Control of Quantum Dynamics Using External Fields Designed by Optimal Control Theory, Learning Algorithms, and Inverse Control.

哲郎 伊丹

Jie‐Ru Hu, Zuo-Yuan Zhang, Jin‐Ming Liu +1 more

Quantum algorithms can afford greater computational efficiency compared to their classical counterparts when addressing specific computing tasks. We describe here the implementation, using a polar molecule in an external electric field, of the single-qudit cyclic permutation identification algorithm proposed by Gedik et al. [ Sci. Rep. 5 , 14671 ( 2015 ). 10.1038/srep10995 ]. A molecular ququart is realized through the field-dressed states generated as the pendular modes of BaI. By employing multi-target optimal control theory, we design microwave pulses for ququart-based operations such as the Fourier transformation and its inverse, as well as the oracle U f operation. Specifically, we design an optimized pulse sequence that realizes a quantum algorithm on a single BaI molecule identifying the parity of a member of a set of cyclic permutations with high fidelity. This demonstrates the applicability of optimal control theory to polar molecules for quantum computation.

Ze-Xia Huang, Huang Decai, You-Hong Yu

Ghassen Dridi, Kaipeng Liu, S. Guérin

We develop an inverse geometric optimization technique that allows the derivation of optimal and robust exact solutions of low-dimension quantum control problems driven by external fields. We determine in the dynamical variable space optimal trajectories constrained to robust solutions by Euler-Lagrange optimization; the control fields are then derived from the obtained robust geodesics and the inverted dynamical equations. We apply this method, referred to as robust inverse optimization (RIO), to design optimal control fields producing a complete or half population transfer and a not quantum gate robust with respect to the pulse inhomogeneities. The method is versatile and can be applied to numerous quantum control problems, e.g., other gates, other types of imperfections, Raman processes, or dynamical decoupling of undesirable effects.

Anatoliy G. Butkovskiy, Yu. I. Samoilenko

Marjuka Ferdousi Lazin, Christian Robert Shelton, Simon N. Sandhofer +1 more

Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.