Digital Propagation

The DigitalPropagation functional propagates a digital quantum circuit through the backend. Because it subclasses PrimitiveFunctional, any symbolic parameters exposed by the underlying Circuit can be queried or updated through helper methods such as get_parameter_names().

Measurement details such as the number of shots are specified separately via readout objects passed to execute().

Parameters

• circuit (Circuit): Circuit to be propagated.

Returns

• FunctionalResult: Access shot counts

• via get_samples() and

• probabilities via get_probabilities().

Usage Example

import numpy as np
from qilisdk.digital import Circuit, H, RX, CNOT
from qilisdk.functionals import DigitalPropagation

# Create a 2-qubit circuit
circuit = Circuit(2)
circuit.add(H(0))
circuit.add(RX(0, theta=np.pi))
circuit.add(CNOT(0, 1))

# Initialize the DigitalPropagation functional
digital_propagation = DigitalPropagation(circuit)

This functional can be executed on any backend that supports digital circuits. For example, we can execute it on the CUDA backend:

from qilisdk.backends import CudaBackend
from qilisdk.readout import Readout

# Run on CUDA backend and retrieve counts
backend = CudaBackend()
results = backend.execute(digital_propagation, Readout().with_sampling(nshots=100))
print(results)

Output

- Functional Results: [

Sampling Results: (
    nshots=100,
    samples={'00': 53, '11': 47}
)

]