Efficient optimization of state preparation in quantum networks using quantum trajectories
arXiv:1801.04382 · doi:10.1088/2058-9565/aace16
Abstract
The wave-function Monte-Carlo method, also referred to as the use of "quantum-jump trajectories", allows efficient simulation of open systems by independently tracking the evolution of many pure-state "trajectories". This method is ideally suited to simulation by modern, highly parallel computers. Here we show that Krotov's method of numerical optimal control, unlike others, can be modified in a simple way, so that it becomes fully parallel in the pure states without losing its effectiveness. This provides a highly efficient method for finding optimal control protocols for open quantum systems and networks. We apply this method to the problem of generating entangled states in a network consisting of systems coupled in a unidirectional chain. We show that due to the existence of a dark-state subspace in the network, nearly-optimal control protocols can be found for this problem by using only a single pure-state trajectory in the optimization, further increasing the efficiency.
17 pages, 4 figures
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- Gradient-based optimal control of open quantum systems using quantum trajectories and automatic differentiation
- Efficient exploration of Hamiltonian parameter space for optimal control of non-Markovian open quantum systems
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