Quantum Brain
← Back to papers

Variational quantum-algorithm based self-consistent calculations for the two-site DMFT model on noisy quantum computing hardware

J. Ehrlich, D. F. Urban, Christian Elsässer·November 17, 2023·DOI: 10.1088/1361-648X/add4db
MedicinePhysics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Dynamical ean field theory (DMFT) is one of the powerful computational approaches to study electron correlation effects in solid-state materials and molecules. Its practical applicability is, however, limited by the quantity of numerical resources required for the solution of the underlying auxiliary Anderson impurity model. Here, the one-to-one mapping between electronic orbitals and the state of a qubit register suggests a significant computational advantage for the use of a quantum computer (QC) for solving this task. In this work we present a QC approach to solve a two-site DMFT model based on the variational quantum eigensolver (VQE) algorithm. We analyze the propagation of stachastic and device errors through the algorithm and their effects on the calculated self-energy. Therefore, we systematically compare results obtained on simulators with calculations on the IBMQ Ehningen QC hardware. We suggest a means to overcome unphysical features in the self-energy which already result from purely stochastic noise. Based heron, we demonstrate the feasibility to obtain self-consistent results of the two-site DMFT model based on VQE simulations with a finite number of shots.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.