Classiq and Rolls-Royce Embed Quantum Linear Solvers into Iterative CFD Workflows - Quantum Computing Report

Skip to content

GQINewsNews Archive 2025News Archive 2024News Archive 2023News Archive 2022News Archive 2021News Archive 2020News Archive 2019News Archive 2018News Archive 2015-2017AnalysisQnalysisPlayersPublic CompaniesPrivate/Startup CompaniesUniversitiesGovernment/Non-ProfitVenture CapitalVenture Capital – Sorted by Quantum CompanyResourcesConferencesToolsOther Websites and Industry AssociationsEducationBooksScorecardsGate Level Software PlatformsIBM Qiskit, Rigetti Forest, Microsoft QDK, Project QReview of the Cirq Quantum Software FrameworkQubit Implementation DashboardQubit CountQubit QualityQubit TechnologySoftware/Startup PartnersCloud Platform Hardware PartnersPodcastsAboutQCR Alerts Sign-Up FormAdvertising InquiriesQCR in the NewsContactPrivacy PolicyMembership

Classiq and Rolls-Royce Embed Quantum Linear Solvers into Iterative CFD Workflows

Quantum software synthesis provider Classiq Technologies and aerospace engineering firm Rolls-Royce plc have demonstrated a hybrid quantum-classical computing framework that embeds a Quantum Linear Solver (QLS) directly into an industrial Computational Fluid Dynamics (CFD) pipeline. Developed to optimize the intensive simulation of aerodynamic flows inside jet engine components, the partnership evaluates how the inherent approximations of near-term fault-tolerant quantum algorithms affect the macro-level convergence of nonlinear fluid equations. By replacing the core linear step of an iterative CFD loop with an algorithmic quantum matrix inversion module, the joint engineering team shifted the focus of quantum fluid dynamics from abstract asymptotic complexity bounds to practical, end-to-end operational performance.