arXiv subjects

Julián Garrido

Publications and source records attributed to Julián Garrido.

9 recordsLinked to original sources

arXiv2026

Towards the exploration of astrophysical datacubes through volumetric rendering within CARTA

Data products from astrophysical observations may contain three or more dimensions: most commonly two spatial dimensions and a third spectral dimension, and possibly additional axes such as polarisation or time. Visualising three-dimensional image data is particularly useful for analysing the kinematics and evolution of various objects; however, the large scale of data produced by next-generation observatories and the complexity of displaying 3D data on a 2D screen make visualisation challenging. In this article, we present a scalable and interactive 3D visualisation approach within the astronomy software CARTA. We implemented a prototype 3D rendering widget with ThreeJS and known techniques to improve efficiency (e.g. compression, downsampling) and found that large datacubes up to 128 GB can be visualised locally with a loading time of a few minutes. We analysed the performance in the frontend and in the backend, finding that the bottleneck of our implementation lies in the frontend. This is due to storing the data in a single array in the frontend, unlike in the backend, where it is accessed and sent in blocks. This study paves the way for making 3D visualisation of large datacubes available to the community by implementing a 3D rendering widget in a future release of CARTA.

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arXiv2026

Advanced computing for reproducibility of astronomy Big Data Science, with a showcase of AMIGA and the SKA Science prototype

The Square Kilometre Array Observatory (SKAO) faces unprecedented technological challenges due to the vast scale and complexity of its data. This paper provides an overview of research by the AMIGA group to address these computing and reproducibility challenges. We present advancements in semantic data models, analysis services integrated into federated infrastructures, and the application to astronomy studies of techniques that enhance research transparency. By showcasing these astronomy work, we demonstrate that achieving reproducible science in the Big Data era is feasible. However, we conclude that for the SKAO to succeed, the development of the SKA Regional Centre Network (SRCNet) must explicitly incorporate these reproducibility requirements into its fundamental architectural design. Embedding these standards is crucial to enable the global community to conduct verifiable and sustainable research within a federated environment.

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arXiv2026

Bringing computation to the data: A MOEA-driven approach for optimising data processing in the context of the SKA and SRCNet

The Square Kilometre Array (SKA) will generate unprecedented data volumes, making efficient data processing a critical challenge. Within this context, the SKA Regional Centres Network (SRCNet) must operate in a near-exascale environment where traditional data-centric computing models based on moving large datasets to centralised resources are no longer viable due to network and storage bottlenecks. To address this limitation, this work proposes a shift towards distributed and in-situ computing, where computation is moved closer to the data. We explore the integration of Function-as-a-Service (FaaS) with an intelligent decision-making entity based on Evolutionary Algorithms (EAs) to optimise data-intensive workflows within SRCNet. FaaS enables lightweight and modular function execution near data sources while abstracting infrastructure management. The proposed decision-making entity employs Multi-Objective Evolutionary Algorithms (MOEAs) to explore near-optimal execution plans considering execution time and energy consumption, together with constraints related to data location and transfer costs. This work establishes a baseline framework for efficient and cost-aware computation-to-data strategies within the SRCNet architecture.

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arXiv2025

Semantic Model for the SKA Regional Centre Network

The unprecedented volume of data from the Square Kilometre Array (SKA) telescopes will require the implementation of robust and solid strategies for efficient data processing and management. In this context, the SKA Regional Centre Network (SRCNet) -- a collaborative global infrastructure comprising multiple regional centres distributed across various geographical regions around the globe -- is poised to play a critical role. This network will be instrumental in facilitating the effective handling and analysis of extensive data streams generated by the telescopes, thereby enabling significant advancements in astronomical research and exploration. This paper introduces a semantic model implemented with JSON-LD designed specifically for the SRCNet, detailing its architecture, data distribution, and computing service. By explicitly defining nodes, resources, relationships, and workflows, this model lays a foundation for interoperability and efficient resource management within the distributed network. The model presented in this text supports two possible configurations: centralized and decentralized -- depending where data reside -- enabling a future service broker to efficiently plan workflows by querying nodes for real-time system availability. Consistency tests conducted using SPARQL queries were made on the model in order to validate and test its integrity. Therefore, this research contributes to the advancement of semantic modeling in astronomy by addressing the semantic model for the SRCNet, a topic that has not been previously explored. This semantic model serves as a precursor to the development of a precise mathematical representation of the network and establishes a foundational framework for a future service broker.

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arXiv2024

Photometry and kinematics of dwarf galaxies from the Apertif HI survey

Context. Understanding the dwarf galaxy population in low density environments is crucial for testing the LCDM cosmological model. The increase in diversity towards low mass galaxies is seen as an increase in the scatter of scaling relations such as the stellar mass-size and the baryonic Tully-Fisher relation (BTFR), and is also demonstrated by recent in-depth studies of an extreme subclass of dwarf galaxies of low surface brightness, but large physical sizes, called ultra-diffuse galaxies (UDGs). Aims. We select galaxies from the Apertif HI survey, and apply a constraint on their i-band absolute magnitude to exclude high mass systems. The sample consists of 24 galaxies, and span HI mass ranges of 8.6 < log ($M_{HI}/M_{Sun}$) < 9.7 and stellar mass range of 8.0 < log ($M_*/M_{Sun}$) < 9.7 (with only three galaxies having log ($M_*/M_{Sun}$) > 9). Methods. We determine the geometrical parameters of the HI and stellar discs, build kinematic models from the HI data using 3DBarolo, and extract surface brightness profiles in g-, r- and i-band from the Pan-STARRS 1 photometric survey. Results. We find that, at fixed stellar mass, our HI selected dwarfs have larger optical effective radii than isolated, optically-selected dwarfs from the literature. We find misalignments between the optical and HI morphologies for some of our sample. For most of our galaxies, we use the HI morphology to determine their kinematics, and we stress that deep optical observations are needed to trace the underlying stellar discs. Standard dwarfs in our sample follow the same BTFR of high-mass galaxies, whereas UDGs are slightly offset towards lower rotational velocities, in qualitative agreement with results from previous studies. Finally, our sample features a fraction (25%) of dwarf galaxies in pairs that is significantly larger with respect to previous estimates based on optical spectroscopic data.

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arXiv2024

Integration of storage endpoints into a Rucio data lake, as an activity to prototype a SKA Regional Centres Network

The Square Kilometre Array (SKA) infrastructure will consist of two radio telescopes that will be the most sensitive telescopes on Earth. The SKA community will have to process and manage near exascale data, which will be a technical challenge for the coming years. In this respect, the SKA Global Network of Regional Centres plays a key role in data distribution and management. The SRCNet will provide distributed computing and data storage capacity, as well as other important services for the network. Within the SRCNet, several teams have been set up for the research, design and development of 5 prototypes. One of these prototypes is related to data management and distribution, where a data lake has been deployed using Rucio. In this paper we focus on the tasks performed by several of the teams to deploy new storage endpoints within the SKAO data lake. In particular, we will describe the steps and deployment instructions for the services required to provide the Rucio data lake with a new Rucio Storage Element based on StoRM and WebDAV within the Spanish SRC prototype.

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arXiv2024

An approach to provide serverless scientific pipelines within the context of SKA

Function-as-a-Service (FaaS) is a type of serverless computing that allows developers to write and deploy code as individual functions, which can be triggered by specific events or requests. FaaS platforms automatically manage the underlying infrastructure, scaling it up or down as needed, being highly scalable, cost-effective and offering a high level of abstraction. Prototypes being developed within the SKA Regional Center Network (SRCNet) are exploring models for data distribution, software delivery and distributed computing with the goal of moving and executing computation to where the data is. Since SKA will be the largest data producer on the planet, it will be necessary to distribute this massive volume of data to the SRCNet nodes that will serve as a hub for computing and analysis operations on the closest data. Within this context, in this work we want to validate the feasibility of designing and deploying functions and applications commonly used in radio interferometry workflows within a FaaS platform to demonstrate the value of this computing model as an alternative to explore for data processing in the distributed nodes of the SRCNet. We have analyzed several FaaS platforms and successfully deployed one of them, where we have imported several functions using two different methods: microfunctions from the CASA framework, which are written in Python code, and highly specific native applications like wsclean. Therefore, we have designed a simple catalogue that can be easily scaled to provide all the key features of FaaS in highly distributed environments using orchestrators, as well as having the ability to integrate them with workflows or APIs. This paper contributes to the ongoing discussion of the potential of FaaS models for scientific data processing, particularly in the context of large-scale, distributed projects such as SKA.

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arXiv2021

A diffuse tidal dwarf galaxy destined to fade out as a "dark galaxy"

We have explored the properties of a peculiar object detected in deep optical imaging and located at the tip of an HI tail emerging from Hickson Compact Group 16. Using multiband photometry from infrared to ultraviolet, we were able to constrain its stellar age to 58$^{+22}_{-9}$ Myr with a rather high metallicity of [Fe/H] = $-$0.16$^{+0.43}_{-0.41}$ for its stellar mass of M$_\star$ = 4.2$\times$10$^6$ M$_\odot$, a typical signature of tidal dwarf galaxies. The structural properties of this object are similar to those of diffuse galaxies, with a round and featureless morphology, a large effective radius (r$_{eff}$ = 1.5 kpc), and a low surface brightness (<$μ_{g}$>$_{eff}$ = 25.6 mag arcsec$^{-2}$). Assuming that the object is dynamically stable and able to survive in the future, its fading in time via the aging of its stellar component will make it undetectable in optical observations in just $\sim$2 Gyr of evolution, even in the deepest current or future optical surveys. Its high HI mass, M(HI) = 3.9$\times$10$^8$ M$_\odot$, and future undetectable stellar component will make the object match the observational properties of dark galaxies, that is, dark matter halos that failed to turn gas into stars. Our work presents further observational evidence of the feasibility of HI tidal features becoming fake dark galaxies; it also shows the impact of stellar fading, particularly in high metallicity systems such as tidal dwarfs, in hiding aged stellar components beyond detection limits in optical observations.

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arXiv2019

Evolution of compact groups from intermediate to final stages: A case study of the HI content of HCG 16

Hickson Compact Group (HCG) 16 is a prototypical compact group of galaxies, apparently in an intermediate stage of evolution, where its galaxies are losing gas to the intra-group medium (IGrM). The wide variety of ongoing process in HCG 16 make it an ideal case study for exploring which processes are likely to dominate the late stages of evolution in compact groups. In order to build a coherent picture of the evolution of this group we make use of the multi-wavelength data available, but focus particularly on HI as a tracer of interactions and evolutionary phase. We reprocess archival VLA L-band data of HCG 16 using the multi-scale CLEAN algorithm to accurately recover diffuse features. Despite the clear disruption of the HI component of HCG 16 we find that it is not globally HI deficient, even though HCG 16a and b have lost the majority of their HI and almost 50% of the group's HI is in the IGrM, including a 160 kpc long tail extending towards the SE. This study indicates that in the recent past (~1 Gyr) galaxies HCG 16a and b likely underwent major interactions that unbound gas without triggering significant star formation. This gas was then swept away by a high speed, close encounter with NGC 848. The starburst events HCG 16c and d have triggered galactic winds which, in the case of HCG 16d, appears to have disrupted its HI reservoir. The tidal features still connected to these galaxies indicate that more HI will soon be lost to the IGrM, while that which remains in the discs will likely be consumed by star formation episodes. This is expected to result in a collection of gas-poor galaxies embedded in a diffuse HI structure, which will gradually be evaporated by the UV background, resembling the final stage of the evolutionary model of compact groups. This work is accompanied by a complete workflow to reproduce the final data products, intended to improve reproducibility. (Abridged)

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