Search Results (10)

This study focuses on the recovery and digitization of three fragmentary meteorological datasets from the archives of the Royal Observatory of the Spanish Navy in Cádiz, covering selected days in 1776, 1788, and 1793. These records include temperature, pressure, and occasional wind observations originally linked to astronomical measurements. After manual transcription and quality control, the historical data were compared with long-term climate statistics from the period 1955–2021 for Cádiz. Despite the absence of metadata on instruments and installation, the 18th-century observations show reasonable agreement with present-day seasonal patterns, indicating their reliability. Wind data, although limited, were documented using an eight-point wind rose and terminology consistent with historical standards. These findings highlight the scientific and historical value of scattered early observations. They provide reference points for validating historical reanalysis and suggest that additional records may exist in naval archives. Continued efforts to recover such data will improve long-term climate reconstructions for southern Spain and beyond. Full article

This paper presents a flexible approach to a multipurpose, heterogeneous archive and data management system model that merges the robustness of legacy grid-based technologies with modern cloud and edge computing paradigms. It leverages innovations driven by big data, IoT, AI, and machine learning to create an adaptive data storage and processing framework. In today’s digital age, where data are the new intangible gold, the “gold rush” lies in managing and storing massive datasets effectively—especially when these data serve governmental or commercial purposes, raising concerns about privacy and data misuse by third-party aggregators. Astronomical data, in particular, require this same thoughtful approach. Scientific discovery increasingly depends on efficient extraction and processing of large datasets. Distributed archival models, unlike centralized warehouses, offer scalability by allowing data to be accessed and processed across locations via cloud services. Incorporating edge computing further enables real-time access with reduced latency. Major astronomical projects must also avoid common single points of failure (SPOFs), often resulting from suboptimal technological choices driven by collaboration politics or In-Kind Contributions (IKCs). These missteps can hinder innovation and long-term project success. The principal goal of this work is to outline best practices in archival and data management projects—from policy development and task planning to use-case definition and implementation. Only after these steps can a coherent selection of hardware, software, or virtual environments be made. The proposed model—CTAARCHS (Cloud-based Technologies for Astronomical Archiving Research Contents and Handling Systems)—is an open-source, multidisciplinary platform supporting big data needs in astronomy. It promotes broad institutional collaboration, offering code repositories and sample data for immediate use. Full article

Studying the host galaxies of fast radio bursts (FRBs) is critical to understanding the formation processes of their sources and, hence, the mechanisms by which they radiate. Toward this end, we have extended the Blinkverse database version 1.0, which already included burst information about FRBs observed by various telescopes, by adding information about 92 published FRB host galaxies to make version 2.0. Each FRB host has 18 parameters describing it, including redshift, stellar mass, star-formation rate, emission line fluxes, etc. In particular, each FRB host includes images collated by FASTView, streamlining the process of looking for clues to understanding the origin of FRBs. FASTView is a tool and API for quickly exploring astronomical sources using archival imaging, photometric, and spectral data. This effort represents the first step in building Blinkverse into a comprehensive tool for facilitating source observation and analysis. Full article

We present an updated repository of sub-mJy extragalactic radio source counts between 150 MHz and 10 GHz, incorporating recent advances in radio surveys and observational techniques. By compiling and refining previous datasets, we provide a comprehensive catalog that enhances the understanding of faint radio-source populations, including Dusty Star-Forming Galaxies (DSFGs) and Radio-Quiet Active Galactic Nuclei (RQAGNs), from intermediate to high redshifts. Our analysis accounts for observational biases, such as resolution effects and Eddington bias, ensuring improved accuracy in flux-density estimations. We also discuss the implications of new-generation radio telescopes, such as the Square-Kilometer Array Observatory (SKAO) and its precursors and pathfinders, to further resolve these populations. Our collection contributes to constraining evolutionary models of radio sources, highlighting the increasing role of polarization studies in distinguishing different classes. This work serves as a key reference for future deep radio surveys targeting the faintest end of the extragalactic radio sky. Full article

The broad point spread function of the NuSTAR telescope makes resolving astronomical X-ray sources a challenging task, especially for off-axis observations. This limitation has affected the observations of the high-mass X-ray binary pulsars SXP 15.3 and SXP 305, in which pulsations are detected from nearly overlapping regions without spatially resolving these X-ray sources. To address this issue, we introduce a deconvolution algorithm designed to enhance NuSTAR’s spatial resolution for closely spaced X-ray sources. We apply this technique to archival data and simulations of synthetic point sources placed at varying separations and locations, testing the algorithm’s efficacy in source detection and differentiation. Our study confirms that on some occasions when SXP 305 is brighter, SXP 15.3 is also resolved, suggesting that some prior non-detections may have resulted from imaging limitations. This deconvolution technique represents a proof of concept test for analyzing crowded fields in the sky with closely spaced X-ray sources in future NuSTAR observations. Full article

In this paper, we investigate the benefits of teaming up data from the radio to the far-infrared (FIR) regime for the characterization of dusty star-forming galaxies (DSFGs). These galaxies are thought to be the star-forming progenitors of local massive quiescent galaxies and to play a pivotal role in the reconstruction of the cosmic star formation rate density up to high redshift. Due to their dust-enshrouded nature, DSFGs are often invisible in the near-infrared/optical/UV bands. Therefore, they necessitate observations at longer wavelengths, primarily the FIR band, where dust emission occurs, and the radio band, which is not affected by dust absorption. Combining data from these two spectral windows makes it possible to characterize even the dustiest objects, enabling the retrieval of information about their age, dust temperature, and star-formation status, and facilitates the differentiation between various galaxy populations that evolve throughout cosmic history. Despite the detection of faint radio sources being a challenging task, this study demonstrates that an effective strategy to build statistically relevant samples of DSFGs would be reaching deep sensitivities in the radio band, even restricted to smaller areas, and then combining these radio observations with FIR/submm data. Additionally, this paper quantifies the improvement in the spectral energy distribution (SED) reconstruction of DSFGs by incorporating ALMA band measurements, in particular, in its upgraded status thanks to the anticipated Wideband Sensitivity Upgrade. Full article

The rise of big data has resulted in the proliferation of numerous heterogeneous data stores. Even though multiple models are used for integrating these data, combining such huge amounts of data into a single model remains challenging. There is a need in the database management archives to manage such huge volumes of data without any particular structure which comes from unconnected and unrelated sources. These data are growing in size and thus demand special attention. The speed with which these data are growing as well as the varied data types involved and stored in scientific archives is posing further challenges. Astronomy is also increasingly becoming a science which is now based on a lot of data processing and involves assorted data. These data are now stored in domain-specific archives. Many astronomical studies are producing large-scale archives of data and these archives are then published in the form of data repositories. These mainly consist of images and text without any structure in addition to data with some structure such as relations with key values. When the archives are published as remote data repositories, it is challenging work to organize the data against their increased diversity and to meet the information demands of users. To address this problem, polystore systems present a new model of data integration and have been proposed to access unrelated data repositories using an uniform single query language. This article highlights the polystore system for integrating large-scale heterogeneous data in the astronomy domain. Full article

The aim of this work is to search for evidence of close binary stars associated with planetary nebulae (ionized stellar envelopes in expansion) by mining the astronomical archive of Gaia EDR3. For this task, using big data techniques, we selected a sample of central stars of planetary nebulae from almost 2000 million sources in an EDR3 database. Then, we analysed some of their parameters, which could provide clues about the presence of close binary systems, and we ran a statistical test to verify the results. Using this method, we concluded that red stars tend to show more affinity with close binarity than blue ones. Full article

The aim of this work is to search for binary stars associated to planetary nebulae (ionized stellar envelopes in expansion), by mining the astronomical archive of Gaia DR2, that is composed by around 1.7 billion stellar sources. For this task, we selected those objects with coincident astrometric parameters (parallaxes and proper motions) with the corresponding central star, among a sample of 211 planetary nebulae. By this method, we found eight binary systems, and we obtained their components positions, separations, temperatures and luminosities, as well as some of their masses and ages. In addition, we estimated the probability for each companion star of having been detected by chance and we analyzed how the number of false matches increase as the separation distance between both stars gets larger. All these procedures have been carried out making use of data mining techniques. Full article

Anecdotal data are currently the best data available to describe baseline conditions of beached oil tar balls on Florida’s First Coast beaches. This study combines field methods and numerical modeling to define a data-driven knowledge base of oil tar ball baseline conditions. Outcomes from the field study include an established methodology for field data collection and laboratory testing of beached oil tar balls, spatial maps of collected samples and analysis of the data as to transport/wash-up trends. Archives of the electronic data, including GPS locations and other informational tags, and collected samples are presented, as are the physical and chemical analyses of the collected samples. The thrust of the physical and chemical analyses is to differentiate the collected samples into highly suspect oil tar balls versus false/non-oil tar ball samples. The numerical modeling involves two-dimensional hydrodynamic simulations of astronomic tides. Results from the numerical modeling include velocity residuals that show ebb-dominated residual currents exiting the inlet via an offshore, counter-rotating dual-eddy system. The tidally derived residual currents are used as one explanation for the observed transport trends. The study concludes that the port activity in the St. Johns River is not majorly contributing to the baseline conditions of oil tar ball wash-up on Florida’s First Coast beaches. Full article