Dedalus: A flexible framework for numerical simulations with spectral methods
Keaton J. Burns, Geoffrey M. Vasil, Jeffrey S. Oishi, Daniel Lecoanet, Benjamin P. Brown
Abstract
This paper describes Dedalus, an open-source Python code for simulating partial differential equations from all areas of physics. Dedalus translates plain-text equations into efficient and parallelized solvers using global spectral methods. Here the authors detail the numerical methods enabling this translation and describe the code's design and implementation. They also illustrate its capabilities with diverse examples, including optical network dynamics, magnetized shocks in plasmas, large-scale oceanic flows, low Reynolds number flows, stellar and atmospheric waves, and diamagnetic levitation.
Topics & Concepts
Python (programming language)Computer sciencePartial differential equationSpectral methodNumerical analysisAlgorithmCode (set theory)Applied mathematicsPhysicsSpectral analysisComputational scienceNumerical modelsDifferential equationReynolds numberComputationTranslation (biology)Computer simulationScripting languageFourier transformOrdinary differential equationFourier analysisStatistical physicsNumerical integrationEnclosureMathematical analysisAdvanced Numerical Methods in Computational MathematicsModel Reduction and Neural NetworksComputational Fluid Dynamics and Aerodynamics