Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2305.17630 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917561719848960 |
|---|---|
| author | Shao, Jieqiu Naris, Mantas Hauser, John Nicotra, Marco M. |
| author_facet | Shao, Jieqiu Naris, Mantas Hauser, John Nicotra, Marco M. |
| contents | The Quantum Projection Operator-Based NewtonMethod for Trajectory Optimization (Q-PRONTO) is a numerical method for solving quantum optimal control problems. This paper significantly improves prior versions of the quantum projection operator by introducing a regulator that stabilizes the solution estimate at every iteration. This modification is shown to not only improve the convergence rate of the algorithm, but also steer the solver towards better local minima compared to the unregulated case. Numerical examples showcase how Q-PRONTO can be used to solve multi-input quantum optimal control problems featuring time-varying costs and undesirable populations that ought to be avoided during the transient. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_17630 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Solving quantum optimal control problems using projection-operator-based Newton steps Shao, Jieqiu Naris, Mantas Hauser, John Nicotra, Marco M. Quantum Physics Systems and Control The Quantum Projection Operator-Based NewtonMethod for Trajectory Optimization (Q-PRONTO) is a numerical method for solving quantum optimal control problems. This paper significantly improves prior versions of the quantum projection operator by introducing a regulator that stabilizes the solution estimate at every iteration. This modification is shown to not only improve the convergence rate of the algorithm, but also steer the solver towards better local minima compared to the unregulated case. Numerical examples showcase how Q-PRONTO can be used to solve multi-input quantum optimal control problems featuring time-varying costs and undesirable populations that ought to be avoided during the transient. |
| title | Solving quantum optimal control problems using projection-operator-based Newton steps |
| topic | Quantum Physics Systems and Control |
| url | https://arxiv.org/abs/2305.17630 |