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Cybernetics and Physics

A numerical approach for the stochastic control of a two-level quantum system

Cutberto Romero-Meléndez, Leopoldo González-Santos, David Castillo-Fernández

Published Sep 30, 2020• 2 citations
Publisher

Abstract

The aim of this paper is to study the problem of controlling the stochastic evolution of a two-level quantum system in the presence of two randomly fluctuating electromagnetic fields, given by a Wiener process. The system is modeled by the stochastic Schr¨odinger equation dependent on time. We set up the quantum optimal control problem by choosing a cost functional type Bolza. By applying the Pontryagin Maximum Stochastic Principle to an extended Hamiltonian, we express the stochastic optimal controls in terms of the co-state of the system. To solve numerically the resulting stochastic differential equations we propose an iterative algorithm using the Euler-Maruyama method. Finally, we obtain the optimal trajectories on the Bloch sphere.

DOI
10.35470/2226-4116-2020-9-2-107-116

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The aim of this paper is to study the problem of controlling the stochastic evolution of a two-level quantum system in the presence of two randomly fluctuating electromagnetic fields, given by a Wiener process. The system is modeled by the stochastic Schr¨odinger equation dependent on time. We set up the quantum optimal control problem by choosing a cost functional type Bolza. By applying the Pontryagin Maximum Stochastic Principle to an extended Hamiltonian, we express the stochastic optimal controls in terms of the co-state of the system. To solve numerically the resulting stochastic differential equations we propose an iterative algorithm using the Euler-Maruyama method. Finally, we obtain the optimal trajectories on the Bloch sphere.
In this paper, we discuss a quantum control algorithm, devised by the authors, inspired in Rabitz and Krotov algorithms and applied to Nuclear Magnetic Resonance (NMR) That algorithm is based on a numerical method for iterative optimization.Specifically, we address the determination of external optimal pulses (controls) to minimal cost, over a two-level quantum system.We use the numerical approximation to find the optimal controls in the case of two external electromagnetic fields, integrating the associated equations of the Pontryagin Maximum Principle.That algorithm unifies and generalizes the Rabitz and Krotov algorithms.We compare the efficiency of these algorithms with the solutions found by analytical methods.
We study the time-optimal robust control of a two-level quantum system subjected to field inhomogeneities. We apply the Pontryagin maximum principle and we introduce a reduced space onto which the optimal dynamics is projected down. This reduction leads to a complete analytical derivation of the optimal solution in terms of elliptic functions and elliptic integrals. Necessary optimality conditions are then obtained for the original system. These conditions are verified numerically and lead to the optimal control protocol. Various examples, ranging from state-to-state transfer to the generation of a NOT gate, illustrate this study. The connection with other geometric optimization approaches that have been used to solve this problem is also discussed. Finally, we show how this method can be combined with numerical optimization algorithms to design robust control for higher-dimensional quantum systems, as illustrated by a Bose-Einstein condensate in an optical lattice.
In this paper we consider the minimum time population transfer problem for a two level quantum system driven by two external fields with bounded amplitude. After projection on the so-called Bloch sphere, we tackle the problem with well-developed techniques of optimal synthesis on 2-D manifolds. Based on the Pontryagin Maximum Principle, we characterize a restricted set of candidate optimal trajectories. Properties on this set, crucial for a complete optimal synthesis, are illustrated by numerical simulations.
A stochastic procedure is developed which allows one to express Pontryagin's maximum principle for a dissipative quantum system solely in terms of stochastic wave functions. Time-optimal controls can be efficiently computed without computing the density matrix. Specifically, the proper dynamical update rules are presented for the stochastic costate variables introduced by Pontryagin's maximum principle, and restrictions on the form of the terminal cost function are discussed. The proposed procedure is confirmed by comparing the results to those obtained from optimal control on Lindbladian dynamics. Numerically, the proposed formalism becomes time and memory efficient for large systems, and it can be generalized to describe non-Markovian dynamics.
In this paper, the Pontryagin-type maximum principle for optimal control of quantum stochastic systems in fermion fields is obtained. These systems have gained significant prominence in numerous quantum applications ranging from physical chemistry to multi-dimensional nuclear magnetic resonance experiments. Furthermore, we establish the existence and uniqueness of solutions to backward quantum stochastic differential equations driven by fermion Brownian motion. The application of noncommutative martingale inequalities and the martingale representation theorem enables this achievement.
The control of a two-level open quantum system subject to dissipation due to environment interaction is considered. The evolution of this system is governed by a Lindblad master equation which is augmented by a stochastic term to model the effect of time-continuous measurements. In order to control this stochastic master equation model, a Fokker–Planck control framework is investigated. Within this strategy, the control objectives are defined based on the probability density functions of the two-level stochastic process and the controls are computed as minimizers of these objectives subject to the constraints represented by the Fokker–Planck equation. This minimization problem is characterized by an optimality system including the Fokker–Planck equation and its adjoint. This optimality system is approximated by a second-order accurate, stable, conservative and positive-preserving discretization scheme. The implementation of the resulting open-loop controls is realized with a receding-horizon algorithm over a sequence of time windows. Results of numerical experiments demonstrate the effectiveness of the proposed approach.