qreservoir 0.3.0

Python package for quantum reservoir computing using Qulacs

Qreservoir

Qreservoir is a lightweight python package built on top of qulacs to simulate quantum extreme learning and quantum reservoir computing models.

Qreservoir is licensed under the MIT license.

Quick Install for Python

pip install qreservoir

Uninstall Qreservoir:

pip uninstall qreservoir

Features

Fast simulation of quantum extreme learning machine and quantum reservoir computing.

Tutorial and API documents

See the following documents for tutorials.

Python sample code

from qreservoir.models.QELModel import QELModel
from qreservoir.reservoirs.HarrRandomReservoir import HarrRandomReservoir
from qreservoir.encoders.HEEncoder import HEEncoder
from qulacs import Observable
from sklearn.linear_model import LinearRegression
import numpy as np

# Define observable list
observable = Observable(2)
observable.add_operator(1.0, "Z 0")
observables = [observable]

# Define model
encoder = HEEncoder(2, 2)
reservoir = HarrRandomReservoir(encoder, 0)
subestimator = LinearRegression()
model = QELModel(reservoir, observables, subestimator)

# Training data
X = np.zeros((10, 2))
y = np.zeros(10)

# Train
model.fit(X, y)

# Predict
X_test = np.zeros((30, 2))
out = model.predict(X_test)

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