A Boot-Strapping Technique to Design Unconditionally Positive Dense Output Formulae for Modified Patankar-Runge-Kutta Methods

Thomas Izgin

Communications on Applied Mathematics and Computation ›› : 1 -25.

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Communications on Applied Mathematics and Computation ›› : 1 -25. DOI: 10.1007/s42967-025-00480-8
Original Paper

A Boot-Strapping Technique to Design Unconditionally Positive Dense Output Formulae for Modified Patankar-Runge-Kutta Methods

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Abstract

In this work, modified Patankar-Runge-Kutta (MPRK) schemes up to order four are considered and equipped with a dense output formula of appropriate accuracy. Since these time integrators are conservative and positivity-preserving for any time step size, we impose the same requirements on the corresponding dense output formula. In particular, we discover that there is an explicit first-order formula. However, to develop a boot-strapping technique, we propose to use implicit formulae which naturally fit into the framework of MPRK schemes. In particular, if lower-order MPRK schemes are used to construct methods of higher order, the same can be done with the dense output formulae we propose in this work. We explicitly construct formulae up to order three and demonstrate how to generalize this approach as long as the underlying Runge-Kutta method possesses a dense output formula of appropriate accuracy. We also note that even though linear systems have to be solved to compute an approximation for intermediate points in time using these higher-order dense output formulae, the overall computational effort to reach a given number of approximations is reduced compared to using the scheme with a smaller step size. We support this fact and our theoretical findings by means of numerical experiments.

Keywords

Dense output formulae / Boot-strapping process / Modified Patankar-Runge-Kutta (MPRK) schemes / Unconditional positivity / Conservativity

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Thomas Izgin. A Boot-Strapping Technique to Design Unconditionally Positive Dense Output Formulae for Modified Patankar-Runge-Kutta Methods. Communications on Applied Mathematics and Computation 1-25 DOI:10.1007/s42967-025-00480-8

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References

[1]

AraújoAL, MuruaA, Sanz-SernaJM. Symplectic methods based on decompositions. SIAM J. Numer. Anal., 1997, 34(5): 1926-1947

[2]

BlanesS, IserlesA, MacnamaraS. Positivity-preserving methods for ordinary differential equations. ESAIM Math. Model. Numer. Anal., 2022, 56(6): 1843-1870

[3]

BolleyC, CrouzeixM. Conservation de la positivité lors de la discrétisation des problèmes d’évolution paraboliques. RAIRO Anal. Numér., 1978, 12(3): 237-245

[4]

BurchardH, DeleersnijderE, MeisterA. A high-order conservative Patankar-type discretisation for stiff systems of production-destruction equations. Appl. Numer. Math., 2003, 47(1): 1-30

[5]

BurchardH, DeleersnijderE, MeisterA. Application of modified Patankar schemes to stiff biogeochemical models for the water column. Ocean Dyn., 2005, 55(3): 326-337

[6]

Butcher, J.C.: Numerical Methods for Ordinary Differential Equations, 3rd edn., pp. 513. John Wiley & Sons Ltd, Chichester (2016). https://doi.org/10.1002/9781119121534

[7]

ButcherJC. B-series and B-series coefficients. J. Numer. Anal. Ind. Appl. Math., 2010, 5(1/2): 39-48

[8]

DoughertyRL, EdelmanA, HymanJM. Nonnegativity-, monotonicity-, or convexity-preserving cubic and quintic Hermite interpolation. Math. Comput., 1989, 52: 471-494

[9]

EnrightWH, JacksonKR, NørsettSP, ThomsenPG. Interpolants for Runge-Kutta formulas. ACM Trans. Math. Softw., 1986, 12(3): 193-218

[10]

Hairer, E., Nørsett, S.P., Wanner, G.: Solving ordinary differential equations. I, 2nd edn. In: Springer Series in Computational Mathematics, vol. 8, pp. 528. Springer, Berlin (1993)

[11]

HussainMZ, SarfrazM. Positivity-preserving interpolation of positive data by rational cubics. J. Comput. Appl. Math., 2008, 218(2): 446-458

[12]

Izgin, T.: A unifying theory for Runge-Kutta-Like time integrators: convergence and stability. PhD thesis, University of Kassel (2024). https://doi.org/10.17170/kobra-202402059522

[13]

IzginT, KopeczS, MeisterA. On Lyapunov stability of positive and conservative time integrators and application to second order modified Patankar-Runge-Kutta schemes. ESAIM Math. Model. Numer. Anal., 2022, 56(3): 1053-1080

[14]

IzginT, KopeczS, MeisterA. On the stability of unconditionally positive and linear invariants preserving time integration schemes. SIAM J. Numer. Anal., 2022, 60(6): 3029-3051

[15]

Izgin, T., Ketcheson, D.I., Meister, A.: Order conditions for Runge-Kutta-like methods with solution-dependent coefficients. Commun. Appl. Math. Computat. Sci. https://doi.org/10.48550/arXiv.2305.14297 (2023)

[16]

IzginT, KopeczS, MeisterA, SchillingA. On the non-global linear stability and spurious fixed points of MPRK schemes with negative RK parameters. Numer. Algorithms, 2024, 96(3): 1221-1242

[17]

Izgin, T., Ranocha, H.: Using Bayesian optimization to design time step size controllers with application to modified Patankar-Runge-Kutta methods. (2023) arXiv:2312.01796

[18]

KetchesonDI, LócziL, JangabylovaA, KusmanovA. Dense output for strong stability preserving Runge-Kutta methods. J. Sci. Comput., 2017, 71(3): 944-958

[19]

KopeczS, MeisterA. On order conditions for modified Patankar-Runge-Kutta schemes. Appl. Numer. Math., 2018, 123: 159-179

[20]

KopeczS, MeisterA. Unconditionally positive and conservative third order modified Patankar-Runge-Kutta discretizations of production-destruction systems. BIT, 2018, 58(3): 691-728

[21]

LefeverR, NicolisG. Chemical instabilities and sustained oscillations. J. Theor. Biol., 1971, 30(2): 267-284

[22]

MickensRE, WashingtonTM. NSFD discretizations of interacting population models satisfying conservation laws. Comput. Math. Appl., 2013, 66(11): 2307-2316 Progress on Difference Equations

[23]

ÖffnerP, TorloD. Arbitrary high-order, conservative and positivity preserving Patankar-type deferred correction schemes. Appl. Numer. Math., 2020, 153: 15-34

[24]

SanduA. Positive numerical integration methods for chemical kinetic systems. J. Comput. Phys., 2001, 170(2): 589-602

[25]

Sandu, A.: Time-stepping methods that favor positivity for atmospheric chemistry modeling. In: Atmospheric Modeling (Minneapolis, MN, 2000). IMA Vol. Math. Appl., vol. 130, pp. 21–37. Springer, New York (2002). https://doi.org/10.1007/978-1-4757-3474-4_2

[26]

TorloD, ÖffnerP, RanochaH. Issues with positivity-preserving Patankar-type schemes. Appl. Numer. Math., 2022, 182: 117-147

[27]

ZennaroM. Natural continuous extensions of Runge-Kutta methods. Math. Comput., 1986, 46: 119-133

Funding

Deutsche Forschungsgemeinschaft(466355003)

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Shanghai University

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