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The Journal of Chemical Physics

Rapidly convergent iteration methods for quantum optimal control of population

Wusheng Zhu, Jair Botina, HERSCHEL A. RABITZ

Published Feb 1, 1998• 437 citations
Publisher

Abstract

A family of new iteration methods is presented for designing quantum optimal controls to manipulate the transition probability. Theoretical analysis shows that these new methods exhibit quadratic and monotonic convergence. Numerical calculations verify that for these new methods, within very few steps, the optimized objective functional comes close to its convergent limit.

DOI
10.1063/1.475576

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A family of new iteration methods is presented for designing quantum optimal controls to manipulate the transition probability. Theoretical analysis shows that these new methods exhibit quadratic and monotonic convergence. Numerical calculations verify that for these new methods, within very few steps, the optimized objective functional comes close to its convergent limit.
A uniform iteration method is presented for achieving quantum optimal control over any real objective with a positive semidefinite Hessian matrix. Theoretical analysis shows that this uniform algorithm exhibits quadratic and monotonic convergence. Numerical calculations verify that for this uniform algorithm, within a few steps, the optimized objective functional comes close to its converged limit. For some optimal control purposes, the objective itself is not required to be directly a physical observable, but it is only necessary that the objective have a suitable association with some desired physical observables. As an illustration of the algorithm, the control objective is chosen to achieve maximum population in a target state as well as minimum phase mismatch with the target state.
The control of quantum dynamics is often concerned with finding time-dependent optimal control fields that can take a system from an initial state to a final state to attain the desired value of an observable. This paper presents a general method for formulating monotonically convergent algorithms to iteratively improve control fields. The formulation is based on a two-point boundary-value quantum control paradigm (TBQCP) expressed as a nonlinear integral equation of the first kind arising from dynamical invariant tracking control. TBQCP is shown to be related to various existing techniques, including local control theory, the Krotov method, and optimal control theory. Several accelerated monotonic convergence schemes for iteratively computing control fields are derived based on TBQCP. Numerical simulations are compared with the Krotov method showing that the new TBQCP schemes are efficient and remain monotonically convergent over a wide range of the iteration step parameters and the control pulse lengths, which is attributable to the trap-free character of the transition probability quantum dynamics control landscape.
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According to the specialty of quantum systems, the reliability or the efficiency of a general optimal control scheme leave much to be desired. In this paper, we develop a special improved quantum optimal control method for using dynamic control field, which can be implemented as fast convergent algorithms. The relations among, convergence speed and iteration step parameters are analyzed in detail through a three-level ¦® system simulation experiments. Theoretical analysis show that this new algorithm exhibits significantly superior to the classical quantum optimal control method and the Krotov method in reliability and convergence rate.
We present a monotonic convergent quantum optimal control method that can be utilized to optimize the control field while exactly enforcing multiple equality constraints for steering quantum systems from an initial state towards desired quantum states. For illustration, special consideration is given to finding optimal control fields with (i) exact zero area and (ii) exact zero area along with constant pulse fluence. The method combined with these two types of constraints is successfully employed to maximize the state-to-state transition probability in a model vibrating diatomic molecule.