Abstract

We have developed a framework for using quantum annealing computation to evaluate a key quantity in ionic diffusion in solids, the correlation factor. Existing methods can only calculate the correlation factor analytically in the case of physically unrealistic models, making it difficult to relate microstructural information about diffusion path networks obtainable by current ab initio techniques to macroscopic quantities such as diffusion coefficients. We have mapped the problem into a quantum spin system described by the Ising Hamiltonian. By applying our framework in combination with ab initio technique, it is possible to understand how diffusion coefficients are controlled by temperatures, pressures, atomic substitutions, and other factors. We have calculated the correlation factor in a simple case with a known exact result by a variety of computational methods, including simulated quantum annealing on the spin models, the classical random walk, the matrix description, and quantum annealing on D-Wave with hybrid solver . This comparison shows that all the evaluations give consistent results with each other, but that many of the conventional approaches require infeasible computational costs. Quantum annealing is also currently infeasible because of the cost and scarcity of qubits, but we argue that when technological advances alter this situation, quantum annealing will easily outperform all existing methods.

Highlights

  • We have developed a framework for using quantum annealing computation to evaluate a key quantity in ionic diffusion in solids, the correlation factor

  • The quantum annealing ­technique1,2 has been widely and successfully applied to challenging combinatorial ­optimizations3, including NP(Non-deterministic Polynomial time)-hard4 and NP-complete p­ roblems3,5–7. Realistic problems such as the capacitated vehicle routing problem (CVRP), optimization of traffic q­ uantity8–11, investment portfolio d­ esign12, scheduling p­ roblems13, and digital m­ arketing14 have recently been addressed by quantum annealing

  • We developed a framework to evaluate the correlation factor, a key quantity used to derive the macroscopic diffusion coefficient for ions in solid materials

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Summary

Introduction

We have developed a framework for using quantum annealing computation to evaluate a key quantity in ionic diffusion in solids, the correlation factor. Quantum annealing computers (QACs) are used only to identify the optimal trajectories while the calculation of Eq [1] is made by a classical counting over a table like Table 1.

Results
Conclusion

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