activity
20212023
most citedHybrid quantum-classical reservoir computing of thermal convection flow

69 citations · 124 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2023★ 1 cited

Generative convective parametrization of dry atmospheric boundary layer

Florian Heyder, Juan Pedro Mellado, Jörg Schumacher

Turbulence parametrizations will remain a necessary building block in kilometer-scale Earth system models. In convective boundary layers, where the mean vertical gradients of conse…

physics.flu-dyn2023★ 21 cited

Reduced-order modeling of two-dimensional turbulent Rayleigh-Bénard flow by hybrid quantum-classical reservoir computing

Philipp Pfeffer, Florian Heyder, Jörg Schumacher

Two hybrid quantum-classical reservoir computing models are presented to reproduce low-order statistical properties of a two-dimensional turbulent Rayleigh-Bénard convection flow a…

quant-ph2022★ 69 cited

Hybrid quantum-classical reservoir computing of thermal convection flow

Philipp Pfeffer, Florian Heyder, Jörg Schumacher

We simulate the nonlinear chaotic dynamics of Lorenz-type models for a classical two-dimensional thermal convection flow with 3 and 8 degrees of freedom by a hybrid quantum--classi…

physics.flu-dyn2021★ 14 cited

Generalizability of reservoir computing for flux-driven two-dimensional convection

Florian Heyder, Juan Pedro Mellado, Jörg Schumacher

We explore the generalization properties of an echo state network applied as a reduced dynamical model to predict flux-driven two-dimensional turbulent convection. To this end, we…

physics.flu-dyn2021★ 19 cited

Echo State Network for two-dimensional turbulent moist Rayleigh-Bénard convection

Florian Heyder, Jörg Schumacher

Recurrent neural networks are machine learning algorithms which are suited well to predict time series. Echo state networks are one specific implementation of such neural networks…