PySlise : a Python package for solving Schrödinger equations

This is an introduction to a new Python package that is able to solve numerically the one and two-dimensional time independent Schrödinger equation. Accompanying this package there is a web based GUI. The main motivator of this research is modernizing and bringing together existing techniques and proven methods. Matslise is a very effective implementation of CP-methods for the one-dimensional Sturm-Liouville equation. But due to the numerous features, this implementation is not highly optimised for efficiency. For this reason we have reimplemented and optimised the algorithms of Matslise and Matscs in C++. This reimplementation became the computation engine for the Python package and the web based GUI (WebAssembly). The Python package is less feature-rich than the original Matslise and Matscs (only Schrödinger equation, no degenerate case detection...), but a lot more optimised. These optimisations include: very efficient eigenfunction calculations, smarter backward propagation, higher order method for Matscs, on request error calculation, using C++ with Eigen. On top of that there is a unified interface to communicate with Matslise, Matscs and the new code for the two-dimensional case

Determining the index of eigenvalues of an elliptic operator

Abstract: Throughout mathematical physics there are many problems dependent on, or consisting of determining eigenvalues of a linear elliptic operator on a given domain with Dirichlet boundary conditions. Some examples are the Schrödinger equation, the wave equation, the linear theory of elasticity, ... Many researchers have invested time and effort in stating and proving theorems about the spectrum of elliptic operators. In this talk we present a new tool to determine the number of eigenvalues less then a given value. Our theorem will be accompanied with examples and historic context

The fast and accurate computation of eigenvalues and eigenfunctions of time-independent one-dimensional Schrödinger equations

In this paper, we present the basic routines of the C++-program Matslise 3.0, an updated but yet restricted version of the matlab package Matslise 2.0. Matslise 3.0 currently allows the accurate, but in comparison to Matslise 2.0, faster computation of eigenvalues and eigenfunctions of one dimensional time-independent Schrödinger problems. The numerical examples show that speed up factors up to 20 (for the eigenvalues) and 200 (for the eigenfunctions) are obtained. These highly optimized routines will enable us, in the near future, to extend Matslise 3.0 to solve time-independent 2D and 3D as well as time-dependent 1D problems

Dolos : language‐agnostic plagiarism detection in source code

Background Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use plagiarism detection tools. Objectives We want to lower the barrier for teachers to detect plagiarism by introducing a new source code plagiarism detection tool (Dolos) that is powered by state-of-the art similarity detection algorithms, offers interactive visualizations, and uses generic parser models to support a broad range of programming languages. Methods Dolos is compared with state-of-the-art plagiarism detection tools in a benchmark based on a standardized dataset. We describe our experience with integrating Dolos in a programming course with a strong focus on online learning and the impact of transitioning to remote assessment during the COVID-19 pandemic. Results and Conclusions Dolos outperforms other plagiarism detection tools in detecting potential cases of plagiarism and is a valuable tool for preventing and detecting plagiarism in online learning environments. It is available under the permissive MIT open-source license at https://dolos.ugent.be. Implications Dolos lowers barriers for teachers to discover, prove and prevent plagiarism in programming courses. This helps to enable a shift towards open and online learning and assessment environments, and opens up interesting avenues for more effective learning and better assessment

ModAu: Modernized Auscultation

Abstract: This paper presents a novel wireless digital stetho-scope design that integrates multiple sensing modalities into a compact form factor. The proposed stethoscope aims to enhance the auscultation data quality by capturing high-quality audio and precise vibration data for improved diagnosis and monitoring of respiratory and cardiac conditions. To enable wireless connectivity, the auscultation device incorporates the latest Bluetooth technology, enabling realtime transmission of auscultation data to a compatible device, such as a smartphone or computer. This allows future healthcare professionals to visualize and analyze the captured data using dedicated software, providing enhanced visualization tools, signal processing algorithms, and machine learning techniques for accurate interpretation and diagnosis. The compact form factor and low-cost design of the stethoscope, makes it suitable for various medical applications, including remote healthcare and long term monitoring

Dolos

Dolos is a source code plagiarism detection tool designed to be as effective as possible to use.If you use this software in your research, please cite it as below