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Several schemes have been proposed to extend Quantum Key Distribution protocols aiming at improving their security or at providing new physical substrates for qubit implementation. We present a toolbox to jointly create, manipulate and…
OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper we introduce OpenML-Python, a client API for Python, opening up the OpenML…
Silicon photomultipliers (SiPMs) are currently the most prevalent photon detection technology in modern experiments in high-energy physics, astroparticle physics, neutrino physics, and dark matter searches. The high detection efficiency for…
Although Raman spectroscopy is widely used for the investigation of biomedical samples and has a high potential for use in clinical applications, it is not common in clinical routines. One of the factors that obstruct the integration of…
The use of Python is noticeably growing among the scientific community, and Astronomy is not an exception. The power of Python consists of being an extremely versatile high-level language, easy to program that combines both traditional…
gPhoton is a new database product and software package that enables analysis of GALEX ultraviolet data at the photon level. The project's stand-alone, pure-Python calibration pipeline reproduces the functionality of the original mission…
CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that…
Advancements in artificial intelligence (AI) have greatly benefited plant phenotyping and predictive modeling. However, unrealized opportunities exist in leveraging AI advancements in model parameter optimization for parameter fitting in…
We present PyMoosh, a Python-based simulation library designed to provide a comprehensive set of numerical tools allowing to compute essentially all optical characteristics of multilayered structures, ranging from reflectance and…
bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to build such models according to the HistFactory framework and…
In medical imaging, there is a growing interest to provide real-time images with good quality for large anatomical structures. To cope with this issue, we developed a library that allows to replace, for some specific clinical applications,…
FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages…
We present a standalone implementation of a data-deconvolution method based on singular value decomposition. The tool is written in python and packaged in the open-source yonder package. yonder receives as input two matrices, one for the…
We present Hyper-Py, a fully restructured and extended Python implementation of HYPER (HYbrid Photometry and Extraction Routine, Traficante et al. 2015). HYPER was originally implemented in IDL, aiming to deliver robust and reproducible…
Recent regulations, such as the European General Data Protection Regulation (GDPR), put stringent constraints on the handling of personal data. Privacy, like security, is a non-functional property, yet most software design tools are focused…
The scope of this paper is to demonstrate a fully working and compact photonic Physical Unclonable Function (PUF) device capable of operating in real life scenarios as an authentication mechanism and random number generator. For this…
High-dimensional entanglement offers a variety of advantages for both fundamental and applied applications in quantum information science. A central building block for such applications is a programmable processor of entangled states, which…
Many modern cheminformatics workflows derive datasets from ChEMBL, but few of these datasets are published with accompanying code for their generation. Consequently, their methodologies (e.g., selection, filtering, aggregation) are opaque,…
A large amount of data is produced every second from modern information systems such as mobile devices, the world wide web, Internet of Things, social media, etc. Analysis and mining of this massive data requires a lot of advanced tools and…
The goal of hyperparameter tuning (or hyperparameter optimization) is to optimize the hyperparameters to improve the performance of the machine or deep learning model. spotPython (``Sequential Parameter Optimization Toolbox in Python'') is…