TY - JOUR
T1 - Optimal Spin Polarization Control for the Spin-Exchange Relaxation-Free System Using Adaptive Dynamic Programming
AU - Wang, Ruigang
AU - Wang, Zhuo
AU - Liu, Sixun
AU - Li, Tao
AU - Li, Feng
AU - Qin, Bodong
AU - Wei, Qinglai
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - This work is the first to solve the 3-D spin polarization control (3DSPC) problem of atomic ensembles, which controls the spin polarization to achieve arbitrary states with the cooperation of multiphysics fields. First, a novel adaptive dynamic programming (ADP) structure is proposed based on the developed multicritic multiaction neural network (MCMANN) structure with nonquadratic performance functions, as a way to solve the multiplayer nonzero-sum game (MP-NZSG) problem in 3DSPC under the constraints of asymmetric saturation inputs. Then, we utilize the MCMANNs to implement the multicritic multiaction ADP (MCMA-ADP) algorithm, whose convergence is proven by the compression mapping principle. Finally, the MCMA-ADP is deployed in the spin-exchange relaxation-free (SERF) system to provide a set of control laws in 3DSPC that fully exploits the multiphysics fields to achieve arbitrary spin polarization states. Numerical simulations support the theoretical results.
AB - This work is the first to solve the 3-D spin polarization control (3DSPC) problem of atomic ensembles, which controls the spin polarization to achieve arbitrary states with the cooperation of multiphysics fields. First, a novel adaptive dynamic programming (ADP) structure is proposed based on the developed multicritic multiaction neural network (MCMANN) structure with nonquadratic performance functions, as a way to solve the multiplayer nonzero-sum game (MP-NZSG) problem in 3DSPC under the constraints of asymmetric saturation inputs. Then, we utilize the MCMANNs to implement the multicritic multiaction ADP (MCMA-ADP) algorithm, whose convergence is proven by the compression mapping principle. Finally, the MCMA-ADP is deployed in the spin-exchange relaxation-free (SERF) system to provide a set of control laws in 3DSPC that fully exploits the multiphysics fields to achieve arbitrary spin polarization states. Numerical simulations support the theoretical results.
KW - 3-D spin polarization control (3DSPC)
KW - adaptive dynamic programming (ADP)
KW - asymmetric input constraint
KW - multicritic multiaction neural networks (MCMANNs)
KW - multiphysics
KW - multiplayer nonzero-sum game (MP-NZSG)
KW - spin-exchange relaxation-free (SERF)
UR - https://www.scopus.com/pages/publications/85146245720
U2 - 10.1109/TNNLS.2022.3230200
DO - 10.1109/TNNLS.2022.3230200
M3 - 文章
C2 - 37015668
AN - SCOPUS:85146245720
SN - 2162-237X
VL - 35
SP - 5835
EP - 5847
JO - IEEE Transactions on Neural Networks and Learning Systems
JF - IEEE Transactions on Neural Networks and Learning Systems
IS - 5
ER -