Probabilistic Eigensolver with a Trapped-Ion Quantum Processor

TL;DR

This paper introduces a hybrid quantum-classical probabilistic method for eigenvalue computation and eigenstate preparation tailored for trapped-ion quantum processors, addressing key challenges in quantum simulation.

Contribution

It presents a novel approach combining classical and quantum techniques specifically designed for trapped-ion systems to improve eigenstate and eigenvalue calculations.

Findings

Demonstrates the feasibility of the method on trapped-ion hardware

Achieves accurate eigenvalue estimations for simulated Hamiltonians

Provides a scalable approach for quantum eigenstate preparation

Abstract

Quantum simulation of complex quantum systems and their properties often requires the ability to prepare initial states in an eigenstate of the Hamiltonian to be simulated. In addition, to compute the eigenvalues of a Hamiltonian is in general a non-trivial problem. Here, we propose a hybrid quantum-classical probabilistic method to compute eigenvalues and prepare eigenstates of Hamiltonians which are simulatable with a trapped-ion quantum processor.