Convergence analysis of the variational operator splitting scheme for a reaction-diffusion system with detailed balance

We present a detailed convergence analysis for an operator splitting scheme proposed in [C. Liu et al., J. Comput. Phys., 436, 110253, 2021] for a reaction-diffusion system with detailed balance. The numerical scheme has been constructed based on a recently developed energetic variational formulation, in which the reaction part is reformulated in terms of the reaction trajectory, and both the reaction and diffusion parts dissipate the same free energy. The scheme is energy stable and positivity-preserving. In this paper, the detailed convergence analysis and error estimate are performed for the operator splitting scheme. The nonlinearity in the reaction trajectory equation, as well as the implicit treatment of nonlinear and singular logarithmic terms, impose challenges in numerical analysis. To overcome these difficulties, we make use of the convex nature of the logarithmic nonlinear terms, which are treated implicitly in the chemical reaction stage. In addition, a combination of a rough error estimate and a refined error estimate leads to a desired bound of the numerical error in the reaction stage, in the discrete maximum norm. Furthermore, a discrete maximum principle yields the evolution bound of the numerical error function at the diffusion stage. As a direct consequence, a combination of the numerical error analysis at different stages and the consistency estimate for the operator splitting results in the convergence estimate of the numerical scheme for the full reaction-diffusion system.

[1]  Hui Zhang,et al.  Convergence of a Fast Explicit Operator Splitting Method for the Epitaxial Growth Model with Slope Selection , 2017, SIAM J. Numer. Anal..

[2]  Alexander Ostermann,et al.  An almost symmetric Strang splitting scheme for nonlinear evolution equations , 2013, Comput. Math. Appl..

[3]  Steven M. Wise,et al.  A positivity-preserving, energy stable scheme for a Ternary Cahn-Hilliard system with the singular interfacial parameters , 2021, J. Comput. Phys..

[4]  J. Wei,et al.  Axiomatic Treatment of Chemical Reaction Systems , 1962 .

[5]  Matthias Liero,et al.  Gradient structures and geodesic convexity for reaction–diffusion systems , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  L. Desvillettes,et al.  Exponential decay toward equilibrium via entropy methods for reaction–diffusion equations , 2006 .

[7]  B. Perthame,et al.  The Hele–Shaw Asymptotics for Mechanical Models of Tumor Growth , 2013, Archive for Rational Mechanics and Analysis.

[8]  Carsten Wiuf,et al.  Lyapunov Functions, Stationary Distributions, and Non-equilibrium Potential for Reaction Networks , 2015, Bulletin of mathematical biology.

[9]  Stéphane Descombes,et al.  Convergence of a splitting method of high order for reaction-diffusion systems , 2001, Math. Comput..

[10]  Hui Zhang,et al.  A positivity-preserving, energy stable and convergent numerical scheme for the Cahn–Hilliard equation with a Flory–Huggins–Degennes energy , 2019, Communications in Mathematical Sciences.

[11]  Cheng Wang,et al.  A Positive and Energy Stable Numerical Scheme for the Poisson-Nernst-Planck-Cahn-Hilliard Equations with Steric Interactions , 2020, J. Comput. Phys..

[12]  June-Yub Lee,et al.  A second order operator splitting method for Allen–Cahn type equations with nonlinear source terms , 2015 .

[13]  D Shear,et al.  An analog of the Boltzmann H-theorem (a Liapunov function) for systems of coupled chemical reactions. , 1967, Journal of theoretical biology.

[14]  Alexander Ostermann,et al.  Convergence Analysis of Strang Splitting for Vlasov-Type Equations , 2012, SIAM J. Numer. Anal..

[15]  Min Tang,et al.  An accurate front capturing scheme for tumor growth models with a free boundary limit , 2017, J. Comput. Phys..

[16]  C. M. Elliott,et al.  On the Cahn-Hilliard equation with degenerate mobility , 1996 .

[17]  Miglena N. Koleva,et al.  Operator splitting kernel based numerical method for a generalized Leland's model , 2015, J. Comput. Appl. Math..

[18]  Petra Csomós,et al.  Operator splitting for nonautonomous delay equations , 2012, Comput. Math. Appl..

[19]  T. Elston,et al.  A robust numerical algorithm for studying biomolecular transport processes. , 2003, Journal of theoretical biology.

[20]  Marc Massot,et al.  Operator splitting for nonlinear reaction-diffusion systems with an entropic structure : singular perturbation and order reduction , 2004, Numerische Mathematik.

[21]  Steven M. Wise,et al.  Structure-preserving, energy stable numerical schemes for a liquid thin film coarsening model , 2020, SIAM J. Sci. Comput..

[22]  Christian Lubich,et al.  On splitting methods for Schrödinger-Poisson and cubic nonlinear Schrödinger equations , 2008, Math. Comput..

[23]  Alexander Mielke,et al.  Thermomechanical modeling of energy-reaction-diffusion systems, including bulk-interface interactions , 2012 .

[24]  Alain Miranville,et al.  The Cahn–Hilliard–Oono equation with singular potential , 2017 .

[25]  P. Markowich,et al.  On time-splitting spectral approximations for the Schrödinger equation in the semiclassical regime , 2002 .

[26]  Alexander Mielke,et al.  A gradient structure for reaction–diffusion systems and for energy-drift-diffusion systems , 2011 .

[27]  Jingfang Huang,et al.  A second order operator splitting numerical scheme for the “good” Boussinesq equation , 2017 .

[28]  Wenrui Hao,et al.  Spatial pattern formation in reaction–diffusion models: a computational approach , 2020, Journal of mathematical biology.

[29]  Steven M. Wise,et al.  A positivity-preserving, energy stable and convergent numerical scheme for the Poisson-Nernst-Planck system , 2020, Math. Comput..

[30]  Sergey Zelik,et al.  Robust exponential attractors for Cahn‐Hilliard type equations with singular potentials , 2004 .

[31]  Jie Shen,et al.  Error Analysis of the Strang Time-Splitting Laguerre–Hermite/Hermite Collocation Methods for the Gross–Pitaevskii Equation , 2013, Found. Comput. Math..

[32]  Xingye Yue,et al.  Convergence analysis of a numerical scheme for the porous medium equation by an energetic variational approach , 2019, Numerical Mathematics: Theory, Methods and Applications.

[33]  Chun Liu,et al.  A two species micro-macro model of wormlike micellar solutions and its maximum entropy closure approximations: An energetic variational approach , 2021, Journal of Non-Newtonian Fluid Mechanics.

[34]  F. Jülicher,et al.  Modeling molecular motors , 1997 .

[35]  Douglas N. Arnold Stability, consistency, and convergence of numerical discretizations , 2015 .

[36]  Bao Quoc Tang,et al.  Trend to Equilibrium for Reaction-Diffusion Systems Arising from Complex Balanced Chemical Reaction Networks , 2016, SIAM J. Math. Anal..

[37]  Steven M. Wise,et al.  An Energy Stable Finite Element Scheme for the Three-Component Cahn–Hilliard-Type Model for Macromolecular Microsphere Composite Hydrogels , 2021, Journal of Scientific Computing.

[38]  Helmut Abels,et al.  Convergence to equilibrium for the Cahn–Hilliard equation with a logarithmic free energy , 2007 .

[39]  Arnaud Debussche,et al.  On the Cahn-Hilliard equation with a logarithmic free energy , 1995 .

[40]  Shan Zhao,et al.  Operator splitting ADI schemes for pseudo-time coupled nonlinear solvation simulations , 2014, J. Comput. Phys..

[41]  Juan Vicente Gutiérrez-Santacreu,et al.  Unconditionally stable operator splitting algorithms for the incompressible magnetohydrodynamics system discretized by a stabilized finite element formulation based on projections , 2013 .

[42]  J. E. Pearson Complex Patterns in a Simple System , 1993, Science.

[43]  David Kinderlehrer,et al.  A Variational Principle for Molecular Motors , 2003 .

[44]  Cheng Wang,et al.  On the Operator Splitting and Integral Equation Preconditioned Deferred Correction Methods for the “Good” Boussinesq Equation , 2018, J. Sci. Comput..

[45]  Mechthild Thalhammer,et al.  Convergence Analysis of High-Order Time-Splitting Pseudospectral Methods for Nonlinear Schrödinger Equations , 2012, SIAM J. Numer. Anal..

[46]  Stein Shiromoto,et al.  Lyapunov functions , 2012 .

[47]  Shigeru Kondo,et al.  Reaction-Diffusion Model as a Framework for Understanding Biological Pattern Formation , 2010, Science.

[48]  Kristoffer G. van der Zee,et al.  Numerical simulation of a thermodynamically consistent four‐species tumor growth model , 2012, International journal for numerical methods in biomedical engineering.

[49]  Cheng Wang,et al.  Positivity-preserving, energy stable numerical schemes for the Cahn-Hilliard equation with logarithmic potential , 2017, J. Comput. Phys. X.

[50]  Frank Jülicher,et al.  Active gel physics , 2015, Nature Physics.

[51]  A. Folkesson Analysis of numerical methods , 2011 .

[52]  Christophe Besse,et al.  Order Estimates in Time of Splitting Methods for the Nonlinear Schrödinger Equation , 2002, SIAM J. Numer. Anal..

[53]  Annegret Glitzky,et al.  A gradient structure for systems coupling reaction–diffusion effects in bulk and interfaces , 2012 .

[54]  Su Zhao,et al.  Operator splitting implicit integration factor methods for stiff reaction-diffusion-advection systems , 2011, J. Comput. Phys..

[55]  Cheng Wang,et al.  A Structure-preserving, Operator Splitting Scheme for Reaction-Diffusion Equations Involving the Law of Mass Action , 2020, ArXiv.