https://github.com/plutoniumm/qudit
numpy based simple qudit simulations in python
https://github.com/plutoniumm/qudit
quantum-computing qudits
Last synced: 2 months ago
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numpy based simple qudit simulations in python
- Host: GitHub
- URL: https://github.com/plutoniumm/qudit
- Owner: plutoniumm
- Created: 2024-10-06T11:24:03.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2026-04-05T10:43:54.000Z (3 months ago)
- Last Synced: 2026-04-05T11:05:45.984Z (3 months ago)
- Topics: quantum-computing, qudits
- Language: Python
- Homepage: https://plutoniumm.github.io/qudit/
- Size: 2.74 MB
- Stars: 0
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
### `qudit`
High performance simulations for qudit systems. To make qudit machine learning, qudit error correction, and qudit circuit simulation easier. Qudit is made fully around `pytorch` to make it easy to mix and match tools without worrying about type errors.
[](https://pypi.org/project/qudit/)
```bash
pip install qudit
```
## Quickstart
In most cases it should not matter if you mix and match `pytorch` with `qudit` since most abstractions are built on top of `pytorch` tensors. The following is two examples to do the same thing, one using the `Circuit` class and the other manually using the matrices.
**Using the `Circuit` class:**
```python
from qudit import Circuit
import torch as pt
C = Circuit(2, dim=2) # 2 qBits with d=2
G = C.gates[2]
C.gate(G.H, dits=[0])
C.gate(G.CX, dits=[0, 1])
ket0 = pt.zeros(2**2)
ket0[0] = 1.0 # |00>
print(C(ket0)) # [1. 0. 0. 1.]/rt2
```
## Contributing
Qudit has a small shell scripts used to generate documentation and run tests. If you want to contribute, please fork the repo and make a pull request with your changes. The running script is `do`.
#### Commands
- `./do help`
- Helper for common workflows (build, tests, docs, etc.)
- `./do build`
- Builds `sdist` + `wheel` and runs `twine check dist/*`.
- `./do deploy`
- Uploads `dist/*` to PyPI via `twine upload` using an API token.
- Token is read from `FILE` (defaults to `.vscode/token.env`).
- `./do test`
- Runs the Python test scripts in `./tests`.
- `./do prof`
- Profiles `./tests/bench_fast.py` with `cProfile` and opens `snakeviz`.
- `./do head`
- Runs `python ./view/headers.py` (used by the docs pipeline).
- `./do docs dev`
- Runs the docs dev server (`npm run dev`).
- `./do docs build`
- Builds the docs (`npm run build`).
#### Common workflows
```bash
# run test scripts
./do test
# build packages locally
./do build
# build docs
./do docs build
# docs dev server
./do docs dev
```
#### PyPI token setup (for `deploy`)
Create a file containing only your PyPI API token (no `export`, no quotes):
- default location: `.vscode/token.env`
- or specify a different file via `FILE=path/to/token.env`
Example:
```bash
FILE=.vscode/token.env ./do deploy
```
## Acknowledgements
Many many thanks to [Sai Sakunthala](https://github.com/Sai-sakunthala) and [R-Phoenix](https://github.com/R-Phoenix) for testing and fixing bugs!
This library is built on top of pytorch, and takes ideas from Qiskit, Cirq, and QuDiet.
### Caveats
`qudit` does not, and will not support openQASM in the near future since hardware is not a goal. There are plans for some amount of interoperability with other qudit simulators, however that will be a long term goal and not a near term one. We will first make qudit stable.