31 citations · 65 across the 7 of their papers we have counts for
7 papers
Stability of nonlinear dissipative systems with applications in fluid dynamics
Javier Gonzalez-Conde, Daniel Isla, Sergiy Zhuk +1
Nonlinear partial differential equations are central to physics, engineering, and finance. Except in a limited number of integrable cases, their solution generally requires numeric…
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks. Application to Insulation Material Degradation Prognostics
Ibai Ramirez, Jokin Alcibar, Joel Pino +2
Physics-Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains…
Bayesian Physics Informed Neural Networks for Reliable Transformer Prognostics
Ibai Ramirez, Jokin Alcibar, Joel Pino +3
Scientific Machine Learning (SciML) integrates physics and data into the learning process, offering improved generalization compared with purely data-driven models. Despite its pot…
Quantum Carleman linearisation efficiency in nonlinear fluid dynamics
Javier Gonzalez-Conde, Dylan Lewis, Sachin S. Bharadwaj +1
Computational fluid dynamics (CFD) is a specialised branch of fluid mechanics that utilises numerical methods and algorithms to solve and analyze fluid-flow problems. One promising…
Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants
Ibai Ramirez, Joel Pino, David Pardo +5
Transformers are crucial for reliable and efficient power system operations, particularly in supporting the integration of renewable energy. Effective monitoring of transformer hea…
Existence of unbiased resilient estimators in discrete quantum systems
Javier Navarro, Ricard Ravell Rodríguez, Mikel Sanz
The Cramér-Rao bound serves as a crucial lower limit for the mean squared error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prio…
Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation
Maximilian Reichert, Quntao Zhuang, Mikel Sanz
We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless…