Qutip Backend

The Qutip backend uses the QuTiP library for CPU-only simulation. It is the most lightweight optional backend — no GPU, no compiled extension — and is well suited to local development, CI pipelines and educational notebooks.

Installation

pip install qilisdk[qutip]

Quick start

import numpy as np
from qilisdk.analog import Schedule, X, Z, Y
from qilisdk.core import ket, tensor_prod
from qilisdk.backends import QutipBackend
from qilisdk.core.interpolator import Interpolation
from qilisdk.functionals import AnalogEvolution
from qilisdk.readout import Readout

T = 10.0
dt = 0.5
nqubits = 1

Hx = sum(X(i) for i in range(nqubits))
Hz = sum(Z(i) for i in range(nqubits))

schedule = Schedule(
    hamiltonians={"driver": Hx, "problem": Hz},
    coefficients={
        "driver": {(0.0, T): lambda t: 1 - t / T},
        "problem": {(0.0, T): lambda t: t / T},
    },
    dt=dt,
    interpolation=Interpolation.LINEAR,
)

initial_state = tensor_prod([(ket(0) - ket(1)).unit() for _ in range(nqubits)]).unit()

backend = QutipBackend()
results = backend.execute(
    AnalogEvolution(schedule=schedule, initial_state=initial_state),
    Readout().with_expectation(observables=[Z(0), X(0), Y(0)]).with_state_tomography(),
)
print(results)

Functional support

Functional

Support

Notes

DigitalPropagation

Statevector simulation via qutip_qip’s CircuitSimulator. Mid-circuit measurements raise ValueError; all measurements must be at the end of the circuit.

AnalogEvolution

Master-equation integration via QuTiP’s qutip.mesolve(). nsteps (default 10_000) caps the internal ODE substeps.

QuantumReservoir

🟡

The QutipBackend does not natively implement Backend._execute_quantum_reservoir. Circuit steps in the reservoir layer fall back to dense QTensor unitary multiplication on CPU; Schedule steps still use QuTiP’s mesolve().

VariationalProgram

Reuses the digital/analog handlers above for each optimization step.

Configuration

QutipBackend has a single constructor option:

Option

Meaning

nsteps

Upper bound on the number of internal ODE substeps used by qutip.mesolve() per schedule interval. Increase it if a long or stiff schedule causes the QuTiP solver to fail with a “max steps exceeded” warning. Defaults to 10_000.

from qilisdk.backends import QutipBackend

backend = QutipBackend(nsteps=50_000)

Note

QutipBackend does not accept a NoiseModel. For noisy digital or analog simulations use QiliSim or CudaBackend instead.