Simulations of QEC codes with loss
Python package for sampling and decoding quantum error correction circuits with photon loss.
Install
Requires Python 3.10 or newer.
From pypi:
pip install qec-loss
# or with uv
uv add qec-loss
Local install
Please first install uv.
git submodule update --init --recursive
uv sync --dev
uv pip install -e . --no-build-isolation --group dev
uv run pre-commit install
The last command installs a git pre-commit hook that runs ruff format on Python and clang-format on C++ under src/qec_loss/_native/.
To format everything manually:
uv run pre-commit run --all-files
Quick start
import stim
from qec_loss import LossyCircuit, ForwardSampler, MonakaBuilder, add_loss_noise
stim_circuit = stim.Circuit.generated(
"surface_code:rotated_memory_z", rounds=5, distance=5
)
circuit = add_loss_noise(stim_circuit, loss_after_2_qubit_gate=0.01)
sampler = ForwardSampler(circuit, seed=7)
batch = sampler.sample(1000)
builder = MonakaBuilder(circuit, model_path="/tmp/monaka")
predictions = builder.decode_batch(batch)
See docs/api.md for the full API.
Test
uv run pytest tests/
1 maintainer
Metadata
1 maintainer
Release files for qec-loss 0.1.3
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| qec_loss-0.1.3.tar.gz | 8.5 MB | Details |
Built distributions (wheels)
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