Effectiveness of the Krotov method in controlling open quantum systems

TL;DR

This paper evaluates the Krotov method for optimizing control in open quantum systems, demonstrating its effectiveness in state preparation and gate implementation under environmental noise, with specific advantages in non-unitary optimization.

Contribution

It compares unitary and non-unitary Krotov optimization approaches for open quantum systems, highlighting conditions where non-unitary optimization outperforms unitary methods.

Findings

Non-unitary optimization outperforms unitary in state preparation.

Unitary optimization can be as effective as non-unitary in certain gate tasks.

Effectiveness depends on leakage states and dissipation distribution.

Abstract

We apply the Krotov method for open and closed quantum systems with the objective of finding optimized controls to manipulate qubit/qutrit systems in the presence of the external environment. In the case of unitary optimization, the Krotov method is first applied to a quantum system neglecting its interaction with the environment. The resulting controls from the unitary optimization are then used to drive the system along with the environmental noise. In the case of non-unitary optimization, the Krotov method already takes into account the noise during the optimization process. We consider two distinct computational task: target-state preparation and quantum gate implementation. These tasks are carried out in simple qubit/qutrit systems and also in systems presenting leakage states. For the state-preparation cases, the controls from the non-unitary optimization outperform the controls from the unitary optimization. However, as we show here, this is not always true for the implementation of quantum gates. There are some situations where the unitary optimization performs equally well compared to the non-unitary optimization. We verify that these situations corresponds to either the absence of leakage states or to the effects of dissipation being spread uniformly over the system, including non-computational levels. For such cases, the quantum gate implementation must cover the entire Hilbert space and there is no way to dodge dissipation. On the other hand, if the subspace containing the computational levels and its complement are differently affected by dissipation, the non-unitary optimization becomes effective.