Computing landscape is evolving rapidly. Exascale computers are here, and quantum supremacy has been demonstrated for several problems, while artificial intelligence (AI) is transforming every aspect of our life. Molecular dynamics simulations at the nexus of exascale computing, quantum computing and AI are revolutionizing quantum materials research. I will describe research and education on quantum materials using our AI and quantum-computing enabled exascale materials simulator (AIQ-XMaS). Specifically, I will describe multiscale simulation approaches combining first-principles nonadiabatic quantum molecular dynamics (NAQMD) and machine-learning-based neural-network quantum molecular dynamics (NNQMD) simulations, where neural networks are trained not only to predict accurate interatomic forces but also to describe quantum-mechanical effects such as polarizability through maximally localized Wannier functions, electronic excitations, and nuclear quantum effects through path integrals. Applications include: (1) picosecond optical, electrical and mechanical control of symmetry breaking in topological ferroelectric skyrmion and skyrmionium for ultralow-power polar topotronics; and (2) self-assembly of layered material metastructures for scalable and robust manufacturing of quantum emitters for future quantum information science and technology. This research was supported by NSF Future Manufacturing Program, Award 2036359, NSF Cybertraining Program, Award 2118061, and Sony Research Award. Simulations were performed at Argonne Leadership Computing Facility under DOE INCITE and Aurora Early Science programs and at Center for Advanced Research Computing of the University of Southern California.
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