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Dynamic programming and viscosity solutions for the optimal control of quantum spin systems
Authors:Srinivas Sridharan  Matthew R. James
Affiliation:
  • a Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Drive #0411, La Jolla, CA 92093-0411, USA
  • b Centre for Quantum Computation and Communication Technology, Research School of Engineering, Australian National University, Canberra, ACT 0200, Australia
  • Abstract:The purpose of this paper is to describe the application of the notion of viscosity solutions to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with an important class of optimal control problems for quantum spin systems. The HJB equation that arises in the control problems of interest is a first-order nonlinear partial differential equation defined on a Lie group. Hence we employ recent extensions of the theory of viscosity solutions to Riemannian manifolds in order to interpret possibly non-differentiable solutions to this equation. Results from differential topology on the triangulation of manifolds are then used develop a finite difference approximation method for numerically computing the solution to such problems. The convergence of these approximations is proven using viscosity solution methods. In order to illustrate the techniques developed, these methods are applied to an example problem.
    Keywords:Optimal control   Quantum spin systems   Dynamic programming   Numerical method   Viscosity solution
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