qutip_qoc.objective module

This module contains the Objective class for storing information about an optimization objective, and the _MultiObjective class for optimizing multiple objectives simultaneously.

class qutip_qoc.objective.Objective(initial, H, target, weight=1)

Bases: object

A class for storing information about an optimization objective.

Examples

To specify an objective for GOAT, provide a gradient function:

initial = qt.basis(2, 0)
target  = qt.basis(2, 1)

sin = lambda t, p: np.sin(p * t)

def d_sin(t, p, idx):
    if idx==0: return t * np.cos(t) # w.r.t. p
    if idx==1: return p * np.cos(t) # w.r.t. t

H = [qt.sigmax(), [qt.sigmay(), sin, {'grad': d_sin}]]

obj = Objective(initial, H, target)

To specify an objective for JOPT, no need for gradient function:

initial = qt.basis(2, 0)
target  = qt.basis(2, 1)

@jax.jit
def sin(t, p)
    return jax.numpy.sin(p * t)

def d_sin(t, p, idx):
    if idx==0: return t * np.cos(t) # w.r.t. p
    if idx==1: return p * np.cos(t) # w.r.t. t

H = [qt.sigmax(), [qt.sigmay(), sin]]

obj = Objective(initial, H, target)

Attributes:

initialqutip.Qobj

The initial state or operator to be transformed.

Hcallable, list

A specification of the time-depedent quantum object. Usually a list with drift Hamiltonian at zero-index followed by the control Hamiltonians. See qutip.QobjEvo for details and examples.

targetqutip.Qobj

The target state or operator.

weightfloat

Only used in multi-objective scenarios. The weight of this objective in the optimization. All weights are normalized to sum to 1.