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Quantum hardware calculations of periodic systems with partition-measurement symmetry verification: Simplified models of hydrogen chain and iron crystals

PHYSICAL REVIEW RESEARCH(2022)

Cited 10|Views7
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Abstract
Running quantum algorithms on real hardware is essential for understanding their strengths and limitations, especially in the noisy intermediate scale quantum (NISQ) era. Herein we focus on the practical aspect of quantum computational calculations of solid-state crystalline materials based on theory developed in our group by using real quantum hardware with a noise mitigation technique referred to as partition-measurement symmetry verification, which performs postselection of shot counts based on Z(2) and U-1 symmetry verification. We select two periodic systems with different levels of complexity for these calculations. One of them is the distorted hydrogen chain as an example of very simple systems, and the other one is iron crystal in the bcc and fcc phases as it is considered to be inaccessible by using classical computational wave-function methods. The ground-state energies are evaluated based on the translational quantum subspace expansion method for the hydrogen chain, and periodic boundary condition adapted variational quantum eigensolver for our iron models. By applying these techniques for the simplest two-qubit iron model systems, the correlation energies obtained by the hardware calculations agree with those of the state-vector simulations within similar to 5 kJ/mol. Although the quantum computational resources used for those experiments are still limited, the techniques applied to obtain our simplified models will be applicable in essentially the same manner to more complicated cases as quantum hardware matures.
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Key words
Quantum Simulation,Quantum Computation,Quantum Computing,Quantum Machine Learning,Semiconductor Quantum Dots
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