arXiv subjects

Sergio García Herreros

Publications and source records attributed to Sergio García Herreros.

4 recordsLinked to original sources

arXiv2026

Implicit-Explicit time integration scheme with Physics-based preconditioning for two-fluid tokamak boundary simulations

In this work, a globally stiffly accurate Implicit-Explicit (IMEX) Runge-Kutta scheme is developed and implemented in the GBS code [Ricci et al., Plasma Phys. Control. Fusion, 2012], for two-fluid plasma turbulence simulations. The stiffest phenomena, governed by shear Alfvén waves and parallel diffusion, are treated implicitly, while the remaining non-stiff terms are advanced explicitly. This splitting enables time steps well beyond the Courant-Friedrichs-Lewy limit, without incurring the full computational cost of a globally implicit formulation. To efficiently solve the implicit subsystem at each time step, a three-dimensional physics-based preconditioner, inspired by techniques developed in the magnetohydrodynamic (MHD) context, is used. The resulting framework is verified through the method of manufactured solutions and exhibits both algorithmic and parallel scalability. Significant advantages in numerical stability and computational efficiency are demonstrated with respect to an adaptive explicit Runge-Kutta scheme.

physics.plasm-ph↗

arXiv2026

On energy conservation laws in the drift-reduced Braginskii model

A revision of the drift-reduced Braginskii model is presented, focusing on its practical implementation in numerical codes, and systematically analyzing the effect of several commonly-used approximations on energy conservation. As a practical example, the effect of the approximations is quantified in the GBS code. By dropping the most important approximations and related energy sinks, the simulation shows increased transport levels and a target heat flux with closer agreement to experimental observations.

physics.plasm-ph↗

arXiv2026

Conservative formulation of the drift-reduced fluid plasma model

A conservative formulation of the drift-reduced fluid plasma model is constructed by analytically inverting the implicit relation defining the polarisation velocity as a function of the time-derivative of the electric field. The obtained model satisfies exact conservation laws for energy, mass, charge and momentum, in arbitrary magnetic geometry, also when electromagnetic fluctuations are included.

physics.plasm-ph↗

arXiv2023

Parameter estimation by learning quantum correlations in continuous photon-counting data using neural networks

We present an inference method utilizing artificial neural networks for parameter estimation of a quantum probe monitored through a single continuous measurement. Unlike existing approaches focusing on the diffusive signals generated by continuous weak measurements, our method harnesses quantum correlations in discrete photon-counting data characterized by quantum jumps. We benchmark the precision of this method against Bayesian inference, which is optimal in the sense of information retrieval. By using numerical experiments on a two-level quantum system, we demonstrate that our approach can achieve a similar optimal performance as Bayesian inference, while drastically reducing computational costs. Additionally, the method exhibits robustness against the presence of imperfections in both measurement and training data. This approach offers a promising and computationally efficient tool for quantum parameter estimation with photon-counting data, relevant for applications such as quantum sensing or quantum imaging, as well as robust calibration tasks in laboratory-based settings.

quant-ph↗