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Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series analytics is therefore crucial to unlocking the…
We describe the application of data mining algorithms to research problems in astronomy. We posit that data mining has always been fundamental to astronomical research, since data mining is the basis of evidence-based discovery, including…
Sensitivity analysis is a cornerstone of climate science, essential for understanding phenomena ranging from storm intensity to long-term climate feedbacks. However, computing these sensitivities using traditional physical models is often…
Time is an important dimension of brain function, but little is still known about the underlying cognitive principles and neurobiological mechanisms. The field of timing and time perception has witnessed rapid growth and multidisciplinary…
The review is conceived to help the reader to interpret present geoneutrino results in the framework of Earth's energetics and composition. Starting from the comprehension of antineutrino production, propagation, and detection, the status…
An essential companion to the development and advancement of the field of Particle Physics is a strong program in physics education at all levels, that can attract entry level students across the full demographic spectrum and provide them…
In the present academic landscape, the process of collecting data is slow, and the lax infrastructures for data collaborations lead to significant delays in coming up with and disseminating conclusive findings. Therefore, there is an…
High-energy physics is primarily concerned with uncovering the laws and principles that govern nature at the fundamental level. Research in this field usually relies on probing the boundaries of established physics, an undertaking typically…
In this study, by attempting to eliminate the disadvantageous complexity of the existing particle generators, we present a discrete probabilistic scheme adapted for the discrete energy spectra in the GEANT4 simulations. In our multi-binned…
Nature has inspired various ground-breaking technological developments in applications ranging from robotics to aerospace engineering and the manufacturing of medical devices. However, accessing the information captured in scientific…
Astrophysical studies require a knowledge of very accurate positions, motions and distances of stars. A brief overview is given of the significance and development of astrometry by ESA's two astrometric satellites, Hipparcos and Gaia,…
Measuring science is based on comparing articles to similar others. However, keyword-based groups of thematically similar articles are dominantly small. These small sizes keep the statistical errors of comparisons high. With the growing…
In the last decade, the multi-sensory approach to data analysis has gained relevance. The possibility of including people with vision difficulties in the field of education and the dissemination of science is part of it. However, in the…
This paper represents the vision of the members of the Fermilab Scientific Computing Division's Computational Physics Department (SCD-CPD) on the status and the evolution of various HEP software tools such as the Geant4 detector simulation…
The rapid growth of scientific literature calls for automated methods to assess and predict research impact. Prior work has largely focused on citation-based metrics, leaving limited evaluation of models' capability to reason about other…
Data and Science has stood out in the generation of results, whether in the projects of the scientific domain or business domain. CERN Project, Scientific Institutes, companies like Walmart, Google, Apple, among others, need data to present…
The evaluation of mathematical results plays a central role in assessing researchers' contributions and shaping the direction of the field. Currently, such evaluations rely primarily on human judgment, whether through journal peer review or…
The search for new comparably light (well below the electroweak scale) feebly interacting particles is an exciting possibility to explain some mysterious phenomena in physics, among them the origin of Dark Matter. The sensitivity study…
Scientific progress depends on sequences of enabling contributions, yet existing AI4Science benchmarks largely focus on citation prediction, literature retrieval, or idea generation rather than the dependencies that make progress possible.…
The anticipated high sensitivity and the science goals of the next generation X-ray space missions, like the International X-ray Observatory or Simbol-X, rely on a low instrumental background, which in turn requires optimized shielding…