Source-available Rust/Python QEC R&D platform with PyMatching-compatible validation, belief-matching, BP-OSD/qLDPC workflows, CPU/GPU batch decoding, and artifact-backed benchmark evidence
Project description
QECTOR Decoder v3
Source-available Rust/Python quantum error correction decoding platform.
QECTOR Decoder v3 provides a Python package backed by a native Rust extension for quantum error correction research and validation workflows. It includes PyMatching-compatible MWPM validation, Union-Find decoding, belief-matching experiments, BP-OSD/qLDPC workflows, batch decoding, and optional GPU backend checks where the release build and target machine support them.
Website: https://www.qector.store
Repository: https://github.com/GuillaumeLessard/qector-decoder
PyPI: https://pypi.org/project/qector-decoder-v3/
Commercial licensing: https://www.qector.store
Installation
Recommended command:
pip install qector-decoder-v3
Verify the install:
python -c "from qector_decoder_v3 import UnionFindDecoder, BlossomDecoder; print('QECTOR OK')"
Optional research and validation extras:
# Stim, Sinter, PyMatching, LDPC and belief-matching ecosystem
pip install "qector-decoder-v3[stim]"
# Benchmark and plotting harness
pip install "qector-decoder-v3[bench]"
# Full validation environment
pip install "qector-decoder-v3[all]"
Supported public wheels
QECTOR v0.5.x public releases target standard CPython wheels for:
| Platform | Wheel status |
|---|---|
| Linux x86_64 | Published |
| Windows x64 | Published |
| macOS arm64 / Apple Silicon | Published |
| macOS Intel x86_64 | Not published in v0.5.x public CI |
CPython free-threaded builds such as cp313t |
Not published in v0.5.x |
Supported Python classifiers are standard CPython 3.9 to 3.13.
Windows note: do not force py -m pip unless you have checked which interpreter the Windows launcher selected. If py selects a free-threaded interpreter such as python3.13t.exe, pip may fall back to a source build and fail because the public repository does not ship the proprietary Rust core. Use the standard active Python environment instead:
pip install qector-decoder-v3
python -c "from qector_decoder_v3 import UnionFindDecoder, BlossomDecoder; print('QECTOR OK')"
Check your Python launcher targets with:
py -0p
Quick start
import numpy as np
from qector_decoder_v3 import UnionFindDecoder, BlossomDecoder
check_to_qubits = [[0, 1], [1, 2], [2, 3], [3, 4]]
n_qubits = 5
syndrome = np.array([0, 1, 0, 0], dtype=np.uint8)
fast = UnionFindDecoder(check_to_qubits, n_qubits)
print(fast.decode(syndrome))
mwpm = BlossomDecoder(check_to_qubits, n_qubits)
print(mwpm.decode(syndrome))
Batch decoding:
import numpy as np
from qector_decoder_v3 import BatchDecoder, CUDABatchDecoder
checks = [[0, 1], [1, 2], [2, 3], [3, 4]]
syndromes = np.random.randint(0, 2, size=(4096, 4), dtype=np.uint8)
cpu = BatchDecoder(checks, n_qubits=5)
corrections = cpu.parallel_batch_decode(syndromes)
if CUDABatchDecoder.is_available():
gpu = CUDABatchDecoder(checks, n_qubits=5)
corrections = gpu.batch_decode(syndromes)
Stim workflow:
import stim
from qector_decoder_v3 import BlossomDecoder
from qector_decoder_v3.stim_compat import stim_circuit_to_check_matrix
circuit = stim.Circuit.generated(
"surface_code:rotated_memory_z",
distance=5,
rounds=5,
after_clifford_depolarization=0.005,
)
checks, n_qubits = stim_circuit_to_check_matrix(circuit)
decoder = BlossomDecoder(checks, n_qubits)
Included decoder families
| Module | Primary use | Status |
|---|---|---|
UnionFindDecoder |
Fast approximate decoding | Stable public API |
FastUnionFindDecoder |
Optimized Union-Find path | Stable public API |
BlossomDecoder |
Exact MWPM / PyMatching-parity validation | Stable public API |
SparseBlossomDecoder |
Faster near-optimal matching | Experimental |
BeliefMatching |
Correlated-noise accuracy experiments | Research/accuracy mode |
BpOsdDecoder |
LDPC and qLDPC workflows | Experimental |
BatchDecoder / CPUBatchDecoder |
CPU Monte Carlo sweeps | Stable public API |
CUDABatchDecoder |
CUDA batch decoding | Runtime/build dependent |
OpenCLBatchDecoder |
OpenCL batch decoding | Runtime/build dependent |
stim_compat |
Stim circuit and DEM conversion | Stable utility |
sinter_compat |
Sinter custom decoder integration | Stable utility |
rest_api |
Local decoding service | Local/partner review only |
Evidence-backed positioning
QECTOR Decoder v3 is positioned as a source-available QEC R&D platform, not as a blanket replacement for every mature decoder in every workload.
The repository includes public benchmark artifacts and reproduction scripts for:
- PyMatching-parity logical-error-rate checks on selected surface-code workloads
- belief-matching accuracy experiments on selected workloads
- GPU bit-identity checks against CPU output on a tested NVIDIA machine
- native memory profiling for selected decoder paths
Important boundaries:
- PyMatching remains faster for standard MWPM latency in the checked-in comparison artifacts.
- Belief-matching is an accuracy/research mode and is much slower in the provided experiments.
- GPU availability and performance depend on wheel build features, drivers, hardware, and runtime checks.
- OpenCL support must be confirmed on the target machine or built under the appropriate licensed/custom configuration.
- REST/API surfaces are for local experiments or controlled review unless separately hardened.
Full methodology, reproducibility notes, and benchmark artifacts are in the GitHub repository:
https://github.com/GuillaumeLessard/qector-decoder
GPU availability check
from qector_decoder_v3 import CUDABatchDecoder, OpenCLBatchDecoder
print("CUDA:", CUDABatchDecoder.is_available())
print("OpenCL:", OpenCLBatchDecoder.is_available())
Do this before making any hardware-specific performance claim.
Licensing
QECTOR Decoder v3 is source-available.
Personal, academic, educational and non-commercial research use is allowed under the repository license. Company use, funded institutional work, SaaS, hosted API deployment, OEM integration, redistribution, paid consulting, or commercial benchmarking requires a commercial license.
Website and commercial licensing:
Contact:
Citation
@software{lessard2026qector,
author = {Guillaume Lessard},
title = {{QECTOR Decoder v3}: Rust/Python Quantum Error Correction Decoding Platform},
year = {2026},
version = {0.5.0},
url = {https://www.qector.store},
note = {Source-available. Commercial license required for commercial use.}
}
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