Superconducting quantum devices are at the heart of modern quantum technology, where they are used both as fundamental building blocks in larger quantum devices and circuits, but also as sensors in quantum metrology. Topological superconductivity enables quantum operations that are robust against disorder and noise, which are currently limiting factors in modern quantum technology. At the same time, these superconducting devices are often realized on a mesoscopic scale, bridging the microscopic and macroscopic regimes. However, our fundamental understanding of how superconductivity behaves on the mesoscopic scale is far from complete, partly because of the technical challenges with simulating such systems with full microscopic theory. Quasicrystals provide a fascinating platform to study the interplay between symmetry, ordered states and topology. Specifically, these systems lack periodicity but are still long-range ordered through discrete scale invariance. While naturally formed quasicrystals are rare, they can be fabricated with atomic precision in real time. Furthermore, artificial quasicrystals can also be created in a wide range of settings, from quantum optics such as photonic lattices and waveguides, adatom and moelcular deposition, to quantum dots and nanowire setups. We will identify real-world applications of these quasiperiodic systems, specifically for quantum technology and quantum information processing. Recently, we identified that the quasiperiodic systems can be utilized to construct a topological pump that requires minimal control to reliably transfer quantum states, both theoretically (https://journals.aps.org/prb/abstract/10.1103/8zys-w2v4) and experimentally (https://arxiv.org/abs/2605.13116). We will continue this line of research, investigating experimental feasibility in other systems and how to improve the pump. We follow several independent approaches; 1. microscopic tight-binding simulations, 2. continuum calculations, 3. quasiclassical simulations. For the tight-binding calculations, we either rely on smaller Python codes through matrix diagonalization, or parallelized matrix-vector multiplications using the open-source software TBTK (http://www.second-quantization.com and https://github.com/dafer45/TBTK). For the continuum calculations, we either rely on smaller Python codes, or the open-source software MCTDH-X (https://iopscience.iop.org/article/10.1088/2058-9565/ab788b). For the quasiclassical simulations, we have developed the open-source framework SuperConga (https://gitlab.com/superconga/superconga), using quasiclassical theory of superconductivity [Applied Physics Reviews 10, 011317 (2023); https://doi.org/10.1063/5.0100324], which can efficiently model mesoscopic superconductivity. SuperConga is the state-of-the art, combining a highly efficient implementation that runs on GPUs, with a user-friendly and well-documented interface. The codes run in parallel, either on CPUs or GPUs, depending on the specific problem and code. We already have many years of experience using CPUs and GPUs in both small and medium allocations at PDC, C3SE, NSC, UPPMAX, and LUMI. In this round, we aim to use Dardel at PDC as it provides a good combination of CPU and GPU nodes, that will enable us to investigate unconventional topological superconductors, and how the unique properties of quasiperiodic systems can be used to create efficient topological pumps for quantum information processing.