Symmetry-enhanced counterdiabatic quantum algorithm for qudits

Year: 2025

Type: article

Abstract: Qubit-based variational quantum algorithms have undergone rapid development in recent years but still face several challenges. Here, we introduce a symmetry-based enhancement to digitized counterdiabatic quantum algorithms, applicable for qudits of any dimension. This approach offers three types of compression compared to conventional variational circuits. First, compression in the circuit depth is achieved by counterdiabatic protocols. Second, information about the problem is compressed by replacing qubits with qudits, allowing for a more efficient representation of the problem. Finally, the number of parameters is reduced by employing the symmetries of the system. We illustrate this approach by tackling a graph-based optimization problem -3-, a highly entangled state preparation, the qutrit W state, and a two-body only antiferromagnetic Ising problem. As our numerical results show, we achieve a better convergence with a lower circuit depth and less measurement overhead, albeit with some identified limitations for which we propose a work-around. This work leads to a better design of shallow variational quantum circuits, improving the feasibility of their implementation on near-term qudit devices.

Source: Physical Review Research

DOI: 10.1103/6ldg-3w1f

Authors: Alberto Bottarelli, Mikel Garcia de Andoin, Pranav Chandarana, Koushik Paul, Xi Chen, Mikel Sanz, Philipp Hauke

Institutions: University of Trento, Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics And Applications, University of the Basque Country, Tecnalia, Instituto de Ciencia de Materiales de Madrid, Ikerbasque, Basque Center for Applied Mathematics

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,625

Funders: Harvard University Center for Italian Renaissance Studies, National Research Council, European Commission, Eusko Jaurlaritza, Euskal Herriko Unibertsitatea, Fondazione Bruno Kessler, Università degli Studi di Trento, Ministerio de Ciencia e Innovación, Provincia Autonoma di Trento, Basque Center for Applied Mathematics, QuantERA, Ministero dell'Università e della Ricerca, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, European Regional Development Fund, Agencia Estatal de Investigación, Nuclear Physics

OpenAlex ID: W4414956311