A parallel and adaptive multigrid solver for the solutions of the optimal control of geometric evolution laws in two and three dimensions

Yang, F, Venkataraman, C, Styles, V and Madzvamuse, A (2015) A parallel and adaptive multigrid solver for the solutions of the optimal control of geometric evolution laws in two and three dimensions. In: 4th International Conference on Computational and Mathematical Biomedical Engineering - CMBE2015, 29 June-1 July 2015, Paris, France. (Accepted)

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Abstract

We present a problem concerning the optimal control of geometric evolution laws. This is a minimisation problem that aims to find a control η which minimises the objective functional J subject to some imposed constraints. We apply this methodology to an application of whole cell tracking. Given two sets of data of cell morphologies, we may solve the optimal control problem to dynamically reconstruct the cell movements between the time frame of these two sets of data. This problem is solved in two and three space dimensions, using a state-of-the-art numerical method, namely multigrid, with adaptivity and parallelism.

Item Type: Conference or Workshop Item (Lecture)
Keywords: Optimal control, geometric evolution laws, phase-field, multigrid, parallel, mesh adaptivity, cell tracking
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
Subjects: Q Science > QA Mathematics > QA0297 Numerical analysis
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Depositing User: Anotida Madzvamuse
Date Deposited: 07 Aug 2015 12:14
Last Modified: 07 Aug 2015 12:16
URI: http://sro.sussex.ac.uk/id/eprint/56044

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Project NameSussex Project NumberFunderFunder Ref
Unravelling new mathematics for 3D cell migrationG1438LEVERHULME TRUSTRPG-2014-149
Mathematical Modelling and Analysis of Spatial Patterning on Evolving SurfacesG0872EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/J016780/1
InCeM: Research Training Network on Integrated Component Cycling in Epithelial Cell MotilityG1546European UnionUnset
Kickstart: Software development and commercialisation of cell tracking algorithmsG1494University of SussexUnset