Work

Toward Practical Application of the Quantum Carleman Lattice Boltzmann Method in Industrial CFD Simulations

Year: 2025

Type: article

Abstract: Computational Fluid Dynamics simulations are crucial in industrial applications but require extensive computational resources, particularly for extreme turbulent regimes. While classical digital approaches remain the standard, quantum computing promises a breakthrough by enabling a more efficient encoding of large-scale simulations with a limited number of qubits. This work presents a practical numerical assessment of a hybrid quantum-classical approach to CFD based on the Lattice Boltzmann Method (LBM). The inherently non-linear LBM equations are linearized via a Carleman expansion and solved using the quantum Harrow-Hassidim-Lloyd algorithm (HHL). We evaluate this method on three benchmark cases featuring different boundary conditions—periodic, bounce-back, and moving wall—using state-vector emulation on high-performance computing resources. Our results confirm the validity of the approach, achieving median error fidelities on the order of$10^{-3}$and success probabilities sufficient for practical quantum state sampling. Notably, the spectral properties of small lattice systems closely approximate those of larger ones, suggesting a pathway to mitigate one of HHL's bottlenecks: eigenvalue pre-evaluation.

Source: IEEE Transactions on Quantum Engineering

DOI: 10.1109/tqe.2025.3620130

Authors: Francesco Turro, Alessandra Lignarolo, Daniele Dragoni

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,075

Funders: National Research Centre, European Commission, NextGenerationEU

Award: G5356239126