Astronomy and Computing最新文献

{"title":"Parameterized Hubble parameter with observational constraints in fractal gravity","authors":"D.K. Raut ,&nbsp;D.D. Pawar ,&nbsp;A.P. Kale ,&nbsp;N.G. Ghungarwar","doi":"10.1016/j.ascom.2025.100955","DOIUrl":"10.1016/j.ascom.2025.100955","url":null,"abstract":"<div><div>In the present paper, the dynamical aspects of the cosmological model of the Universe have been studied in fractal gravity, which is an effective quantum field theory. The parameterized Hubble parameter, given by <span><math><mrow><mi>H</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow><mo>=</mo><mfrac><mrow><msub><mrow><mi>H</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow><mrow><mn>2</mn></mrow></mfrac><mrow><mo>(</mo><mn>1</mn><mo>+</mo><msup><mrow><mrow><mo>(</mo><mn>1</mn><mo>+</mo><mi>z</mi><mo>)</mo></mrow></mrow><mrow><mi>n</mi></mrow></msup><mo>)</mo></mrow><mo>,</mo></mrow></math></span> is used to solve the field equations, where <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> and <span><math><mi>n</mi></math></span> are model parameters. We have obtained the approximate best-fit values of the model parameters using the least squares method, incorporating observational constraints from available datasets such as Hubble <span><math><mrow><mi>H</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow></mrow></math></span> and Pantheon, by applying the root mean square error (RMSE) formula.</div><div>For the approximate best fit values obtained from the model parameters, we observe that the deceleration parameter <span><math><mrow><mi>q</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow></mrow></math></span> exhibits a signature-flipping (transition) point within the range <span><math><mrow><mn>0</mn><mo>.</mo><mn>5</mn><mo>≤</mo><msub><mrow><mi>z</mi></mrow><mrow><mi>d</mi><mi>a</mi></mrow></msub><mo>≤</mo><mn>1</mn><mo>.</mo><mn>668</mn><mo>,</mo></mrow></math></span> marking the transition from a decelerated universe to an accelerated expanding universe. In addition, we discuss various physical parameters, including pressure, energy density, and energy conditions.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100955"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing the position and stability of the Lagrangian points under the gravitational effect of the Sun, Moon and the Earth including its oblateness","authors":"M. Kumar ,&nbsp;S. Yadav ,&nbsp;P.K. Behera","doi":"10.1016/j.ascom.2025.100966","DOIUrl":"10.1016/j.ascom.2025.100966","url":null,"abstract":"<div><div>The present study explores the existence and stability of the Lagrangian points in the Earth–Moon–Sun system, consider the artificial satellite moving around the Earth under the gravitational attraction of the Sun, the Earth and the Moon. Equations of motion of the satellite are determined in spherical polar coordinate system with the help of potential of the Earth. The positions and stability of the Lagrangian points lie on the <span><math><mi>x</mi></math></span>-axis and <span><math><mi>y</mi></math></span>-axis are investigated including the effect of <span><math><msub><mrow><mi>J</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> (oblateness of the Earth), <span><math><mi>ν</mi></math></span> (orbital angle of the Moon around the bary-center), <span><math><mi>α</mi></math></span> (orbital angle of the bary-center system around the Sun) and <span><math><mi>θ</mi></math></span> (longitude of the satellite). Finally, the zero velocity curves are drawn by taking different values of Jacobi constant. It is observed that region of possible motion decreases on increasing the values of Jacobi constants</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100966"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Africanus I. Scalable, distributed and efficient radio data processing with Dask-MS and Codex Africanus","authors":"S.J. Perkins ,&nbsp;J.S. Kenyon ,&nbsp;L.A.L. Andati ,&nbsp;H.L. Bester ,&nbsp;O.M. Smirnov ,&nbsp;B.V. Hugo","doi":"10.1016/j.ascom.2025.100958","DOIUrl":"10.1016/j.ascom.2025.100958","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The physical configuration of new radio interferometers such as MeerKAT, SKA, ngVLA and DSA-2000 informs the development of software in two important areas. Firstly, tractably processing the sheer quantity of data produced by new instruments necessitates subdivision and processing on multiple nodes. Secondly, the sensitivity inherent in modern instruments due to improved engineering practices and greater data quantities necessitates the development of new techniques to capitalize on the enhanced sensitivity of modern interferometers.&lt;/div&gt;&lt;div&gt;This produces a critical tension in radio astronomy software development: a fully optimized pipeline is desirable for producing science products in a tractable amount of time, but the design requirements for such a pipeline are unlikely to be understood upfront in the context of artefacts unveiled by greater instrument sensitivity. Therefore, new techniques must continuously be developed to address these artefacts and integrated into a full pipeline. As Knuth reminds us, “Premature optimization is the root of all evil”. This necessitates a fundamental trade-off between a trifecta of (1) performant code (2) flexibility and (3) ease-of-development. At one end of the spectrum, rigid design requirements are unlikely to capture the full scope of the problem, while throw-away research code is unsuitable for production use.&lt;/div&gt;&lt;div&gt;This work proposes a framework for the development of radio astronomy techniques within the above trifecta. In doing so, we favour flexibility and ease-of-development over performance, but this does not necessarily mean that the software developed within this framework is slow. Practically this translates to using data formats and software from the Open Source Community. For example, by using &lt;span&gt;NumPy&lt;/span&gt; arrays and/or &lt;span&gt;Pandas&lt;/span&gt; dataframes, a plethora of algorithms immediately become available to the scientific developer.&lt;/div&gt;&lt;div&gt;Focusing on performance, the breakdown of Moore’s Law in the 2010s and the resultant growth of both multi-core and distributed (including cloud) computing, a fundamental shift in the writing of radio astronomy algorithms and the storage of data is required: It is necessary to &lt;em&gt;shard&lt;/em&gt; data over multiple processors and compute nodes, and to write algorithms that operate on these shards in parallel. The growth in data volumes compounds this requirement. Given the fundamental shift in compute architecture we believe this is central to the performance of any framework going forward, and is given especial emphasis in this one.&lt;/div&gt;&lt;div&gt;This paper describes two Python libraries, &lt;span&gt;Dask-MS&lt;/span&gt; and &lt;span&gt;codex africanus&lt;/span&gt; &lt;!--&gt; &lt;!--&gt;which enable the development of distributed High-Performance radio astronomy code with &lt;span&gt;Dask&lt;/span&gt;. &lt;span&gt;Dask&lt;/span&gt; is a lightweight Python parallelization and distribution framework that seamlessly integrates with the &lt;span&gt;PyData&lt;/span&gt; ecosystem to address radio astronomy “Big Data","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100958"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of spiral galaxies by spiral arm number using convolutional neural network","authors":"Ming Wei Lee,&nbsp;John Y.H. Soo,&nbsp;Syarawi M.H. Sharoni","doi":"10.1016/j.ascom.2025.100965","DOIUrl":"10.1016/j.ascom.2025.100965","url":null,"abstract":"<div><div>The structural information of spiral galaxies such as the spiral arm number, offer valuable insights into the formation processes of spirals and their physical roles in galaxy evolution. We developed classifiers based on convolutional neural networks (CNNs) using variants of the EfficientNet architecture with different transfer learning techniques and pre-trained weights to categorise spiral galaxies by their number of spiral arms. A selected dataset from Galaxy Zoo 2, comprising 11<!--> <!-->718 images filtered based on appropriate criteria is used for training and evaluation. Both the V2M model (EfficientNetV2M architecture fine-tuned on ImageNet) and the B0 model (EfficientNetB0 architecture with Zoobot pre-trained weights) achieved high accuracy on the down-sampled dataset, with most performance metrics exceeding 0.8 across all classes, except for galaxies with 4 arms due to the limited number of samples in this category. Merging higher-arm-number classes (more than 4 arms) improved the V2M model’s accuracy significantly for 4-arm galaxies, as this approach allowed the model to focus on more distinct features within fewer, broader categories with a more balanced class distribution. GradCAM++ and SmoothGrad highlight the networks’ effectiveness in classifying galaxies, through the distinction of the galaxy structures and the extraction of the spiral arms, with the V2M model showing better capabilities in both tasks. Lower-arm galaxies tend to be misclassified as “can’t tell” when their spiral arms are not clearly visible, while higher-arm galaxies tend to be misclassified as having fewer arms when their features are only partially detected. The study also found that galaxies with 3 arms tend to have lower stellar masses, and this tendency is reduced in the model predictions. The models’ mispredictions between 2-arm and 1/3-arm are likely resulting from external interference and dynamic nature of spiral arms. The V2M model prediction also shows a slight tendency towards higher stellar mass in <strong>many-arm</strong> galaxies.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100965"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SSOXmatch: A Java pipeline to compute cross-matches of Solar System bodies in astronomical observations","authors":"T. Alonso-Albi","doi":"10.1016/j.ascom.2025.100968","DOIUrl":"10.1016/j.ascom.2025.100968","url":null,"abstract":"<div><div>In this paper I will describe a new software package developed using the Java programming language, aimed to compute the positions of any Solar System body (among asteroids, comets, planets, and satellites) to help to perform cross-matches of them in observations taken from earth- and space-based observatories. The space telescopes supported are Hubble, James Webb, Euclid, XMM-Newton, Spitzer, Herschel, Gaia, Kepler, Chandra, and TESS, although the flexibility of the software allows to support any other mission without the need to change a single line of code. The orbital elements can be selected among the asteroid database from the Lowell observatory (completed with the cometpro database of comets maintained by the LTE), and the JPL database of minor bodies.</div><div>The software does not depend on external tools, and performs its own numerical integration of minor bodies. The dynamical model implemented for the Solar System includes the gravity effects of all major bodies, including the Earth, Moon, and Pluto as individual bodies, 16 perturbing asteroids as in other tools, the General Relativity effects, the oblateness of the Sun, Earth, and Moon, and the non-gravitational forces for both comets and asteroids. A complete set of web services allow to compute the cross-matches (that are later to be confirmed, for instance by visual inspection of the images) and also ephemerides of specific bodies. The code is highly optimized and follows the highest standards in terms of software quality and documentation.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100968"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of ghost dark energy on cosmic evolution in f(Q, L m) theory","authors":"M. Zeeshan Gul ,&nbsp;M. Sharif ,&nbsp;S.A. Qureshi","doi":"10.1016/j.ascom.2025.100956","DOIUrl":"10.1016/j.ascom.2025.100956","url":null,"abstract":"<div><div>The primary aim of this research is to explore the ghost dark energy model in the framework of <span><math><mi>f</mi></math></span>(<span>Q</span>, <span>L</span> _m) gravity, where <span>Q</span> represents the non-metricity scalar and <span>L</span> _m denotes the matter-Lagrangian density. To achieve this objective, we investigate the homogeneous and isotropic universe with an ideal matter distribution. We examine a scenario with interacting fluids that encompass both dark energy and dark matter in this context. Further, we reconstruct <span><math><mi>f</mi></math></span>(<span>Q</span>, <span>L</span> _m) model to examine the effects of this extended gravitational framework on the cosmic evolution. We explore the behavior of numerous cosmic parameters corresponding to distinct parametric values. The viability of the ghost dark energy model is evaluated by the matter contents, revealing that it supports the fast expansion of the cosmos. Furthermore, the statefinder <span><math><mrow><mo>(</mo><mi>r</mi><mo>,</mo><mi>s</mi><mo>)</mo></mrow></math></span> and standard diagnostic pairs <span><math><mrow><mo>(</mo><msub><mrow><mi>ω</mi></mrow><mrow><mi>D</mi></mrow></msub><mo>−</mo><msubsup><mrow><mi>ω</mi></mrow><mrow><mi>D</mi></mrow><mrow><mo>′</mo></mrow></msubsup><mo>)</mo></mrow></math></span> are used to study the various cosmic eras. This study offers novel perspectives on the correlation between dark energy models and modified gravity theories, thereby enhancing our comprehension of cosmic evolution. Our results align with recent observational evidence, indicating that the <span><math><mi>f</mi></math></span>(<span>Q</span>, <span>L</span> _m) model effectively characterizes dark energy and cosmic evolution.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100956"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-stage machine learning-based method to estimate wind parameters from Hα lines of massive stars","authors":"Felipe Ortiz ,&nbsp;Raquel Pezoa ,&nbsp;Michel Curé ,&nbsp;Ignacio Araya ,&nbsp;Roberto O.J. Venero ,&nbsp;Catalina Arcos ,&nbsp;Pedro Escárate ,&nbsp;Natalia Machuca ,&nbsp;Alejandra Christen","doi":"10.1016/j.ascom.2025.100941","DOIUrl":"10.1016/j.ascom.2025.100941","url":null,"abstract":"<div><div>This work presents a multi-stage method for estimating wind parameters in the domain of massive stars. We use the H<span><math><mi>α</mi></math></span> non-rotating synthetic spectral lines from the ISOSCELES database’s <span><math><mi>δ</mi></math></span>-slow solutions to train a Gaussian Mixture Model-based cluster method and a deep neural network classifier. Then, the observed H<span><math><mi>α</mi></math></span> line profiles are deconvolved and classified into a class that provides a reduced subset of line profiles defined in ISOSCELES. This allows us to accurately and rapidly identify the closest line profile within the selected subset and obtain the wind parameters: <span><math><msub><mrow><mi>v</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> and <span><math><mover><mrow><mi>M</mi></mrow><mrow><mo>̇</mo></mrow></mover></math></span>. Compared to traditional methods, this multi-stage proposal significantly reduces the computation time required to determine the wind parameters and gives more accurate and objective results. Interesting results of this work include evaluating the method for a sample of 12 B-supergiants, offering a notable improvement in the fitting of the line profiles, as it allows for a better approximation of the shape of the P Cygni lines for both components, absorption, and emission.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100941"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D radio data visualisation in open science platforms for next-generation observatories","authors":"I. Labadie-García,&nbsp;J. Garrido,&nbsp;L. Verdes-Montenegro,&nbsp;M.Á. Mendoza,&nbsp;M. Parra-Royón,&nbsp;S. Sánchez-Expósito,&nbsp;R. Ianjamasimanana","doi":"10.1016/j.ascom.2025.100949","DOIUrl":"10.1016/j.ascom.2025.100949","url":null,"abstract":"<div><div>Next-generation telescopes will bring groundbreaking discoveries but they will also present new technological challenges. The Square Kilometre Array Observatory (SKAO) will be one of the most demanding scientific infrastructures, with a projected data output of 700 PB per year to be distributed to a network of SKA Regional Centres. Current tools are not fully suited to manage such massive data volumes, therefore, new research is required to transform science archives from data providers into service providers. In this paper we examine how a science archive can deliver advanced visualisation capabilities for the SKA science archive. In particular, we have conducted a thorough exploration of existing visualisation software for astronomy and other fields to identify tools capable of addressing Big Data requirements. Using selected technologies, we have developed a prototype archive that provides access to interactive visualisations of 3D radio data through web-based interfaces, adhering to International Virtual Observatory Alliance (IVOA) recommendations to favour interoperability and Open Science practices. In addition, we discuss how current IVOA recommendations support these visualisation capabilities and how they could be expanded. Our prototype archive includes a service to generate 3D models on the fly as a server operation, enabling remote visualisations in a flexible manner; for instance, a set of parameters can be used to customise the models and their visualisation. We have used SKA precursor and pathfinder data to test its usability and scalability, concluding that remote visualisation is a viable solution for handling high-volume data. However, our prototype is constrained by memory limitations, requiring techniques to reduce memory usage.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100949"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Africanus IV. The Stimela2 framework: Scalable and repeatable workflows, from local to cloud compute","authors":"O.M. Smirnov ,&nbsp;S. Makhathini ,&nbsp;J.S. Kenyon ,&nbsp;H.L. Bester ,&nbsp;S.J. Perkins ,&nbsp;A.J.T. Ramaila ,&nbsp;B.V. Hugo","doi":"10.1016/j.ascom.2025.100959","DOIUrl":"10.1016/j.ascom.2025.100959","url":null,"abstract":"<div><div><span>Stimela2</span> is a new-generation framework for developing data reduction workflows. It is designed for radio astronomy data but can be adapted for other data processing applications. <span>Stimela2</span> aims at the middle ground between ease of development, human readability, and enabling robust, scalable and repeatable workflows. <span>Stimela2</span> defines a YAML-based domain specific language (DSL), which represents workflows by linear, concise and intuitive YAML-format <em>recipes</em>. Atomic data reduction tasks (binary executables, Python functions and code, and CASA tasks) are described by YAML-format <em>cab definitions</em> detailing each task’s <em>schema</em> (inputs and outputs). The <span>Stimela2</span> DSL provides a rich syntax for chaining tasks together, and encourages a high degree of modularity: recipes may be nested into other recipes, and configuration is cleanly separated from recipe logic. Tasks can be executed natively or in isolated environments using containerization technologies such as Apptainer. The container images are open-source and maintained through a companion package called <span>cult-cargo</span>. This enables the development of system-agnostic and repeatable workflows. <span>Stimela2</span> facilitates the deployment of scalable, distributed workflows by interfacing with the <span>Slurm</span> scheduler and the <span>Kubernetes</span> API. The latter allows workflows to be readily deployed in the cloud. Previous papers in this series used <span>Stimela2</span> as the underlying technology to run workflows on the AWS cloud.</div><div>This paper presents an overview of <span>Stimela2</span>’s design, architecture and use in the radio astronomy context.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100959"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the power of uncertainty: A journey into Bayesian Neural Networks for stellar dating","authors":"Víctor Tamames-Rodero ,&nbsp;Andrés Moya ,&nbsp;Luis Manuel Sarro ,&nbsp;Roberto Javier López-Sastre","doi":"10.1016/j.ascom.2025.100957","DOIUrl":"10.1016/j.ascom.2025.100957","url":null,"abstract":"<div><h3>Context:</h3><div>Astronomy and astrophysics demand rigorous handling of uncertainties to ensure the credibility of outcomes. The growing integration of artificial intelligence offers a novel avenue to address this necessity. This convergence presents an opportunity to create advanced models capable of quantifying diverse sources of uncertainty and automating complex data relationship exploration.</div></div><div><h3>What:</h3><div>We introduce a hierarchical Bayesian architecture whose probabilistic relationships are modeled by neural networks, designed to forecast stellar attributes such as mass, radius, and age (our main target). This architecture handles both observational uncertainties stemming from measurements and epistemic uncertainties inherent in the predictive model itself. As a result, our system generates distributions that encapsulate the potential range of values for our predictions, providing a comprehensive understanding of their variability and robustness.</div></div><div><h3>Methods:</h3><div>Our focus is on dating main sequence stars using a technique known as Chemical Clocks, which serves as both our primary astronomical challenge and a model prototype. In this work, we use hierarchical architectures to account for correlations between stellar parameters and optimize information extraction from our dataset. We also employ Bayesian neural networks for their versatility and flexibility in capturing complex data relationships.</div></div><div><h3>Results:</h3><div>By integrating our machine learning algorithm into a Bayesian framework, we have successfully propagated errors consistently and managed uncertainty treatment effectively, resulting in predictions characterized by broader uncertainty margins. This approach facilitates more conservative estimates in stellar dating. Our architecture achieves age predictions with a mean absolute error of less than 1 Ga for the stars in the test dataset.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"52 ","pages":"Article 100957"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}