To support 6G communication and metaverse minded robot decision-making, we establish a unified quantum transformer (called Q-Transformer) with the capability of prediction and adaptive feedback control interaction, which consists of quantum encode-decode coupling processes. This newly proposed Q-Transformer is integrated into our previously developed quantum cloud computing platform as its smart federated learning engine, which is supported by our recently designed and justified neutral atom quantum computer. The main purpose to develop such an integrated big model platform system is to conduct high-dimensional vector decision-making for real-world internet of things (IoT) systems, which involve big data managements and heavy numerical computations. Specific applications such as multiple objective based robot routing, resource allocation, and dynamic pricing will be given. Related optimization and equilibrium policies will be trained with numerical simulations.

Wanyang Dai is a Distinguished Professor in Nanjing University, Chief Scientist at Su Xia Control Technology, President and CEO of U.S. based (blochchain and quantum computing) SIR Forum, President of Jiangsu Probability & Statistics Society, Chairman of Jiangsu Big Data-Blockchain and Smart Information Special Committee, Chief Scientist at Depths Digital Economy Research Institute.He was an MTS and principal investigator in U.S. based AT&T Bell Labs (currently Nokia Bell Labs) with some project won “Technology Transfer” now called cloud system. His research includes stochastic processes related optimization and optimal control, admission/scheduling/routing protocols and performance analysis/optimization for various projects in BigData-Blockchain oriented quantum-cloud computing and the next generation of wireless and wireline communication systems, forward/backward stochastic (ordinary/partial) differential equations and their applications to queueing systems, stochastic differential games, communication networks, Internet of Things, financial engineering, energy and power engineering, etc.His “influential” achievements are published in “big name” journals including Quantum Information Processing, Operational Research, Operations Research, Computers & Mathematics with Applications, Communications in Mathematical Sciences, Journal of Computational and Applied Mathematics, Queueing Systems, Mathematical and Computer Modeling of Dynamical Systems, etc. His researches are awarded as outstanding papers by various academic societies, e.g., IEEE Top Conference Series, etc. He received his Ph.D. degree in applied mathematics jointly with industrial engineering and systems engineering from Georgia Institute of Technology, Atlanta, GA, U.S.A., in 1996, where he worked on stochastics and applied probability concerning network performance modeling and analysis, algorithm design and implementation via stochastic diffusion approximation. The breakthrough results and methodologies developed in his thesis were cited, used, and claimed as “contemporaneous and independent” achievements by some other subsequent breakthrough papers that were presented as “45 minutes invited talk in probability and statistics” in International Congress of Mathematicians (ICM) 1998, which is the most privilege honor in the mathematical society. The designed finite element-Galerkin algorithm to compute the stationary distributions of reflecting Brownian motions (weak solutions of general dimensional partial differential equations) is also well-known to the related fields.