cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology. cbcbeat is a Python-based software collection targeting computational cardiac electrophysiology problems. cbcbeat contains solvers of varying complexity and performance for the classical monodomain and bidomain equations coupled with cardiac cell models. The cbcbeat solvers are based on algorithms described in Sundnes et al (2006) and the core FEniCS Project software (Logg et al, 2012). All cbcbeat solvers allow for automated derivation and computation of adjoint and tangent linear solutions, functional derivatives and Hessians via the dolfin-adjoint software (Farrell et al, 2013). The computation of functional derivatives in turn allows for automated and efficient solution of optimization problems such as those encountered in data assimillation or other inverse problems. cbcbeat is based on the finite element functionality provided by the FEniCS Project software, the automated derivation and computation of adjoints offered by the dolfin-adjoint software and cardiac cell models from the CellML repository. cbcbeat originates from the Center for Biomedical Computing, a Norwegian Centre of Excellence, hosted by Simula Research Laboratory, Oslo, Norway.
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References in zbMATH (referenced in 3 articles , 1 standard article )
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- Erhardt, André H.; Mardal, Kent-Andre; Schreiner, Jakob E.: Dynamics of a neuron-glia system: the occurrence of seizures and the influence of electroconvulsive stimuli. A mathematical and numerical study (2020)
- Viola, Francesco; Meschini, Valentina; Verzicco, Roberto: Fluid-structure-electrophysiology interaction (FSEI) in the left-heart: a multi-way coupled computational model (2020)
- Marie E. Rognes, Patrick E. Farrell, Simon W. Funke, Johan E. Hake, Molly M. C. Maleckar: cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology (2017) not zbMATH