301,496 research outputs found
Pseudo-Exponential-Type Solutions of Wave Equations Depending on Several Variables
Using matrix identities, we construct explicit pseudo-exponential-type
solutions of linear Dirac, Loewner and Schr\"odinger equations depending on two
variables and of nonlinear wave equations depending on three variables
Numerical solutions of random mean square Fisher-KPP models with advection
[EN] This paper deals with the construction of numerical stable solutions of random mean square Fisher-Kolmogorov-Petrosky-Piskunov (Fisher-KPP) models with advection. The construction of the numerical scheme is performed in two stages. Firstly, a semidiscretization technique transforms the original continuous problem into a nonlinear inhomogeneous system of random differential equations. Then, by extending to the random framework, the ideas of the exponential
time differencing method, a full vector discretization of the problem
addresses to a random vector difference scheme. A sample approach of the random vector difference scheme, the use of properties of Metzler matrices and the logarithmic norm allow the proof of stability of the numerical solutions in the mean square sense. In spite of the computational complexity, the results are illustrated by comparing the results with a test problem where the exact solution is known.Ministerio de Economia y Competitividad, Grant/Award Number: MTM2017-89664-PCasabán Bartual, MC.; Company Rossi, R.; Jódar Sánchez, LA. (2020). Numerical solutions of random mean square Fisher-KPP models with advection. Mathematical Methods in the Applied Sciences. 43(14):8015-8031. https://doi.org/10.1002/mma.5942S801580314314FISHER, R. A. (1937). THE WAVE OF ADVANCE OF ADVANTAGEOUS GENES. Annals of Eugenics, 7(4), 355-369. doi:10.1111/j.1469-1809.1937.tb02153.xBengfort, M., Malchow, H., & Hilker, F. M. (2016). 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Seasonal Invasion Dynamics in a Spatially Heterogeneous River with Fluctuating Flows. Bulletin of Mathematical Biology, 76(7), 1522-1565. doi:10.1007/s11538-014-9957-3Faou, E. (2009). Analysis of splitting methods for reaction-diffusion problems using stochastic calculus. Mathematics of Computation, 78(267), 1467-1483. doi:10.1090/s0025-5718-08-02185-6Doering, C. R., Mueller, C., & Smereka, P. (2003). Interacting particles, the stochastic Fisher–Kolmogorov–Petrovsky–Piscounov equation, and duality. Physica A: Statistical Mechanics and its Applications, 325(1-2), 243-259. doi:10.1016/s0378-4371(03)00203-6Siekmann, I., Bengfort, M., & Malchow, H. (2017). Coexistence of competitors mediated by nonlinear noise. The European Physical Journal Special Topics, 226(9), 2157-2170. doi:10.1140/epjst/e2017-70038-6McKean, H. P. (1975). Application of brownian motion to the equation of kolmogorov-petrovskii-piskunov. Communications on Pure and Applied Mathematics, 28(3), 323-331. doi:10.1002/cpa.3160280302Berestycki, H., & Nadin, G. (2012). Spreading speeds for one-dimensional monostable reaction-diffusion equations. Journal of Mathematical Physics, 53(11), 115619. doi:10.1063/1.4764932Cortés, J. C., Jódar, L., Villafuerte, L., & Villanueva, R. J. (2007). Computing mean square approximations of random diffusion models with source term. Mathematics and Computers in Simulation, 76(1-3), 44-48. doi:10.1016/j.matcom.2007.01.020Villafuerte, L., Braumann, C. A., Cortés, J.-C., & Jódar, L. (2010). Random differential operational calculus: Theory and applications. Computers & Mathematics with Applications, 59(1), 115-125. doi:10.1016/j.camwa.2009.08.061Casabán, M.-C., Cortés, J.-C., & Jódar, L. (2016). Solving linear and quadratic random matrix differential equations: A mean square approach. Applied Mathematical Modelling, 40(21-22), 9362-9377. doi:10.1016/j.apm.2016.06.017Sarmin, E. N., & Chudov, L. A. (1963). On the stability of the numerical integration of systems of ordinary differential equations arising in the use of the straight line method. USSR Computational Mathematics and Mathematical Physics, 3(6), 1537-1543. doi:10.1016/0041-5553(63)90256-8Sanz-Serna, J. M., & Verwer, J. G. (1989). Convergence analysis of one-step schemes in the method of lines. Applied Mathematics and Computation, 31, 183-196. doi:10.1016/0096-3003(89)90118-5Calvo, M. P., de Frutos, J., & Novo, J. (2001). Linearly implicit Runge–Kutta methods for advection–reaction–diffusion equations. Applied Numerical Mathematics, 37(4), 535-549. doi:10.1016/s0168-9274(00)00061-1Cox, S. M., & Matthews, P. C. (2002). Exponential Time Differencing for Stiff Systems. Journal of Computational Physics, 176(2), 430-455. doi:10.1006/jcph.2002.6995De la Hoz, F., & Vadillo, F. (2016). Numerical simulations of time-dependent partial differential equations. 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Nonlinear theory for coalescing characteristics in multiphase Whitham modulation theory
The multiphase Whitham modulation equations with phases have
characteristics which may be of hyperbolic or elliptic type. In this paper a
nonlinear theory is developed for coalescence, where two characteristics change
from hyperbolic to elliptic via collision. Firstly, a linear theory develops
the structure of colliding characteristics involving the topological sign of
characteristics and multiple Jordan chains, and secondly a nonlinear modulation
theory is developed for transitions. The nonlinear theory shows that coalescing
characteristics morph the Whitham equations into an asymptotically valid
geometric form of the two-way Boussinesq equation. That is, coalescing
characteristics generate dispersion, nonlinearity and complex wave fields. For
illustration, the theory is applied to coalescing characteristics associated
with the modulation of two-phase travelling-wave solutions of coupled nonlinear
Schr\"odinger equations, highlighting how collisions can be identified and the
relevant dispersive dynamics constructed.Comment: 40 pages, 2 figure
Grassmannian flows and applications to nonlinear partial differential equations
We show how solutions to a large class of partial differential equations with
nonlocal Riccati-type nonlinearities can be generated from the corresponding
linearized equations, from arbitrary initial data. It is well known that
evolutionary matrix Riccati equations can be generated by projecting linear
evolutionary flows on a Stiefel manifold onto a coordinate chart of the
underlying Grassmann manifold. Our method relies on extending this idea to the
infinite dimensional case. The key is an integral equation analogous to the
Marchenko equation in integrable systems, that represents the coodinate chart
map. We show explicitly how to generate such solutions to scalar partial
differential equations of arbitrary order with nonlocal quadratic
nonlinearities using our approach. We provide numerical simulations that
demonstrate the generation of solutions to
Fisher--Kolmogorov--Petrovskii--Piskunov equations with nonlocal
nonlinearities. We also indicate how the method might extend to more general
classes of nonlinear partial differential systems.Comment: 26 pages, 2 figure
The Trajectory-Coherent Approximation and the System of Moments for the Hartree-Type Equation
The general construction of quasi-classically concentrated solutions to the
Hartree-type equation, based on the complex WKB-Maslov method, is presented.
The formal solutions of the Cauchy problem for this equation, asymptotic in
small parameter \h (\h\to0), are constructed with a power accuracy of
O(\h^{N/2}), where N is any natural number. In constructing the
quasi-classically concentrated solutions, a set of Hamilton-Ehrenfest equations
(equations for middle or centered moments) is essentially used. The nonlinear
superposition principle has been formulated for the class of quasi-classically
concentrated solutions of the Hartree-type equations. The results obtained are
exemplified by the one-dimensional equation Hartree-type with a Gaussian
potential.Comments: 6 pages, 4 figures, LaTeX Report no: Subj-class:
Accelerator PhysicsComment: 36 pages, LaTeX-2
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