ilp-decoder 0.1.0

An implementation of ILP decoders for quantum error correction.

ILP Decoder

An implementation of the ILP decoder for circuit-level noise.

Included is a ilp_decoder.ILPDecoder class that is configured using a stim.DetectorErrorModel and decodes shot data, directly outputting predicted observables (without sinter), as well as a ilp_decoder.ILPSinterDecoder class, which subclasses sinter.Decoder, for interfacing with sinter.

Installation

To install from pypi, run:

pip install ilp_decoder

To install from source, run:

pip install -e .

from the root directory.

Usage

Here is an example of how the decoder can be used directly with Stim:

import stim
import numpy as np
from ilp_decoder import ILPDecoder

num_shots = 100
d = 3
p = 0.001
circuit = stim.Circuit.generated(
    "surface_code:rotated_memory_x",
    rounds=d,
    distance=d,
    before_round_data_depolarization=p,
    before_measure_flip_probability=p,
    after_reset_flip_probability=p,
    after_clifford_depolarization=p
)

sampler = circuit.compile_detector_sampler()
shots, observables = sampler.sample(num_shots, separate_observables=True)

decoder = ILPDecoder(circuit)

predicted_observables = decoder.decode_batch(shots)
num_mistakes = np.sum(np.any(predicted_observables != observables, axis=1))

print(f"{num_mistakes}/{num_shots}")

Sinter integration

To integrate with sinter, you can use the ilp_decoder.ILPSinterDecoder class, which inherits from sinter.Decoder. To use it, you can use the custom_decoders argument when using sinter.collect:

import sinter
from ilp_decoder import ILPSinterDecoder, sinter_decoders

samples = sinter.collect(
    num_workers=4,
    max_shots=1_000_000,
    max_errors=1000,
    tasks=generate_example_tasks(),
    decoders=['ilp'],
    custom_decoders=sinter_decoders()
    print_progress=True,
)

Advanced ILP solvers

You can use whatever ILP solver supported by cvxpy instead of the default one highs, though highs should be one of the fastest open-source solver available. If you have access to gurobi, you may gain some extra speed boost (not tested).