Reduction-based strategy for optimal control of Bose-Einstein condensates
Document Type
Article
Publication Date
2-1-2022
Abstract
Applications of Bose-Einstein condensates (BEC) often require that the condensate be prepared in a specific complex state. Optimal control is a reliable framework to prepare such a state while avoiding undesirable excitations, and, when applied to the time-dependent Gross-Pitaevskii equation (GPE) model of BEC in multiple space dimensions, results in a large computational problem. We propose a control method based on first reducing the problem, using a Galerkin expansion, from a partial differential equation to a low-dimensional Hamiltonian ordinary differential equation system. We then apply a two-stage hybrid control strategy. At the first stage, we approximate the control using a second Galerkin-like method known as the chopped random basis to derive a finite-dimensional nonlinear programing problem, which we solve with a differential evolution algorithm. This search method then yields a candidate local minimum which we further refine using a variant of gradient descent. This hybrid strategy allows us to greatly reduce excitations both in the reduced model and the full GPE system.
Identifier
85125593164 (Scopus)
Publication Title
Physical Review E
External Full Text Location
https://doi.org/10.1103/PhysRevE.105.025311
e-ISSN
24700053
ISSN
24700045
PubMed ID
35291192
Issue
2
Volume
105
Recommended Citation
Adriazola, J. and Goodman, R. H., "Reduction-based strategy for optimal control of Bose-Einstein condensates" (2022). Faculty Publications. 3123.
https://digitalcommons.njit.edu/fac_pubs/3123