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Towards Neural Variational Monte Carlo That Scales Linearly with System Size
Or Sharir, Garnet Kin-Lic Chan, Anima Anandkumar
Quantum many-body problems are some of the most challenging problems in science and are central to demystifying some exotic quantum phenomena, e.g., high-temperature superconductor…
Hyper-optimized approximate contraction of tensor networks with arbitrary geometry
Johnnie Gray, Garnet Kin-Lic Chan
Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compres…
Simulating challenging correlated molecules and materials on the Sycamore quantum processor
Ruslan N. Tazhigulov, Shi-Ning Sun, Reza Haghshenas +6
Simulating complex molecules and materials is an anticipated application of quantum devices. With strong quantum advantage demonstrated in artificial tasks, we examine how such adv…