Quantum Elements, USC Publish a New Quantum Monte Carlo (QMC) Method for Noisy Circuit Simulation - 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

Quantum Elements, USC Publish a New Quantum Monte Carlo (QMC) Method for Noisy Circuit Simulation

Quantum Elements and the University of Southern California (USC) have published a peer-reviewed paper in Physical Review Letters (PRL) detailing a new Quantum Monte Carlo (QMC) algorithm that significantly lowers the classical computing power needed to simulate noisy quantum circuits. Traditional open-system simulations rely on direct density-matrix tracking, which scales exponentially quickly crippling classical hardware. The new paper titled Real-Time Sign-Problem-Suppressed Quantum Monte Carlo Algorithm for Noisy Quantum Circuit Simulations co-authored by Dr. Tong Shen and USC Professor Daniel A. Lidar, describes how the new algorithm suppresses the notorious quantum “sign problem.” This new algorithm models noisy quantum-circuit behavior with a fraction of the computational footprint while still preserving the critical dynamics needed to evaluate QEC and decoder performance.