1. Variational ansatz-based quantum simulation of imaginary time evolution
- Author
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Tyson Jones, Xiao Yuan, Ying Li, Simon C. Benjamin, Sam McArdle, and Suguru Endo
- Subjects
Quantum Physics ,Quantum machine learning ,Computer Networks and Communications ,Computer science ,Quantum simulator ,FOS: Physical sciences ,Statistical and Nonlinear Physics ,01 natural sciences ,Imaginary time ,lcsh:QC1-999 ,lcsh:QA75.5-76.95 ,010305 fluids & plasmas ,Computational Theory and Mathematics ,0103 physical sciences ,Computer Science (miscellaneous) ,Statistical physics ,lcsh:Electronic computers. Computer science ,010306 general physics ,Ground state ,Quantum Physics (quant-ph) ,Quantum ,Energy (signal processing) ,lcsh:Physics ,Ansatz ,Quantum computer - Abstract
Imaginary time evolution is a powerful tool for studying quantum systems. While it is possible to simulate with a classical computer, the time and memory requirements generally scale exponentially with the system size. Conversely, quantum computers can efficiently simulate quantum systems, but not non-unitary imaginary time evolution. We propose a variational algorithm for simulating imaginary time evolution on a hybrid quantum computer. We use this algorithm to find the ground-state energy of many-particle systems; specifically molecular hydrogen and lithium hydride, finding the ground state with high probability. Our method can also be applied to general optimisation problems and quantum machine learning. As our algorithm is hybrid, suitable for error mitigation and can exploit shallow quantum circuits, it can be implemented with current quantum computers., Comment: 14 pages
- Published
- 2019
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