Research
My research in a general sense deals with simulation, optimization and inverse problems using particle solvers. I mainly apply these techniques to kinetic equations in the context of fusion energy research.
You can find my main publications below. You can find a more extensive list, including open access/preprint links on my Google Scholar page here.
Journal articles
- Løvbak, E., Samaey, G., Accelerated simulation of Boltzmann-BGK equations near the diffusive limit with asymptotic-preserving multilevel Monte Carlo. SIAM Journal on Scientific Computing 45(4), pp. A1862 - A1889. (2023)
- Løvbak, E., Samaey, G., Vandewalle, S., A multilevel Monte Carlo method for asymptotic-preserving particle schemes. Numerische Mathematik, 148(1), 141-186. (2021)
Conference proceedings
- Løvbak, E., Blondeel, F., Lee, A., Vanroye, L., Van Barel, A., Samaey, G., Reversible random number generation for adjoint Monte Carlo simulation of the heat equation. Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2022. Springer, pp. 451-468. (2024)
- Løvbak, E., Mortier, B., Samaey, G., Vandewalle, S., Multilevel Monte Carlo with improved correlation for kinetic equations in the diffusive scaling. Lecture Notes in Computational Science - ICCS 2020. Springer, 374-388. (2020)
- Løvbak, E., Samaey, G., Vandewalle, S., A Multilevel Monte Carlo Asymptotic-Preserving Particle Method for Kinetic Equations in the Diffusion Limit. Monte Carlo and Quasi-Monte Carlo Methods - MCQMC 2018. Springer, 383-402. (2020)
Recorded talks
- Løvbak, E., Samaey, G., Vandewalle, S., Stochastic optimization for tokamak fusion reactor divertor design. RWTH Aachen UQ Hybrid Seminar. 23 November 2021.
- Løvbak, E., Mortier, B., Samaey, G., Vandewalle, S., Asymptotic-preserving multilevel Monte Carlo particle methods for diffusively scaled kinetic equations. RWTH Aachen UQ Hybrid Seminar. 27 October 2020.
- Løvbak, E., Mortier, B., Samaey, G., Vandewalle, S., Particle Simulation of Diffusive Kinetic Equations with Multilevel Monte Carlo. 14th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing - MCQMC 2020 (online). 10-14 August 2020.