Digital twinHow Much Training is Needed with a Digital Twin?arXiv API — полнотекстовый поиск "digital twin" · 17hDigital twinPUR-1 Cyber-Physical Digital TwinarXiv — Computational Engineering, Finance, and Science (cs.CE) · yesterdayDigital twinForesight session on the future of cyber-physical systems security in RussiaspbIT · yesterdayForecastingStochastic Nonlinear MPC with Gaussian Mixture Uncertainty PropagationarXiv — Systems and Control (eess.SY) · yesterdayMarket & productsUS Nurses Protest Against Hospital Contracts with PalantirCNews · yesterdayModellingDigital Sector Expands AI Practice with Agentic ScenariosCNews · 2dModellingMechanics of Democratic Dominance: System Dynamics for Consent EngineeringarXiv — Physics and Society (physics.soc-ph) · 2dDigital twinRemote-Sensing-Based Channel Modeling for 6G Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 2dForecastingDistributed MPC for Optimal Consensus of Heterogeneous Multi-Agent SystemsarXiv — Systems and Control (eess.SY) · 2dEnergyInitialization Is Key in Federated Short-Term Load ForecastingarXiv — Systems and Control (eess.SY) · 2dDigital twinSpec2Twin-Chain: Automating Blockchain Digital Twin ConstructionarXiv API — полнотекстовый поиск "digital twin" · 2dDigital twinCyber-Physical Machine Tool with Real-Time Machining Process Digital TwinarXiv API — полнотекстовый поиск "digital twin" · 2d
Bayesian Calibration of an Accelerator Digital Twin with Machine Learning Assistance
US & West ·
A method is developed for calibrating a digital twin of a particle accelerator at Brookhaven National Laboratory using beam orbit measurements. Bayesian methods estimate parameters, including quadrupole transfer functions, with uncertainties. Machine learning acceleration is provided by an emulator trained on an ensemble of Bmad simulations with perturbed parameters.
Why it matters
The work shows how combining Bayesian calibration and ML emulators enables accurate digital twins of complex physical systems, relevant for modeling large infrastructure.
Original headline
Machine learning assisted Bayesian calibration of an accelerator digital twin from orbit response data
Investigates how many training pilots are needed when a digital twin of a wireless channel is used for channel estimation. The twin is treated as a complementary measurement fused with pilot observations. For the first time, this trade-off is formalized and quantified.
The article discusses an architecture of a digital twin for nuclear systems, integrating multiple models (physics-based and data-driven) to support decision making, state estimation, predictive control, and real-time data processing. The twin must synchronize with the physical facility faster than its operational cycle.
The company 'Aktiv' has finalized a document based on the foresight session held in Moscow in March 2025. The document includes strategic recommendations and forecasts for the industry development until 2040.
