cbcbeat: an adjoint-enabled framework for ... - Open Journals
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cbcbeat: an adjoint-enabled framework for ... - Open Journals
computational cardiac electrophysiology. Marie E. ... SIAM Journal on. Scientific Computing 35 (4): C369âC393. doi:10.1137/120873558. Logg, Anders ...
cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology Marie E. Rognes1 , Patrick E. Farrell2 , Simon W. Funke1 , Johan E. Hake3 , and Molly M. C. Maleckar4 1
Simula Research Laboratory 2 University of Oxford 3 Ski videregående skole 4 Allen Institute of Cell Science 29 March 2017 Paper DOI: http://dx.doi.org/10.21105/joss.00224 Software Repository: https://bitbucket.org/meg/cbcbeat Software Archive: http://dx.doi.org/10.5281/zenodo.801552
Summary cbcbeat (cbcbeat 2017) 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 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. The cbcbeat source code is hosted with Bitbucket (https://bitbucket.org/meg/cbcbeat) with documentation on readthedocs (http://cbcbeat.readthedocs.io).
References cbcbeat. 2017. “Cbcbeat: An Adjoint-Enabled Framework for Computational Cardiac Electrophysiology.” https://bitbucket.org/meg/cbcbeat. Farrell, P. E., D. A. Ham, S. W. Funke, and M. E. Rognes. 2013. “Automated Derivation of the Adjoint of High-Level Transient Finite Element Programs.” SIAM Journal on Scientific Computing 35 (4): C369–C393. doi:10.1137/120873558. Logg, Anders, Kent-Andre Mardal, Garth N. Wells, and others. 2012. Automated Solution of Differential Equations by the Finite Element Method. Springer. doi:10.1007/978-3-642-23099-8. Sundnes, Joakim, Glenn Terje Lines, Xing Cai, Bjørn Fredrik Nielsen, Kent-Andre Mardal, and Aslak Tveito. 2006. Computing the Electrical Activity in the Heart. Springer-Verlag.
