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Drift-preserving numerical integrators for stochastic Poisson systems. (English) Zbl 1480.65014

Summary: We perform a numerical analysis of a class of randomly perturbed Hamiltonian systems and Poisson systems. For the considered additive noise perturbation of such systems, we show the long-time behaviour of the energy and quadratic Casimirs for the exact solution. We then propose and analyse a drift-preserving splitting scheme for such problems with the following properties: exact drift preservation of energy and quadratic Casimirs, mean-square order of convergence 1, weak order of convergence 2. These properties are illustrated with numerical experiments.

MSC:

65C30 Numerical solutions to stochastic differential and integral equations
65P10 Numerical methods for Hamiltonian systems including symplectic integrators
60H10 Stochastic ordinary differential equations (aspects of stochastic analysis)
60H35 Computational methods for stochastic equations (aspects of stochastic analysis)

References:

[1] Abdulle, A.; Cohen, D.; Vilmart, G.; Zygalakis, K., High order weak methods for stochastic differential equations based on modified equations, SIAM J. Sci. Comput., 34, A1800-A1823 (2012) · Zbl 1246.65008 · doi:10.1137/110846609
[2] Alamo, A.; Sanz-Serna, J. M., Word combinatorics for stochastic differential equations: splitting integrators, Commun. Pure Appl. Anal., 18, 2163-2195 (2019) · Zbl 1476.60092
[3] Anton, R.; Cohen, D., Exponential integrators for stochastic Schrödinger equations driven by itønoise, J. Comput. Math., 36, 276-309 (2018) · Zbl 1413.65006 · doi:10.4208/jcm.1701-m2016-0525
[4] Anton, R.; Cohen, D.; Larsson, S.; Wang, X., Full discretization of semilinear stochastic wave equations driven by multiplicative noise, SIAM J. Numer. Anal., 54, 1093-1119 (2016) · Zbl 1336.65008 · doi:10.1137/15M101049X
[5] Blanes, S. and Casas, F., A concise introduction to geometric numerical integration, Monographs and Research Notes in Mathematics, CRC Press, Boca Raton, FL, 2016. MR 3642447. · Zbl 1343.65146
[6] Brugnano, L.; Calvo, M.; Montijano, J. I.; Rández, L., Energy-preserving methods for Poisson systems, J. Comput. Appl. Math., 236, 3890-3904 (2012) · Zbl 1247.65092 · doi:10.1016/j.cam.2012.02.033
[7] Brugnano, L.; Gurioli, G.; Iavernaro, F., Analysis of energy and quadratic invariant preserving (EQUIP) methods, J. Comput. Appl. Math., 335, 51-73 (2018) · Zbl 1444.65069 · doi:10.1016/j.cam.2017.11.043
[8] Brugnano, L.; Iavernaro, F., Line integral methods which preserve all invariants of conservative problems, J. Comput. Appl. Math., 236, 3905-3919 (2012) · Zbl 1246.65108 · doi:10.1016/j.cam.2012.03.026
[9] Burrage, P. M.; Burrage, K., Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise, Numer. Algor., 65, 519-532 (2014) · Zbl 1291.65017 · doi:10.1007/s11075-013-9796-6
[10] Celledoni, E.; Farré Puiggalí, M.; Høiseth, E. H.; Martín de Diego, D., Energy-preserving integrators applied to nonholonomic systems, J. Nonlinear Sci., 29, 1523-1562 (2019) · Zbl 1436.37094 · doi:10.1007/s00332-018-9524-4
[11] Celledoni, E.; McLachlan, R. I.; McLaren, D. I.; Owren, B.; Quispel, G. R.W.; Wright, W. M., Energy-preserving Runge-Kutta methods, M2AN Math. Model. Numer. Anal., 43, 645-649 (2009) · Zbl 1169.65348 · doi:10.1051/m2an/2009020
[12] Celledoni, E.; Owren, B.; Sun, Y., The minimal stage, energy preserving Runge-Kutta method for polynomial Hamiltonian systems is the averaged vector field method, Math. Comput., 83, 1689-1700 (2014) · Zbl 1296.65182 · doi:10.1090/S0025-5718-2014-02805-6
[13] Chen, C.; Cohen, D.; D’Ambrosio, R.; Lang, A., Drift-preserving numerical integrators for stochastic Hamiltonian systems, Adv. Comput. Math., 46, 1-22 (2020) · Zbl 07188447 · doi:10.1007/s10444-020-09771-5
[14] Cohen, D., On the numerical discretisation of stochastic oscillators, Math. Comput. Simul., 82, 1478-1495 (2012) · Zbl 1246.65012 · doi:10.1016/j.matcom.2012.02.004
[15] Cohen, D.; Cui, J.; Hong, J.; Sun, L., Exponential integrators for stochastic Maxwell’s equations driven by itô noise, J. Comput. Phys., 410 (2020) · Zbl 1436.60061
[16] Cohen, D.; Dujardin, G., Energy-preserving integrators for stochastic Poisson systems, Commun. Math. Sci., 12, 1523-1539 (2014) · Zbl 1310.60074 · doi:10.4310/CMS.2014.v12.n8.a7
[17] Cohen, D.; Hairer, E., Linear energy-preserving integrators for Poisson systems, BIT, 51, 91-101 (2011) · Zbl 1216.65175 · doi:10.1007/s10543-011-0310-z
[18] Cohen, D.; Larsson, S.; Sigg, M., A trigonometric method for the linear stochastic wave equation, SIAM J. Numer. Anal., 51, 204-222 (2013) · Zbl 1273.65010 · doi:10.1137/12087030X
[19] Cohen, D.; Sigg, M., Convergence analysis of trigonometric methods for stiff second-order stochastic differential equations, Numer. Math., 121, 1-29 (2012) · Zbl 1247.65004 · doi:10.1007/s00211-011-0426-8
[20] Cui, J., Hong, J., and Sheng, D., Convergence in density of splitting AVF scheme for stochastic Langevin equation, arXiv (2019) Available at https://arxiv.org/abs/1906.03439.
[21] de la Cruz, H.; Jimenez, J. C.; Zubelli, J. P., Locally linearized methods for the simulation of stochastic oscillators driven by random forces, BIT, 57, 123-151 (2017) · Zbl 1364.65021 · doi:10.1007/s10543-016-0620-2
[22] Gonzalez, O., Time integration and discrete Hamiltonian systems, J. Nonlinear Sci., 6, 449-467 (1996) · Zbl 0866.58030 · doi:10.1007/s003329900018
[23] Hairer, E., Energy-preserving variant of collocation methods, JNAIAM. J. Numer. Anal. Ind. Appl. Math., 5, 73-84 (2010) · Zbl 1432.65185
[24] Hairer, E.; Lubich, C.; Wanner, G., Geometric numerical integration illustrated by the Störmer-Verlet method, Acta Numer., 12, 399-450 (2003) · Zbl 1046.65110 · doi:10.1017/S0962492902000144
[25] Hairer, E.; Lubich, C.; Wanner, G., Geometric Numerical Integration: Structure-Preserving Algorithms for Ordinary Differential Equations (2006), Springer-Verlag: Springer-Verlag, Berlin, Heidelberg · Zbl 1094.65125
[26] Han, M.; Ma, Q.; Ding, X., High-order stochastic symplectic partitioned Runge-Kutta methods for stochastic Hamiltonian systems with additive noise, Appl. Math. Comput., 346, 575-593 (2019) · Zbl 1429.65016 · doi:10.1016/j.amc.2018.10.041
[27] Holm, D. D.; Tyranowski, T. M., Stochastic discrete Hamiltonian variational integrators, BIT, 58, 1009-1048 (2018) · Zbl 06989587 · doi:10.1007/s10543-018-0720-2
[28] Hong, J.; Scherer, R.; Wang, L., Midpoint rule for a linear stochastic oscillator with additive noise, Neural Parallel Sci. Comput., 14, 1-12 (2006) · Zbl 1105.65008
[29] Iavernaro, F.; Trigiante, D., High-order symmetric schemes for the energy conservation of polynomial Hamiltonian problems, JNAIAM J. Numer. Anal. Ind. Appl. Math., 4, 87-101 (2009) · Zbl 1191.65169
[30] Kojima, H., Invariants preserving schemes based on explicit Runge-Kutta methods, BIT, 56, 1317-1337 (2016) · Zbl 1358.65046 · doi:10.1007/s10543-016-0608-y
[31] Komori, Y.; Cohen, D.; Burrage, K., Weak second order explicit exponential Runge-Kutta methods for stochastic differential equations, SIAM J. Sci. Comput., 39, A2857-A2878 (2017) · Zbl 1387.65064 · doi:10.1137/15M1041341
[32] Leimkuhler, B. and Reich, S.. Simulating Hamiltonian dynamics, Cambridge Monographs on Applied and Computational Mathematics Vol. 14, Cambridge University Press, Cambridge, 2004. MR 2132573. · Zbl 1069.65139
[33] Liao, M., Random motion of a rigid body, J. Theor. Probab., 10, 201-211 (1997) · Zbl 0876.60032 · doi:10.1023/A:1022654717555
[34] McLachlan, R. I.; Quispel, G. R.W.; Robidoux, N., Geometric integration using discrete gradients, R. Soc. Lond. Philos. Trans. Ser. A Math. Phys. Eng. Sci., 357, 1021-1045 (1999) · Zbl 0933.65143 · doi:10.1098/rsta.1999.0363
[35] Milstein, G. N.; Repin, Y. M.; Tretyakov, M. V., Symplectic integration of Hamiltonian systems with additive noise, SIAM J. Numer. Anal., 39, 2066-2088 (2002) · Zbl 1019.60056 · doi:10.1137/S0036142-901387440
[36] Milstein, G.N. and Tretyakov, M.V., Stochastic Numerics for Mathematical Physics, Scientific Computation, Springer-Verlag, Berlin, 2004. Available at . MR 2069903. · Zbl 1085.60004
[37] Miyatake, Y., An energy-preserving exponentially-fitted continuous stage Runge-Kutta method for Hamiltonian systems, BIT, 54, 777-799 (2014) · Zbl 1304.65263 · doi:10.1007/s10543-014-0474-4
[38] Miyatake, Y.; Butcher, J. C., A characterization of energy-preserving methods and the construction of parallel integrators for Hamiltonian systems, SIAM J. Numer. Anal., 54, 1993-2013 (2016) · Zbl 1342.65232 · doi:10.1137/15M1020861
[39] Quispel, G. R.W.; McLaren, D. I., A new class of energy-preserving numerical integration methods, J. Phys. A, 41 (2008) · Zbl 1132.65065
[40] Sanz-Serna, J.M. and Calvo, M.P., Numerical Hamiltonian problems, Applied Mathematics and Mathematical Computation Vol. 7, Chapman & Hall, London, 1994. MR 1270017. · Zbl 0816.65042
[41] Schurz, H., Analysis and discretization of semi-linear stochastic wave equations with cubic nonlinearity and additive space-time noise, Discr Contin. Dyn. Syst. Ser. S, 1, 353-363 (2008) · Zbl 1167.60014 · doi:10.3934/dcdss.2008.1.353
[42] Seesselberg, M.; Breuer, H. P.; Petruccione, F.; Honerkamp, J.; Mais, H., Simulation of one-dimensional noisy hamiltonian systems and their application to particle storage rings, Z. Phys., C62, 63-73 (1994)
[43] Senosiain, M. J.; Tocino, A., A review on numerical schemes for solving a linear stochastic oscillator, BIT, 55, 515-529 (2015) · Zbl 1322.65017 · doi:10.1007/s10543-014-0507-z
[44] Strømmen Melbø, A. H.; Higham, D. J., Numerical simulation of a linear stochastic oscillator with additive noise, Appl. Numer. Math., 51, 89-99 (2004) · Zbl 1060.65007 · doi:10.1016/j.apnum.2004.02.003
[45] Tasaka, N.; Satoh, S.; Hatanaka, T.; Yamada, K., Stochastic stabilization of rigid body motion of a spacecraft on SE(3), Int. J. Control., 1-8 (2021) · Zbl 1482.93685 · doi:10.1080/00207179.2019.1637544
[46] Vilmart, G., Weak second order multirevolution composition methods for highly oscillatory stochastic differential equations with additive or multiplicative noise, SIAM J. Sci. Comput., 36, A1770-A1796 (2014) · Zbl 1320.65019 · doi:10.1137/130935331
[47] Walter, J.; Gonzalez, O.; Maddocks, J. H., On the stochastic modeling of rigid body systems with application to polymer dynamics, Multiscale Model. Simul., 8, 1018-1053 (2010) · Zbl 1200.60048 · doi:10.1137/090765705
[48] Wang, B.; Wu, X., Functionally-fitted energy-preserving integrators for Poisson systems, J. Comput. Phys., 364, 137-152 (2018) · Zbl 1398.65337 · doi:10.1016/j.jcp.2018.03.015
[49] Wu, X.; Wang, B.; Shi, W., Efficient energy-preserving integrators for oscillatory Hamiltonian systems, J. Comput. Phys., 235, 587-605 (2013) · Zbl 1291.65363 · doi:10.1016/j.jcp.2012.10.015
[50] Zhou, W.; Zhang, J.; Hong, J.; Song, S., Stochastic symplectic Runge-Kutta methods for the strong approximation of Hamiltonian systems with additive noise, J. Comput. Appl. Math., 325, 134-148 (2017) · Zbl 1367.65015 · doi:10.1016/j.cam.2017.04.050
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