| Full text | |
| Author(s): |
Fernandes, Marllos E. F.
;
Fanchini, Felipe F.
;
de Lima, Emanuel F.
;
Castelano, Leonardo K.
Total Authors: 4
|
| Document type: | Journal article |
| Source: | Journal of Physics A-Mathematical and Theoretical; v. 56, n. 49, p. 14-pg., 2023-12-08. |
| Abstract | |
We apply the Krotov method (KM) for open and closed quantum systems to find optimized controls to manipulate qubit/qutrit systems in the presence of the external environment. In the case of unitary optimization, the KM 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 KM already takes into account the noise during the optimization process. We consider two distinct computational tasks: 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 correspond 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. (AU) | |
| FAPESP's process: | 23/04987-6 - Quantum optimization and machine learning: variational algorithms and applications |
| Grantee: | Felipe Fernandes Fanchini |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 19/09624-3 - Optimal quantum control and quantum information in semiconductor nanostructures |
| Grantee: | Leonardo Kleber Castelano |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 14/23648-9 - Quantum control of ultracold matter |
| Grantee: | Emanuel Fernandes de Lima |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 21/04655-8 - Machine learning and its applications in quantum physics: metrology, thermology, phase transitions and dynamical decoupling |
| Grantee: | Felipe Fernandes Fanchini |
| Support Opportunities: | Regular Research Grants |