Navigating on Quantum Control Solution Subspaces
arXiv:2001.05941 · doi:10.1103/PhysRevA.102.033108
Abstract
Quantum Optimal Control (QOC) is the field devoted to the production of external control protocols that actively guide quantum dynamics. Solutions to QOC problems were shown to constitute continuous submanifolds of control space. A solution navigation method exploiting this property to achieve secondary features in the control protocols was proposed [Larocca \textit{et al}, arXiv:1911.07105]. Originally, the technique involved the computation of the exact Hessian matrix. In this paper, we show that the navigation can be alternatively performed with a finite-difference approximation scheme, thus enabling the application of this procedure in systems where computing the exact Hessian is out of reach.
7 pages, 9 figures
References in corpus (20)
- Quantum Simulation
- Probing many-body dynamics on a 51-atom quantum simulator
- Quantum Communication
- Control of quantum phenomena: Past, present, and future
- Training Schrödinger's cat: quantum optimal control
- The European Quantum Technologies Roadmap
- Single ion heat engine with maximum efficiency at maximum power
- Digitized adiabatic quantum computing with a superconducting circuit
- Chopped random-basis quantum optimization
- The quantum harmonic Otto cycle
- Comparing, Optimising and Benchmarking Quantum Control Algorithms in a Unifying Programming Framework
- Driving at the quantum speed limit: Optimal control of a two-level system
- Gradient optimization of analytic controls: the route to high accuracy quantum optimal control
- Introduction to Quantum Optimal Control for Quantum Sensing with Nitrogen-Vacancy Centers in Diamond
- Frictionless atom cooling in harmonic traps: a time-optimal approach
- Exploring constrained quantum control landscapes
- Auxiliary matrix formalism for interaction representation transformations, optimal control and spin relaxation theories
- Quantum Optimal Control: Landscape Structure and Topology
- Exploring the top and bottom of the quantum control landscape
- Exploiting Landscape Geometry to Enhance Quantum Optimal Control