Related papers: Cait: analysis toolkit for cryogenic particle dete…
Many popular Python libraries use C-extensions for performance-critical operations allowing users to combine the best of the two worlds: The simplicity and versatility of Python and the performance of C. A drawback of this approach is that…
In this work, we describe and demonstrate a novel Technology Computer Aided Design (TCAD) driven methodology to re-center room-temperature Process Design Kits (PDKs) for cryogenic operation using a limited set of experimental measurements.…
Time-to-event (survival) analysis models the time until a pre-specified event occurs. When time is measured in discrete units or rounded into intervals, standard continuous-time models can yield biased estimators. In addition, the event of…
We present SAInT, a Python-based tool for visually exploring and understanding the behavior of Machine Learning (ML) models through integrated local and global sensitivity analysis. Our system supports Human-in-the-Loop (HITL) workflows by…
The usage of the high-level scripting language Python has enabled new mechanisms for data interrogation, discovery and visualization of scientific data. We present yt, an open source, community-developed astrophysical analysis and…
Computer simulation has become one of the most important tools in scientific research in many disciplines. Benefiting from the dynamical trajectories regulated by versatile interatomic interactions, various material properties can be…
A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project is aimed to support the development of machine learning…
Background: As traditional coding tasks in education become increasingly vulnerable to the use of Generative AI, there is a critical need for authentic, project-based assessments that evaluate students' scientific inquiry. To address this…
PypeIt is a Python package for semi-automated reduction of astronomical, spectroscopic data. Its algorithms build on decades-long development of previous data reduction pipelines by the developers (Bernstein, Burles, & Prochaska, 2015;…
Efficient discovery of electrocatalysts for electrochemical energy conversion reactions is of utmost importance to combat climate change. With the example of the oxygen reduction reaction we show that by utilising a data-driven discovery…
A new, modular toolkit for creating simulations of 2D X-ray pixel detectors, X-CSIT (X-ray Camera SImulation Toolkit), is being developed. The toolkit uses three sequential simulations of detector processes which model photon interactions,…
While nonclassical light sources are fundamental to quantum communication and computing, solid-state platforms like color centers and quantum dots require cryogenic temperatures to reach the performance levels necessary for practical…
Coherent scattering is a flavor-blind, high-rate, as yet undetected neutrino interaction predicted by the Standard Model. We propose to use a compact (kg-scale), two-phase (liquid-gas) argon ionization detector to measure coherent neutrino…
$\texttt{gCastle}$ is an end-to-end Python toolbox for causal structure learning. It provides functionalities of generating data from either simulator or real-world dataset, learning causal structure from the data, and evaluating the…
We introduce SciWING, an open-source software toolkit which provides access to pre-trained models for scientific document processing tasks, inclusive of citation string parsing and logical structure recovery. SciWING enables researchers to…
While machine learning offers diverse techniques suitable for exploring various medical research questions, a cohesive synergistic framework can facilitate the integration and understanding of new approaches within unified model development…
Our work explores the utilization of deep learning, specifically leveraging the CodeBERT model, to enhance code security testing for Python applications by detecting SQL injection vulnerabilities. Unlike traditional security testing methods…
QC Lab is an open-source Python package for QC dynamics simulations aimed to promote the development of QC algorithms, and their application to a wide variety of relevant model problems. It follows a modular design that facilitates…
Law-enforcement investigations aimed at preventing attacks by violent extremists have become increasingly important for public safety. The problem is exacerbated by the massive data volumes that need to be scanned to identify complex…
Cryogenic scintillating calorimeters are ultrasensitive particle detectors for rare event searches, particularly for the search for dark matter and the measurement of neutrino properties. These detectors are made from scintillating target…