Numerical methods for biomembranes: Conforming subdivision methods versus non-conforming PL methods
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- by Jingmin Chen, Thomas Yu, Patrick Brogan, Robert Kusner, Yilin Yang and Andrew Zigerelli HTML | PDF
- Math. Comp. 90 (2021), 471-516
Abstract:
The Canham-Helfrich-Evans models of biomembranes consist of a family of geometric constrained variational problems. In this article, we compare two classes of numerical methods for these variational problems based on piecewise linear (PL) and subdivision surfaces (SS). Since SS methods are based on spline approximation and can be viewed as higher order versions of PL methods, one may expect that the only difference between the two methods is in the accuracy order. In this paper, we prove that a numerical method based on minimizing any one of the ‘PL Willmore energies’ proposed in the literature would fail to converge to a solution of the continuous problem, whereas a method based on minimization of the bona fide Willmore energy, well-defined for SS but not PL surfaces, succeeds. Motivated by this analysis, we propose also a regularization method for the PL method based on techniques from conformal geometry. We address a number of implementation issues crucial for the efficiency of our solver. A software package called Wmincon accompanies this article, and provides parallel implementations of all the relevant geometric functionals. When combined with a standard constrained optimization solver, the geometric variational problems can then be solved numerically. To this end, we realize that some of the available optimization algorithms/solvers are capable of preserving symmetry, while others manage to break symmetry; we explore the consequences of this observation.References
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Additional Information
- Jingmin Chen
- Affiliation: Citigroup Global Markets Inc., 390 Greenwich Street, New York, New York 10013
- MR Author ID: 1228463
- Email: jingmchen@gmail.com
- Thomas Yu
- Affiliation: Department of Mathematics, Drexel University Philadelphia, Pennsylvania 19104
- MR Author ID: 644909
- Email: yut@drexel.edu
- Patrick Brogan
- Affiliation: Department of Mathematics, Drexel University Philadelphia, Pennsylvania 19104
- Email: pbrogan12@gmail.com
- Robert Kusner
- Affiliation: Department of Mathematics, University of Massachusetts at Amherst, Amherst, Massachusetts 01003
- MR Author ID: 244560
- Email: kusner@math.umass.edu
- Yilin Yang
- Affiliation: Center for Computational Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142
- MR Author ID: 1348918
- Email: yiliny@mit.edu
- Andrew Zigerelli
- Affiliation: Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
- ORCID: 0000-0003-0550-6986
- Email: anz37@pitt.edu
- Received by editor(s): January 25, 2019
- Received by editor(s) in revised form: March 13, 2020, June 20, 2020, and July 12, 2020
- Published electronically: November 20, 2020
- Additional Notes: The second author was supported in part by the National Science Foundation grants DMS 0512673, DMS 0915068, and DMS 1115915. The third author was supported in part by the Office of the Provost and the Steinbright Career Development Center of Drexel University. The fourth author was supported in part by the Aspen Center For Physics (funded by NSF-PHY 1607611), ICERM (funded by NSF-DMS 1439786), and MSRI (funded by NSF-DMS 1440140). The sixth author was supported in part by a 2013 Goldwater scholarship during his study at Drexel University.
- © Copyright 2020 by the authors
- Journal: Math. Comp. 90 (2021), 471-516
- MSC (2020): Primary 49M25, 49M37, 65D99, 65K10, 65Z05; Secondary 30C30
- DOI: https://doi.org/10.1090/mcom/3584
- MathSciNet review: 4194152