Abstract
Optimal control theory provides a general, means for designing controls to manipulate quantum phenomena. Traditional implementation requires solving coupled nonlinear equations to obtain the optimal control solution, whereas this work introduces a combinatorial quantum control (CQC) algorithm to avoid this complexity. The CQC technique uses a predetermined toolkit of small time step propagators in conjunction with combinatorial optimization to identify a proper sequence for the toolkit members. Results indicate that the CQC technique exhibits invariance of search effort to the number of system states and very favorable scaling upon comparison to a standard gradient algorithm, taking into consideration that CQC is easily parallelizable.
Original language | English (US) |
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Pages (from-to) | 151-153 |
Number of pages | 3 |
Journal | Journal of Computational Chemistry |
Volume | 31 |
Issue number | 1 |
DOIs | |
State | Published - Jan 15 2010 |
All Science Journal Classification (ASJC) codes
- General Chemistry
- Computational Mathematics
Keywords
- Combinatorial optimization
- Genetic algorithm
- Propagator toolkit
- Quantum control
- Schrödinger equation