classiq 0.1.13

Classiq SDK Package

The Classiq Quantum Algorithm Design platform helps teams build sophisticated quantum circuits that could not be designed otherwise

We do this by synthesizing high-level functional models into optimized quantum circuits, taking into account the constraints that are important to the designer. Furthermore, we are able to generate circuits for practically any universal gate-based quantum computer and are compatible with most quantum cloud providers.

Requirements

Python 3.8+

Installation

pip install --upgrade pip
$ pip install 'classiq[all]'

Example

from classiq import generator
from classiq_interface.generator.state_preparation import (
    StatePreparation,
    PMF,
    StatePreparationOutputs,
    Metrics,
    NonNegativeFloatRange,
)
from classiq_interface.generator.qft import QftInputs, QFT

probabilities = (0.5, 0.1, 0.2, 0.005, 0.015, 0.12, 0.035, 0.025)
pmf = PMF(pmf=probabilities)
sp_params = StatePreparation(
    probabilities=pmf,
    num_qubits=4,
    error_metric={Metrics.KL: NonNegativeFloatRange(upper_bound=0.3)},
)

circuit_generator = generator.Generator(qubit_count=20, max_depth=100)
output_dict = circuit_generator.StatePreparation(params=sp_params)

state_preparation_output = output_dict[StatePreparationOutputs.OUT]

qft_params = QFT(num_qubits=3)
circuit_generator.QFT(
    params=qft_params, in_wires={QftInputs.IN: state_preparation_output}
)

circuit = circuit_generator.generate()
circuit.show()

License

See license.