This work deals with the simulation of a two‐dimensional ideal lattice having simple tetragonal geometry. The harmonic character of the oscillators give rise to a system of second‐order linear differential equations, which can be recast into matrix form. The explicit solutions which govern the dynamics of this system can be expressed in terms of matrix trigonometric functions. For the derivation we employ the Lagrangian formalism to determine the correct solutions, which extremize the underlying action of the system. In the numerical evaluation we develop diverse state‐of‐the‐art algorithms which efficiently tackle equations with matrix sine and cosine functions. For this purpose, we introduce two special series related to trigonometric functions. They provide approximate solutions of the system through a suitable combination. For the final computation an algorithm based on Taylor expansion with forward and backward error analysis for computing those series had to be devised. We also implement several MATLAB programs which simulate and visualize the two‐dimensional lattice and check its energy conservation.
Category: Matrix functions
Computing Matrix Trigonometric Functions with GPUs through Matlab, P. Alonso, J. Peinado, J. Ibañez, J. Sastre, E. Defez, The Journal of Supercomputing, 75, 2019, 1227–1240 , doi: https://doi.org/10.1007/s11227-018-2354-1, Preprint
On the inverse of the Caputo matrix exponential. (E. Defez, M. Tung, B. Chen-Charpentier and J.M. Alonso) Mathematics (MDPI, ISSN 2227-7390). Vol. 7 (12), 2019, pp. 1137. doi:10.3390/math7121137
New matrix series expansions for the matrix cosine approximations, E. Defez, J. Ibáñez, P. Alonso, J.M. Alonso J. Peinado, and P. Alonso-Jordá, in the International Conference Mathematical Modelling in Engineering and Human Behaviour 2019, Mathematical Modelling Conference Series at the Institute for Multidisciplinary Mathematics, Universitat Politècnica de València, July, 10-12, 2019, Valencia (Spain).
Computing matrix functions by matrix Bernouilli Series, E. Defez, J. Ibañez, J. Peinado, P. Alonso-Jordá and J.M. Alonso, 19th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2019, June-July 2019, Rota (Cadiz)-SPAIN.
Fast Taylor polynomial evaluation for the matrix cosine, J. Sastre, J. Ibañez, P. Alonso, J. Peinado and E. Defez, Journal of Computational and Applied Mathematics, vol. 354 pp. 641-650, July 2019 https://doi.org/10.1016/j.cam.2018.12.041, Preprint Matlab code cosmpol.m
Fast Taylor polynomial evaluation for the matrix cosine, J. Sastre, J. Ibañez, P. Alonso, J. Peinado and E. Defez, 18th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2018, July 2018, Rota (Cadiz)-SPAIN.
In this work we introduce a new method to compute the matrix cosine. It is based on recent new matrix polynomial evaluation methods for the Taylor approximation and forward and backward error analysis. The matrix polynomial evaluation methods allow to evaluate the Taylor polynomial approximation of the cosine function more efficiently than using Paterson-Stockmeyer method. A MATLAB implementation of the new algorithm is provided, giving better efficiency and accuracy than state-of-the-art algorithms.
Boosting the computation of the matrix exponential, J. Sastre, J. Ibáñez, E. Defez, Appl. Math. Comput. in press, 2018, doi:10.1016/j.amc.2018.08.017, Preprint, Matlab code expmpol.m.
This paper presents new Taylor algorithms for the computation of the matrix exponential based on recent new matrix polynomial evaluation methods. Those methods are more efficient than the well known Paterson–Stockmeyer method. The cost of the proposed algorithms is reduced with respect to previous algorithms based on Taylor approximations. Tests have been performed to compare the MATLAB implementations of the new algorithms to a state-of-the-art Padé algorithm for the computation of the matrix exponential, providing higher accuracy and cost performances.
First article with an application of the new matrix polynomial evaluation methods from J. Sastre, Efficient evaluation of matrix polynomials, Linear Algebra Appl. 539, (2018) 229-250. With the new matrix polynomial evaluation methods, Taylor approximation methods are more efficient than Padé approximant based methods.
- Two algorithms for computing the matrix cosine function, Jorge Sastre, Javier Ibáñez, Pedro Alonso, Jesús Peinado, Emilio Defez. Applied Mathematics and Computation, Volume 312, pp. 66-77, November 2017, Preprint. Matlab code cosmtay.m.