Astroparticle projects at the Eastern Colombia region: facilities and instrumentation

We describe some projects and initiatives for astroparticles physics from basic and application level. Three specialized instruments have been design, built and put into operation for the study of various characteristics and phenomena of cosmic rays. One of detector based on Cherenkov effect consists of three Water Cherenkov Detectors calibrated spatially and temporally, that allow the characterization of secondary cascades of cosmic ray particles. These devices allow to study the original composition and parameters of primary cosmic rays from the secondary particles detected on the ground. A second type of detectors based on scintillation effect are used for specific applications in the characterization of materials and mountainous structures. These detectors allow the counting of incident secondaries particles (muons mainly) while determining their arrival direction. Studing their attenuation in the material medium we can infer composition and density profiles

Mejora eficiente para la estimación de la energía libre superficial del ligante asfáltico mediante herramientas de Machine Learning

The Surface Free Energy (SFE) of a material is defined as the energy needed to create a new surface unit under vacuum conditions. This property is directly related to the resistance to fracture and recovery of material and the ability to create strong adhesion with other materials. This value can be used as a complementary parameter for the selection and optimal combination of materials for asphalt mixtures, as well as in the micromechanical modeling of fracture and recovery processes of said mixtures. This document describes the results of the implementation of the use of machine learning and Random Forest prediction techniques for the estimation of surface free energy based on data from previous studies. The experimental samples were twenty-three asphalt binders used in a Strategic Highway Research Program (SHRP). A decrease of 54% and 82% in the mean absolute error (MAE) and the mean square error (MSE), respectively was found for the new model built. While the model fits better with a 12% improvement, according to the adjusted determination coefficient, the accuracy and the score of the model also increases notably in 2% and 55%, respectively.La energía libre de superficie de un material se define como la energía necesaria para crear una nueva unidad de superficie en condiciones de vacío. Esta propiedad está directamente relacionada con la resistencia a la fractura y recuperación de un material y con la capacidad de crear una fuerte adhesión con otros materiales. Este valor puede ser utilizado como parámetro complementario para la selección y combinación óptima de materiales para mezclas asfálticas, así como en el modelado micromecánico de procesos de fractura y recuperación de dichas mezclas. Este documento describe los resultados de la implementación del uso del aprendizaje automático y las técnicas de predicción de bosque aleatorio para la estimación de la energía libre superficial basada en datos de estudios anteriores. Las muestras experimentales fueron veintitrés ligantes de asfalto usados en un Programa de Investigación Estratégica de Carreteras (SHRP). Podemos destacar una disminución de 54% y 82% en el error medio absoluto (MAE) y el error cuadrático medio (MSE), respectivamente. Si bien el modelo encaja mejor con una mejora del 12%, según el coeficiente de determinación ajustado, la precisión y la puntuación del modelo también aumentan notablemente en un 2% y 55% respectivamente

Astroparticle projects at the Eastern Colombia region: facilities and instrumentation

We describe some projects and initiatives for astroparticles physics from basic and application level. Three specialized instruments have been design, built and put into operation for the study of various characteristics and phenomena of cosmic rays. One of detector based on Cherenkov effect consists of three Water Cherenkov Detectors calibrated spatially and temporally, that allow the characterization of secondary cascades of cosmic ray particles. These devices allow to study the original composition and parameters of primary cosmic rays from the secondary particles detected on the ground. A second type of detectors based on scintillation effect are used for specific applications in the characterization of materials and mountainous structures. These detectors allow the counting of incident secondaries particles (muons mainly) while determining their arrival direction. Studing their attenuation in the material medium we can infer composition and density profiles

Dataset for Sun dynamics from topological features

The present study presents an extensive dataset meticulously curated from solar images sourced from the Solar and Heliospheric Observatory (SOHO), encompassing a range of spectral bands. This collaborative effort spans multiple disciplines and culminates in a robust and automated methodology that traverses the entire spectrum from solar imaging to the computation of spectral parameters and relevant characteristics. The significance of this undertaking lies in the profound insights yielded by the dataset. Encompassing diverse spectral bands and employing topological features, the dataset captures the multifaceted dynamics of solar activity, fostering interdisciplinary correlations and analyses with other solar phenomena. Consequently, the data's intrinsic value is greatly enhanced, affording researchers in solar physics, space climatology, and related fields the means to unravel intricate processes. To achieve this, an open-source Python library script has been developed, consolidating three pivotal stages: image acquisition, image processing, and parameter calculation. Originally conceived as discrete modules, these steps have been unified into a single script, streamlining the entire process. Applying this script to various solar image types has generated multiple datasets, subsequently synthesized into a comprehensive compilation through a data mining procedures. During the image processing phase, conventional libraries like OpenCV and Python's image analysis tools were harnessed to refine images for analysis. In contrast, image acquisition utilized established URL libraries in Python, facilitating direct access to original SOHO repository images and eliminating the need for local storage. The computation of spectral parameters involved a fusion of standard Python libraries and tailored algorithms for specific attributes. This approach ensures precise computation of a diverse array of attributes crucial for comprehensive analysis of solar images

SunspotCalc: Una aplicación basada en Web y Python para calcular la rotación diferencial del sol y su fotosfera

En este manuscrito presentamos una aplicación web con soporte en lenguaje de programación PYTHON, REACTJS y JAVASCRIPT, libre y abierta, para el desarrollo de una actividad de enseñanza-aprendizaje de la astronomía, específicamente para el cálculo de la rotación diferencial del Sol para estudiantes y publicó en general en edad escolar entre 10 y 18 años. El propósito fundamental es la de difundir el conocimiento del Sol y algunas de sus propiedades. La aplicación web es autocontenida y con suficiente guía y ayuda para que cualquiera pueda usarla, además de su dinamismo y diseño innovador, pretende presentar estrategias agradables para la enseñanza y aprendizaje de la ciencia en torno al Sol.In this manuscript we present a web application with support in PYTHON, REACTJS and JAVASCRIPT programming language, free and open, for the development of a teaching-learning activity of astronomy, specifically for the calculation of the differential rotation of the Sun for students and general public in school age between 10 and 18 years old. The main purpose is to spread the knowledge of the Sun and some of its properties. The web application is self-contained and with enough guidance and help for anyone to use it, in addition to its dynamism and innovative design, it aims to present pleasant strategies for teaching and learning science around the Sun

The DESI Bright Galaxy Survey: Final Target Selection, Design, and Validation

Over the next 5 yr, the Dark Energy Spectroscopic Instrument (DESI) will use 10 spectrographs with 5000 fibers on the 4 m Mayall Telescope at Kitt Peak National Observatory to conduct the first Stage IV dark energy galaxy survey. At z 10 million galaxies spanning 14,000 deg2 . In this work, we present and validate the final BGS target selection and survey design. From the Legacy Surveys, BGS will target an r 80% fiber assignment efficiency. Finally, BGS Bright and BGS Faint will achieve >95% redshift success over any observing condition. BGS meets the requirements for an extensive range of scientific applications. BGS will yield the most precise baryon acoustic oscillation and redshift-space distortion measurements at z < 0.4. It presents opportunities for new methods that require highly complete and dense samples (e.g., N-point statistics, multitracers). BGS further provides a powerful tool to study galaxy populations and the relations between galaxies and dark matter