spirit:
use quizx::basic_rules::*;
loop {
match g.find_edge(|v0,v1,_| check_spider_fusion(&g, v0, v1)) {
Some((v0,v1,_)) => spider_fusion_unchecked(&mut g, v0, v1),
None => break,
};
}
On my laptop, the PyZX code takes about 98 seconds to fuse 1 million spiders, whereas the QuiZX code takes 17 milliseconds.