Simulating Quantum Configurational Tunneling Using Machine Learning Assisted Quantum Computation
Quantum computing is currently entering an era of realworld application development. Here we present our work on developing one of the first such applications by simulating an experiment, which exhibits quantum tunnelling between different electronic configurations. The material system we deal with is 1TTaS2 in a metastable state, where electrons crystalize into a mosaic of lattices separated by domain walls. We developed a strongly correlated model which is able to describe the configurational ordering
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