Related papers: Cait: analysis toolkit for cryogenic particle dete…
As a result of recent advancements in generative AI, the field of data science is prone to various changes. The way practitioners construct their data science workflows is now irreversibly shaped by recent advancements, particularly by…
Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe $\textit{causal-learn}$, an open-source Python library for causal discovery. This library…
We introduce NetworKit, an open-source software package for analyzing the structure of large complex networks. Appropriate algorithmic solutions are required to handle increasingly common large graph data sets containing up to billions of…
A Geant4-based Python/C++ simulation and coding framework, which has been developed and used in order to aid the R&D efforts for thermal neutron detectors at neutron scattering facilities, is described. Built upon configurable geometry and…
Constraint-based causal discovery relies on numerous conditional independence tests (CITs), but its practical applicability is severely constrained by the prohibitive computational cost, especially as CITs themselves have high time…
Be it for a malicious or legitimate purpose, packing, a transformation that consists in applying various operations like compression or encryption to a binary file, i.e. for making reverse engineering harder or obfuscating code, is widely…
We present KITE, a general purpose open-source tight-binding software for accurate real-space simulations of electronic structure and quantum transport properties of large-scale molecular and condensed systems with tens of billions of…
Weakly Interacting Massive Particles (WIMPs) are candidates for non-baryonic Dark Matter. WIMPs are supposed to interact with baryonic matter via scattering off nuclei producing a nuclear recoil with energies up to a few 10 keV with a very…
An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including temperature,…
Predictive systems, in particular machine learning algorithms, can take important, and sometimes legally binding, decisions about our everyday life. In most cases, however, these systems and decisions are neither regulated nor certified.…
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical…
Broadly defined as the Internet of Things (IoT), the growth of commodity devices that integrate physical processes with digital connectivity has had profound effects on society--smart homes, personal monitoring devices, enhanced…
The testing and quality assurance of cryogenic superconducting detectors is a time- and labor-intensive process. As experiments deploy increasingly larger arrays of detectors, new methods are needed for performing this testing quickly.…
Particle tracking is commonly used to study time-dependent behavior in many different types of physical and chemical systems involving constituents that span many length scales, including atoms, molecules, nanoparticles, granular particles,…
Together with the recent CLIC detector model CLICdet a new software suite was introduced for the simulation and reconstruction of events in this detector. This note gives a brief introduction to CLICdet and describes the CLIC experimental…
The most common method to auto-grade a student's submission in a CS1 or a CS2 course is to run it against a pre-defined test suite and compare the results against reference results. However, this technique cannot be used if the correctness…
Cryo-electron tomography (cryo-ET) enables in situ visualization of macromolecular structures, where subtomogram analysis tasks such as classification, alignment, and averaging are critical for structural determination. However, effective…
Repeatable and reliable site-specific preparation of specimens for atom probe tomography (APT) at cryogenic temperatures has proven challenging. A generalized workflow is required for cryogenic-specimen preparation including lift-out via…
Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) and other rare-event physics searches, like dark matter detection, have been especially furthered by increasing sensitivity to low-energy particle interactions. Experiments using…
Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might have compromised an enterprise network for a long time without being discovered. To have a more effective analysis, CTI open standards have…