Astronomy and Computing最新文献_第5页

Modified teukolsky framework for environmentally-coupled black hole ringdown: A physics-informed neural network approach for improved gravitational wave analysis 环境耦合黑洞衰荡的改进teukolsky框架：改进引力波分析的物理信息神经网络方法

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.ascom.2026.101072

A Stanley Raj, Adityan S․, Praveen Kumar K․C․

{"title":"Modified teukolsky framework for environmentally-coupled black hole ringdown: A physics-informed neural network approach for improved gravitational wave analysis","authors":"A Stanley Raj, Adityan S․, Praveen Kumar K․C․","doi":"10.1016/j.ascom.2026.101072","DOIUrl":"10.1016/j.ascom.2026.101072","url":null,"abstract":"<div><div>This research present a novel Physics-Informed Neural Network (PINN) framework for modeling Gravitational Wave (GW) ringdown signals from binary black hole systems, explicitly incorporating the gravitational influence of nearby compact objects. Traditional analyses of ringdown waveforms typically assume isolated black holes, but real astrophysical environments often involve complex multi-body dynamics. To address this, the classical Teukolsky formalism is extended, which governs spin-2 perturbations in Kerr spacetime, by introducing external attenuation potentials<strong>.</strong> These potentials model the dynamical effects of secondary compact objects, enabling the capture of environmental interference during the ringdown phase.</div><div>Our Physics Informed Neural Network (PINN) architecture is designed to solve the modified Teukolsky equation while simultaneously learning the underlying physical behavior from observational or simulated constraints. By embedding the governing differential equations into the training process, the model ensures physical consistency while benefiting from the generalization ability of deep learning. This framework allows for accurate reconstruction of GW ringdown signals affected by external bodies and provides insights into the Quasinormal Mode (QNM) structure under non-isolated conditions.</div><div>The proposed method not only improves waveform modeling in realistic astrophysical scenarios but also lays the groundwork for machine learning applications in complex multi-body gravitational systems<strong>.</strong> This approach holds promise for better characterization of environmental effects in GW signals and advancing the precision of black hole spectroscopy in the era of next-generation gravitational wave detectors.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"55 ","pages":"Article 101072"},"PeriodicalIF":1.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173476","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}

引用次数: 0

Nano-particle Transition Matrix code implementation 纳米粒子过渡矩阵代码实现

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-04-01 Epub Date: 2026-02-03 DOI: 10.1016/j.ascom.2026.101077

G. La Mura , G. Mulas , G. Aresu , M.A. Iatì , C. Cecchi-Pestellini , S. Rezaei , R. Saija

{"title":"Nano-particle Transition Matrix code implementation","authors":"G. La Mura , G. Mulas , G. Aresu , M.A. Iatì , C. Cecchi-Pestellini , S. Rezaei , R. Saija","doi":"10.1016/j.ascom.2026.101077","DOIUrl":"10.1016/j.ascom.2026.101077","url":null,"abstract":"<div><div>Electromagnetic scattering and absorption by material particles is a fundamental physical problem with a broad range of applications, going from laboratory experiments, biology and material sciences, all the way up to environmental studies and astrophysical investigations. In spite of its primary importance, an exact theoretical treatment is only possible for a limited range of ideal cases, while realistic situations require the development of numerical solutions. In the course of the years, several techniques were developed to model the effects of scattering and absorption in more general cases, using approaches such as the Discrete Dipole Approximation (DDA), the Finite Difference Time Domain (FDTD) method, the Transition Matrix formalism (T-matrix) or the Mean Field Theory (MFT). Among these possibilities, the T-matrix approach grants the highest degree of flexibility in modeling aggregates of spherically symmetric particles with arbitrary overall morphology and composition, but its application has been limited by the challenging computational requirements of the method in realistic cases. This paper describes the Nano-Particle Transition Matrix Code project (<span>NP_TMcode</span>), a new implementation of the T-matrix formalism that, taking advantage of high performance parallel hardware architectures, allows the solution of increasingly complex models, while substantially reducing the computing time. The paper describes the code structure, with a particular focus on the algorithm optimization, and it presents the results of the performance analysis for a set of development applications.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"55 ","pages":"Article 101077"},"PeriodicalIF":1.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173479","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}

引用次数: 0

FAST-MEPSA: An optimised and faster version of peak detection algorithm MEPSA 快速-MEPSA：峰值检测算法MEPSA的优化和更快版本

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-04-01 Epub Date: 2025-12-02 DOI: 10.1016/j.ascom.2025.101040

M. Maistrello , R. Maccary , C. Guidorzi

{"title":"FAST-MEPSA: An optimised and faster version of peak detection algorithm MEPSA","authors":"M. Maistrello , R. Maccary , C. Guidorzi","doi":"10.1016/j.ascom.2025.101040","DOIUrl":"10.1016/j.ascom.2025.101040","url":null,"abstract":"<div><div>We present <span>FAST-MEPSA</span>, an optimised version of the <span>MEPSA</span> algorithm developed to detect peaks in uniformly sampled time series affected by uncorrelated Gaussian noise. Although originally conceived for the analysis of gamma-ray burst (GRB) light curves (LCs), <span>MEPSA</span> can be readily applied to other transient phenomena. The algorithm scans the input data by applying a set of 39 predefined patterns across multiple timescales. While robust and effective, its computational cost becomes significant at large re-binning factors. To address this, <span>FAST-MEPSA</span> introduces a sparser offset-scanning strategy. In parallel, building on <span>MEPSA</span>’s flexibility, we introduce a 40th pattern specifically designed to recover a class of elusive peaks that are typically sub-threshold and lie on the rising edge of broader structures—often missed by the original pattern set. Both versions of <span>FAST-MEPSA</span> — with 39 and 40 patterns — were validated on simulated GRB LCs. Compared to <span>MEPSA</span>, the new implementation achieves a speed-up of nearly a factor 400 at high re-binning factors, with only a minor (<span><math><mrow><mo>∼</mo><mn>4</mn><mtext>%</mtext></mrow></math></span>) reduction in the number of detected peaks. It retains the same detection efficiency while significantly lowering the false positive rate of low significance. The inclusion of the new pattern increases the recovery of previously undetected and sub-threshold peaks. These improvements make <span>FAST-MEPSA</span> an effective tool for large-scale analyses where a robust trade-off between speed, efficiency, and reliability is essential. The adoption of 40 patterns instead of the classical 39 is advisable when an enhanced efficiency in detecting faint events is desired. The code is made publicly available.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"55 ","pages":"Article 101040"},"PeriodicalIF":1.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684927","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}

引用次数: 0

Genetic algorithm demystified for cosmological parameter estimation 遗传算法在宇宙学参数估计中的应用

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-04-01 Epub Date: 2025-12-08 DOI: 10.1016/j.ascom.2025.101041

R.C. Bernardo , Y. Chen

引用次数: 0

Entropy-based properties and Bayesian modeling of the Xexponential Distribution with applications in astronomy 基于熵的性质和x指数分布的贝叶斯建模及其在天文学中的应用

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-04-01 Epub Date: 2025-12-27 DOI: 10.1016/j.ascom.2025.101054

Abdelfateh Beghriche , Zineb Azouz , Halim Zeghdoudi

{"title":"Entropy-based properties and Bayesian modeling of the Xexponential Distribution with applications in astronomy","authors":"Abdelfateh Beghriche , Zineb Azouz , Halim Zeghdoudi","doi":"10.1016/j.ascom.2025.101054","DOIUrl":"10.1016/j.ascom.2025.101054","url":null,"abstract":"<div><div>This study introduces and systematically investigates the X-Exponential Distribution (XED), a one-parameter lifetime model that generalizes the exponential–gamma mixture structure. We derive closed-form expressions and simulation-based evaluations of several entropy measures, including Shannon, Rényi, and Tsallis entropy, as well as information divergence measures such as the Kullback–Leibler divergence. Special emphasis is placed on the distribution’s flexibility in modeling stochastic uncertainty and its intermediate tail behavior, which arises naturally from its representation as a mixture of exponential and gamma components. Furthermore, the mean and variance are obtained in explicit form, and connections to reliability modeling are highlighted. A Bayesian framework is outlined to incorporate prior uncertainty on the rate parameter, allowing hierarchical extensions. Application to lifetime and reliability data illustrates that the XED provides superior goodness-of-fit compared to classical exponential models, confirming its usefulness in applied probability, reliability engineering, and related domains.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"55 ","pages":"Article 101054"},"PeriodicalIF":1.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883943","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}

引用次数: 0

The XMM-Newton and INTEGRAL operational ground segment: Synergetic systems and software operated for more than two decades xmm -牛顿和INTEGRAL作战地面部分：协同系统和软件已经运行了20多年

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-01-01 Epub Date: 2025-09-06 DOI: 10.1016/j.ascom.2025.101000

Marcus G.F. Kirsch , Greta De Marco , Frank Dreger , Aniris Inojosa , Gianluca Gaudenzi , Jutta M. Huebner , Sebastian Kriege , Richard Southworth , Uwe Weissmann

{"title":"The XMM-Newton and INTEGRAL operational ground segment: Synergetic systems and software operated for more than two decades","authors":"Marcus G.F. Kirsch , Greta De Marco , Frank Dreger , Aniris Inojosa , Gianluca Gaudenzi , Jutta M. Huebner , Sebastian Kriege , Richard Southworth , Uwe Weissmann","doi":"10.1016/j.ascom.2025.101000","DOIUrl":"10.1016/j.ascom.2025.101000","url":null,"abstract":"<div><div>The European Space Agency (ESA) has been operating the XMM-Newton and INTEGRAL observatories for over two decades, providing invaluable high-energy astrophysical data. Both missions share a synergistic operational ground segment, allowing for streamlined mission control, automation enhancements, and optimized resource utilization. This paper discusses the evolution of the mission control system, the integration of automation for spacecraft and instrument operations, and the adoption of virtualization technologies to ensure long-term mission sustainability. Additionally, it highlights the challenges of maintaining real-time telemetry-driven operations while minimizing operational costs. Lessons learned from these missions provide key insights for future ESA science operations. A key outcome highlighted in this work is the long-term success of retaining the legacy SOCS-2000 system, which has reliably operated for over two decades despite evolving hardware and software environments.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"54 ","pages":"Article 101000"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050404","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}

引用次数: 0

Advanced Data Products for radio observatories 射电天文台的先进数据产品

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-01-01 Epub Date: 2025-09-12 DOI: 10.1016/j.ascom.2025.101003

Villard E. , Ahmadi A. , Bolton R. , Breen S. , Castro S. , De Breuck C. , Deg N. , Delli Veneri M. , Emsellem E. , Fleming S. , Guglielmetti F. , Hess K.M. , Hibbard J. , Holties H. , Humphreys L. , Iacobelli M. , Jachym P. , Jones B. , Kimball A. , Koch E. , Zwaan M.

{"title":"Advanced Data Products for radio observatories","authors":"Villard E. , Ahmadi A. , Bolton R. , Breen S. , Castro S. , De Breuck C. , Deg N. , Delli Veneri M. , Emsellem E. , Fleming S. , Guglielmetti F. , Hess K.M. , Hibbard J. , Holties H. , Humphreys L. , Iacobelli M. , Jachym P. , Jones B. , Kimball A. , Koch E. , Zwaan M.","doi":"10.1016/j.ascom.2025.101003","DOIUrl":"10.1016/j.ascom.2025.101003","url":null,"abstract":"<div><div>Advanced Data Products (ADPs) are increasingly central to enhancing the efficiency and scientific output of radio observatories. Designed to bridge the gap between raw observational data and science-ready results, ADPs reduce processing overhead, improve reproducibility, and enable a wider range of researchers to engage with complex datasets. Their benefits include accelerated research, interoperability across archives, and reduced duplication of computational effort, with direct implications for sustainability. This paper summarizes the outcomes of the ADP2024 workshop, which reviewed current practices at major facilities including ALMA, SKAO, LOFAR, VLA, and ESO. We highlight lessons learned from ongoing initiatives. Critical issues identified include standardization, provenance tracking, quality assurance, and long-term maintenance. We conclude that ADPs represent a key step toward sustainable, accessible, and scientifically optimized data ecosystems in radio astronomy.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"54 ","pages":"Article 101003"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060755","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}

引用次数: 0

Physics-informed Lane-Emden solvers using Lynx-Net: Implementing radial basis functions in Kolmogorov representation 使用Lynx-Net的物理知情Lane-Emden解算器：在Kolmogorov表示中实现径向基函数

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-01-01 Epub Date: 2025-09-11 DOI: 10.1016/j.ascom.2025.100997

Elmira Mirzabeigi , Maryam Babaei , Amir Hossein Karami , Sepehr Rezaee , Rezvan Salehi , Kourosh Parand

{"title":"Physics-informed Lane-Emden solvers using Lynx-Net: Implementing radial basis functions in Kolmogorov representation","authors":"Elmira Mirzabeigi , Maryam Babaei , Amir Hossein Karami , Sepehr Rezaee , Rezvan Salehi , Kourosh Parand","doi":"10.1016/j.ascom.2025.100997","DOIUrl":"10.1016/j.ascom.2025.100997","url":null,"abstract":"<div><div>This paper introduces a novel approach for solving Lane-Emden equations using Lynx-Net, a Physics-Informed Neural Network that integrates Radial Basis Functions (RBFs) within the Kolmogorov representation framework. Lynx-Net addresses these challenges by combining RBF-enhanced function approximation with physics-informed constraints: differential-equation residuals are enforced during training, ensuring stability and rapid convergence. Across a spectrum of polytropic indices, our experiments show that Lynx-Net consistently outperforms prior machine-learning approaches, achieving lower errors without incurring excessive computational cost. The proposed model leverages the function approximation capabilities of RBFs and physics-informed constraints to enhance solution stability and convergence. By incorporating differential equation residuals into the learning process, Lynx-Net minimizes errors while maintaining computational efficiency. Experimental results across multiple test cases demonstrate its superiority over conventional solvers and existing machine learning-based approaches. This research highlights the potential of integrating RBFs with PINNs for solving nonlinear differential equations, providing a scalable and efficient framework applicable to broader problems in astrophysics and engineering.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"54 ","pages":"Article 100997"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100052","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}

引用次数: 0

Experiences of commercial supercomputing in radio astronomy data processing 商用超级计算机在射电天文数据处理中的经验

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-01-01 Epub Date: 2025-10-03 DOI: 10.1016/j.ascom.2025.101013

I.P. Kemp , S.J. Tingay , S.D. Midgely , D.A. Mitchell

{"title":"Experiences of commercial supercomputing in radio astronomy data processing","authors":"I.P. Kemp , S.J. Tingay , S.D. Midgely , D.A. Mitchell","doi":"10.1016/j.ascom.2025.101013","DOIUrl":"10.1016/j.ascom.2025.101013","url":null,"abstract":"<div><div>The ongoing exponential growth of computational power, and the growth of the commercial High Performance Computing (HPC) industry, has led to a point where ten commercial systems currently exceed the performance of the highest-used HPC system in radio astronomy in Australia, and one of these exceeds the expected requirements of the Square Kilometre Array (SKA) Science Data Processors.</div><div>In order to explore implications of this emerging change in the HPC landscape for radio astronomy, we report results from a survey conducted via semi-structured interviews with 14 Australian scientists and providers with experience of commercial HPC in astronomy and similar data intensive fields. We supplement these data with learnings from two earlier studies in which we investigated the application of commercial HPC to radio astronomy data processing, using cases with very different data and processing considerations.</div><div>We use the established qualitative research approach of thematic analysis to extract key messages from our interviews. We find that commercial HPC can provide major advantages in accessibility and availability, and may contribute to increasing researchers’ career productivity. Significant barriers exist, however, including the need for access to increased expertise in systems programming and parallelization, and a need for recognition in research funding. We comment on potential solutions to these issues.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"54 ","pages":"Article 101013"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269552","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}

引用次数: 0

Africanus III. pfb-imaging–A flexible radio interferometric imaging suite 非洲III。pfb成像-一个灵活的无线电干涉成像套件

IF 1.8 4区物理与天体物理

Astronomy and Computing Pub Date : 2026-01-01 Epub Date: 2025-09-11 DOI: 10.1016/j.ascom.2025.100996

H.L. Bester , J.S. Kenyon , A. Repetti , S.J. Perkins , O.M. Smirnov , T. Blecher , Y. Mhiri , J. Roth , I. Heywood , Y. Wiaux , B.V. Hugo

{"title":"Africanus III. pfb-imaging–A flexible radio interferometric imaging suite","authors":"H.L. Bester , J.S. Kenyon , A. Repetti , S.J. Perkins , O.M. Smirnov , T. Blecher , Y. Mhiri , J. Roth , I. Heywood , Y. Wiaux , B.V. Hugo","doi":"10.1016/j.ascom.2025.100996","DOIUrl":"10.1016/j.ascom.2025.100996","url":null,"abstract":"<div><div>The popularity of the CLEAN algorithm in radio interferometric imaging stems from its maturity, speed, and robustness. While many alternatives have been proposed in the literature, none have achieved mainstream adoption by astronomers working with data from interferometric arrays operating in the big data regime. This lack of adoption is largely due to increased computational complexity, absence of mature implementations, and the need for astronomers to tune obscure algorithmic parameters. This work introduces <span>pfb-imaging</span>: a flexible library that implements the scaffolding required to develop and accelerate general radio interferometric imaging algorithms. We demonstrate how the framework can be used to implement a sparsity-based image reconstruction technique known as (unconstrained) SARA in a way that scales with image size rather than data volume and features interpretable algorithmic parameters. The implementation is validated on terabyte-sized data from the MeerKAT telescope, using both a single compute node and Amazon Web Services computing instances.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"54 ","pages":"Article 100996"},"PeriodicalIF":1.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060754","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}

引用次数: 0