Approximation of Wave Packets on the Real Line
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jats:titleAbstract</jats:title>jats:pIn this paper we compare three different orthogonal systems in jats:inline-formulajats:alternativesjats:tex-math$$\textrm{L}_2({\mathbb {R}})$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> mml:mrow mml:msub mml:mtextL</mml:mtext> mml:mn2</mml:mn> </mml:msub> mml:mrow mml:mo(</mml:mo> mml:miR</mml:mi> mml:mo)</mml:mo> </mml:mrow> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> which can be used in the construction of a spectral method for solving the semi-classically scaled time dependent Schrödinger equation on the real line, specifically, stretched Fourier functions, Hermite functions and Malmquist–Takenaka functions. All three have banded skew-Hermitian differentiation matrices, which greatly simplifies their implementation in a spectral method, while ensuring that the numerical solution is unitary—this is essential in order to respect the Born interpretation in quantum mechanics and, as a byproduct, ensures numerical stability with respect to the jats:inline-formulajats:alternativesjats:tex-math$$\textrm{L}_2({\mathbb {R}})$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> mml:mrow mml:msub mml:mtextL</mml:mtext> mml:mn2</mml:mn> </mml:msub> mml:mrow mml:mo(</mml:mo> mml:miR</mml:mi> mml:mo)</mml:mo> </mml:mrow> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> norm. We derive asymptotic approximations of the coefficients for a wave packet in each of these bases, which are extremely accurate in the high frequency regime. We show that the Malmquist–Takenaka basis is superior, in a practical sense, to the more commonly used Hermite functions and stretched Fourier expansions for approximating wave packets.</jats:p>
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Acknowledgements: KL wishes to acknowledge UK Engineering and Physical Sciences Research Council (EPSRC) for the grant EP/L016516/1 for the University of Cambridge Centre for Doctoral Training, the Cambridge Centre for Analysis, which supported the research and writing of this paper. KL is also grateful to the Department of Computer Science, KU Leuven for their hospitality during a visit where some of the research for this paper was done. MW thanks FWO Research Foundation Flanders for the postdoctoral research fellowship he enjoyed while some of the research for this paper was done. MW also thanks the Polish National Science Centre (SONATA-BIS-9), project no. 2019/34/E/ST1/00390, for the funding that supported the research. This work is partially supported by the Simons Foundation Award No 663281 granted to the Institute of Mathematics of the Polish Academy of Sciences for the years 2021–2023. The authors would like to thank Bruno Salvy and André Weideman for helpful correspondence on the steepest descent method, and are especially grateful to Nico Temme for the helpful discussions on Hermite functions and the method of steepest descent which helped simplify the section on the Malmquist–Takenaka functions.
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1432-0940