A fully efficient time-parallelized quantum optimal control algorithm
This work addresses the computational bottleneck of quantum optimal control for researchers, enabling faster simulations across multiple domains.
The authors present a time-parallelized quantum optimal control algorithm that achieves near-linear speedup with the number of processors, reducing computational time proportionally. Demonstrated on spin systems, molecular orientation, and Bose-Einstein condensates.
We present a time-parallelization method that enables to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of application of this numerical scheme.