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Comparative study of adaptive variational quantum eigensolvers for multi-orbital impurity models

Anirban Mukherjee, Noah Berthusen, João C. Getelina, Peter P. Orth, Yongxin Yao

2023Communications Physics21 citationsDOIOpen Access PDF

Abstract

Abstract Hybrid quantum-classical embedding methods for correlated materials simulations provide a path towards potential quantum advantage. However, the required quantum resources arising from the multi-band nature of d and f electron materials remain largely unexplored. Here we compare the performance of different variational quantum eigensolvers in ground state preparation for interacting multi-orbital embedding impurity models, which is the computationally most demanding step in quantum embedding theories. Focusing on adaptive algorithms and models with 8 spin-orbitals, we show that state preparation with fidelities better than 99.9% can be achieved using about 2 14 shots per measurement circuit. When including gate noise, we observe that parameter optimizations can still be performed if the two-qubit gate error lies below 10 −3 , which is slightly smaller than current hardware levels. Finally, we measure the ground state energy on IBM and Quantinuum hardware using a converged adaptive ansatz and obtain a relative error of 0.7%.

Topics & Concepts

ImpurityQuantumPhysicsComputer scienceStatistical physicsApplied mathematicsComputational physicsMathematicsQuantum mechanicsQuantum and electron transport phenomenaQuantum Computing Algorithms and ArchitecturePhysics of Superconductivity and Magnetism