TY - JOUR
T1 - Adaptive optimal control of entangled qubits
AU - Goodwin, David L.
AU - Singh, Pranav
AU - Foroozandeh, Mohammadali
N1 - Funding Information:
Funding: M.F. is grateful to the Royal Society for a University Research Fellowship and a University Research Fellow Enhancement Award (URF\R1\180233 and RGF\EA\181018) that have funded this project.
PY - 2022/12/7
Y1 - 2022/12/7
N2 - Developing fast, robust, and accurate methods for optimal control of quantum systems comprising interacting particles is one of the most active areas of current science. Although a valuable repository of algorithms is available for numerical applications in quantum control, the high computational cost is somewhat overlooked. Here, we present a fast and accurate optimal control algorithm for systems of interacting qubits, QOALA (quantum optimal control by adaptive low-cost algorithm), which is predicted to offer O(M
2) speedup for an M-qubit system, compared to the state-of-the-art exact methods, without compromising overall accuracy of the optimal solution. The method is general and compatible with diverse Hamiltonian structures. The proposed approach uses inexpensive low-accuracy approximations of propagators far from the optimum, adaptively switching to higher accuracy, higher-cost propagators when approaching the optimum. In addition, the utilization of analytical Lie algebraic derivatives that do not require computationally expensive matrix exponential brings even better performance.
AB - Developing fast, robust, and accurate methods for optimal control of quantum systems comprising interacting particles is one of the most active areas of current science. Although a valuable repository of algorithms is available for numerical applications in quantum control, the high computational cost is somewhat overlooked. Here, we present a fast and accurate optimal control algorithm for systems of interacting qubits, QOALA (quantum optimal control by adaptive low-cost algorithm), which is predicted to offer O(M
2) speedup for an M-qubit system, compared to the state-of-the-art exact methods, without compromising overall accuracy of the optimal solution. The method is general and compatible with diverse Hamiltonian structures. The proposed approach uses inexpensive low-accuracy approximations of propagators far from the optimum, adaptively switching to higher accuracy, higher-cost propagators when approaching the optimum. In addition, the utilization of analytical Lie algebraic derivatives that do not require computationally expensive matrix exponential brings even better performance.
UR - http://www.scopus.com/inward/record.url?scp=85143559961&partnerID=8YFLogxK
U2 - 10.1126/sciadv.abq4244
DO - 10.1126/sciadv.abq4244
M3 - Article
C2 - 36475803
AN - SCOPUS:85143559961
VL - 8
SP - eabq4244
JO - Science Advances
JF - Science Advances
SN - 2375-2548
IS - 49
M1 - eabq4244
ER -