info:eu-repo/semantics/article
Exploiting landscape geometry to enhance quantum optimal control
Fecha
2020-02Registro en:
Larocca, Martin; Calzetta, Esteban Adolfo; Wisniacki, Diego Ariel; Exploiting landscape geometry to enhance quantum optimal control; American Physical Society; Physical Review A; 101; 2; 2-2020; 1-7
2469-9926
2469-9934
CONICET Digital
CONICET
Autor
Larocca, Martin
Calzetta, Esteban Adolfo
Wisniacki, Diego Ariel
Resumen
The successful application of quantum optimal control (QOC) over the past decades has unlocked the possibility of directing the dynamics of quantum systems. Nevertheless, solutions obtained from QOC algorithms are usually highly irregular, making them unsuitable for direct experimental implementation. In this paper, we propose a method to reshape those unattractive optimal controls. The approach is based on the fact that solutions to QOC problems are not isolated policies but constitute multidimensional submanifolds of control space. This was originally shown for finite-dimensional systems. Here, we analytically prove that this property is still valid in a continuous variable system. The degenerate subspace can be effectively traversed by moving in the null subspace of the Hessian of the cost function, allowing for the pursuit of secondary objectives. To demonstrate the usefulness of this procedure, we apply the method to smooth and compress optimal protocols in order to meet laboratory demands.