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Scaling the Variational Quantum Eigensolver for Dynamic Portfolio Optimization

2024/12/26 by Álvaro Nodar, Nodar, Álvaro, De León, Irene +21 · 3 citations
Computer Science · Economics, Econometrics and Finance · #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.2412.19150

Abstract

This work explores the potential of the Variational Quantum Eigensolver in solving Dynamic Portfolio Optimization problems surpassing the 100 qubit utility frontier. We systematically analyze how to scale this strategy in complexity and size, from 6 to 112 qubits, by testing different combinations of ansatz and optimizer on a real Quantum Processing Unit. We achieve best results by using a combination of a Differential Evolution classical optimizer and an ansatz circuit tailored to both the problem and the properties of the Quantum Processing Unit.

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