JOPT fails for state transfer problems in open systems

[pmenczel]

The following script sets up a simple example problem where a (dissipative) qubit should be transferred from the ground state to the excited state. Using JOPT, the optimize_pulses function raises a ValueError. (Note that the same example works fine with GOAT.)

import numpy as np
import qutip as qt
from qutip_qoc import Objective, optimize_pulses

from jax import jit, numpy

# --- Setup problem ---
Hd = qt.Qobj(np.diag([1, 2]))
c_ops = [np.sqrt(0.1) * qt.sigmam()]
Hc = qt.sigmax()

Ld = qt.liouvillian(H=Hd, c_ops=c_ops)
Lc = qt.liouvillian(Hc)

initial_state = qt.fock_dm(2, 0)
target_state = qt.fock_dm(2, 1)

times = np.linspace(0, 2 * np.pi, 250)

# --- Run JOPT ---
@jit
def sin_x(t, c, **kwargs):
    return c[0] * numpy.sin(c[1] * t)
L = [Ld, [Lc, sin_x]]

guess_params = [1, 0.5]

res_jopt = optimize_pulses(
    objectives = Objective(initial_state, L, target_state),
    control_parameters = {
        "ctrl_x": {"guess": guess_params, "bounds": [(-1, 1), (0, 2 * np.pi)]}
    },
    tlist = times,
    algorithm_kwargs = {
        "alg": "JOPT",
        "fid_err_targ": 0.001,
    },
)

The error message is as follows:

Traceback (most recent call last):
  File "/home/paulm/qutip/qutip-qoc/tmp/bug2.py", line 28, in <module>
    res_jopt = optimize_pulses(
        objectives = Objective(initial_state, L, target_state),
    ...<7 lines>...
        },
    )
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip_qoc/pulse_optim.py", line 422, in optimize_pulses
    return _global_local_optimization(
        objectives,
    ...<7 lines>...
        qtrl_optimizers,
    )
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip_qoc/_optimizer.py", line 359, in _global_local_optimization
    min_res = optimizer(
        func=multi_objective.goal_fun,
    ...<6 lines>...
        **optimizer_kwargs,
    )
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/_lib/_util.py", line 440, in wrapper
    return fun(*args, **kwargs)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_basinhopping.py", line 696, in basinhopping
    bh = BasinHoppingRunner(x0, wrapped_minimizer, take_step_wrapped,
                            accept_tests, disp=disp)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_basinhopping.py", line 78, in __init__
    minres = minimizer(self.x)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_basinhopping.py", line 294, in __call__
    return self.minimizer(self.func, x0, **self.kwargs)
           ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_minimize.py", line 738, in minimize
    res = _minimize_lbfgsb(fun, x0, args, jac, bounds,
                           callback=callback, **options)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_lbfgsb_py.py", line 386, in _minimize_lbfgsb
    sf = _prepare_scalar_function(fun, x0, jac=jac, args=args, epsilon=eps,
                                  bounds=bounds,
                                  finite_diff_rel_step=finite_diff_rel_step)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_optimize.py", line 291, in _prepare_scalar_function
    sf = ScalarFunction(fun, x0, args, grad, hess,
                        finite_diff_rel_step, bounds, epsilon=epsilon)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_differentiable_functions.py", line 223, in __init__
    self._update_fun()
    ~~~~~~~~~~~~~~~~^^
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_differentiable_functions.py", line 295, in _update_fun
    fx = self._wrapped_fun(self.x)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/scipy/optimize/_differentiable_functions.py", line 21, in wrapped
    fx = fun(np.copy(x), *args)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip_qoc/objective.py", line 143, in goal_fun
    infid += self._weights[i] * alg.infidelity(params)
                                ~~~~~~~~~~~~~~^^^^^^^^
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip_qoc/_jopt.py", line 153, in _infid
    diff_dag = Qobj(diff.data.adjoint(), dims=diff.dims)
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip/core/qobj.py", line 279, in __init__
    self._initialize_data(arg, dims, copy)
    ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
  File "/home/paulm/miniconda3/envs/qutip-master-qoc/lib/python3.13/site-packages/qutip/core/qobj.py", line 265, in _initialize_data
    raise ValueError('Provided dimensions do not match the data: ' +
                     f"{self._dims.shape} vs {self._data.shape}")
ValueError: Provided dimensions do not match the data: (4, 1) vs (1, 4)

This issue was discovered while creating the interactive test notebooks in #44