PyLlama: A stable and versatile Python toolkit for the electromagnetic modelling of multilayered anisotropic media

PyLlama is a handy Python toolkit to compute the electromagnetic reflection and transmission properties of arbitrary multilayered linear media, including case anisotropy. Relying on 4×4-matrix formalism, implements not only transfer matrix method, that most popular choice in existing codes, but also scattering which numerically stable all situations (e.g., thick, highly birefringent cholesteric structures at grazing incident angles). designed suit practical needs by allowing user create, edit assemble layers or domains with great ease. In this article, we present theory underlying methods outline architecture main features PyLlama. Finally, validate code comparison available analytical solutions demonstrate its versatility numerical stability modelling media varying complexity. A detailed documentation tutorial are provided separate manual. Applications range from design optical components polaritonic effects polar crystals, study structurally coloured materials living world. Program Title: – Toolkit for Electromagnetic Modelling Multilayered Anisotropic Media CPC Library link program files: https://doi.org/10.17632/dzw8x5vyrv.1 Developer's repository link: https://github.com/VignoliniLab/PyLlama Licensing provisions: GPLv3 Programming language: Supplementary material: User guide tutorials https://pyllama.readthedocs.io/ Nature problem: Computation coefficients composed an number layers, possibly mixing isotropic anisotropic, absorbing non-absorbing materials, linearly circularly polarised light. Solution method: Implementation both method (faster) (more robust) relying 4×4 formalism. Additional comments restrictions unusual features: Integration physical model handle structures, blueprint integration user-created custom systems, hassle-free export spectra non-programmers even complex and/or systems. External routines include: Numpy [1], Scipy [2], as well Sympy [3] (optional). Numpy, https://numpy.org/. Scipy, https://www.scipy.org/. Sympy, https://www.sympy.org/.