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More than a void? The detection and characterization of cavities in a simulated galaxy’s interstellar medium
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2025-01-01 DOI: 10.1016/j.ascom.2024.100923
Abolfazl Taghribi , Marco Canducci , Michele Mastropietro , Sven De Rijcke , Reynier Frans Peletier , Peter Tino , Kerstin Bunte
The interstellar medium of galaxies is filled with holes, bubbles, and shells, typically interpreted as remnants of stellar evolution. There is growing interest in the study of their properties to investigate stellar and supernova feedback. So far, the detection of cavities in observational and numerical data is mostly done visually and, hence, is prone to biases. Therefore, we present an automated, objective method for discovering cavities in particle simulations, with demonstrations using hydrodynamical simulations of a dwarf galaxy. The suggested technique extracts holes based on the persistent homology of particle positions and identifies tight boundary points around each. With a synthetic ground-truth analysis, we investigate the relationship between data density and the detection radius, demonstrating that higher data density also allows for the robust detection of smaller cavities. By tracking the boundary points, we can measure the shape and physical properties of the cavity, such as its temperature. In this contribution, we detect 808 holes in 21 simulation snapshots. We classified the holes into supernova-blown bubbles and cavities unrelated to stellar feedback activity based on their temperature profile and expansion behaviour during the 100 million years covered by the simulation snapshots analysed for this work. Surprisingly, less than 40% of the detected cavities can unequivocally be linked to stellar evolution. Moreover, about 36% of the cavities are contracting, while 59% are expanding. The rest do not change for a few million years. Clearly, it is erroneous to interpret observational data based on the premise that all cavities are supernova-related and expanding. This study reveals that supernova-driven bubbles typically exhibit smaller diameters, larger expansion velocities, and lower kinetic ages (with a maximum of 220 million years) compared to other cavities.
{"title":"More than a void? The detection and characterization of cavities in a simulated galaxy’s interstellar medium","authors":"Abolfazl Taghribi ,&nbsp;Marco Canducci ,&nbsp;Michele Mastropietro ,&nbsp;Sven De Rijcke ,&nbsp;Reynier Frans Peletier ,&nbsp;Peter Tino ,&nbsp;Kerstin Bunte","doi":"10.1016/j.ascom.2024.100923","DOIUrl":"10.1016/j.ascom.2024.100923","url":null,"abstract":"<div><div>The interstellar medium of galaxies is filled with holes, bubbles, and shells, typically interpreted as remnants of stellar evolution. There is growing interest in the study of their properties to investigate stellar and supernova feedback. So far, the detection of cavities in observational and numerical data is mostly done visually and, hence, is prone to biases. Therefore, we present an automated, objective method for discovering cavities in particle simulations, with demonstrations using hydrodynamical simulations of a dwarf galaxy. The suggested technique extracts holes based on the persistent homology of particle positions and identifies tight boundary points around each. With a synthetic ground-truth analysis, we investigate the relationship between data density and the detection radius, demonstrating that higher data density also allows for the robust detection of smaller cavities. By tracking the boundary points, we can measure the shape and physical properties of the cavity, such as its temperature. In this contribution, we detect 808 holes in 21 simulation snapshots. We classified the holes into supernova-blown bubbles and cavities unrelated to stellar feedback activity based on their temperature profile and expansion behaviour during the 100 million years covered by the simulation snapshots analysed for this work. Surprisingly, less than 40% of the detected cavities can unequivocally be linked to stellar evolution. Moreover, about 36% of the cavities are contracting, while 59% are expanding. The rest do not change for a few million years. Clearly, it is erroneous to interpret observational data based on the premise that all cavities are supernova-related and expanding. This study reveals that supernova-driven bubbles typically exhibit smaller diameters, larger expansion velocities, and lower kinetic ages (with a maximum of 220 million years) compared to other cavities.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100923"},"PeriodicalIF":1.9,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144117","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}
引用次数: 0
Virtual realities: Is there only one advanced image display that astronomers need?
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2025-01-01 DOI: 10.1016/j.ascom.2024.100896
C.J. Fluke, H.K. Walsh, L. de Zoete Grundy, B. Brady
Data visualisation is an essential ingredient of scientific analysis, discovery, and communication. Along with a human (to do the looking) and the data (something to look at), an image display device is a key component of any data visualisation workflow. For the purpose of this work, standard displays include combinations of laptop displays, peripheral monitors, tablet and smartphone screens, while the main categories of advanced displays are stereoscopic displays, tiled display walls, digital domes, virtual/mixed reality (VR/MR) head-mounted displays, and CAVE/CAVE2-style immersive rooms. We present the results of the second Advanced Image Displays for Astronomy (AIDA) survey, advertised to the membership of the Astronomical Society of Australia (ASA) during June–August 2021. The goal of this survey was to gather background information on the level of awareness and usage of advanced displays in astronomy and astrophysics research. From 17 complete survey responses, sampled from a population of 750 ASA members, we infer that: (1) a high proportion of ASA members use standard displays but do not use advanced displays; (2) a moderate proportion have seen a VR/MR HMD, and may also have used one — but not for research activities; and (3) there is a need for improved knowledge in general about advanced displays, along with relevant software or applications that can target specific science needs. We expect that this is compatible with the experiences of much of the international astronomy and astrophysics research community. We suggest that VR/MR head-mounted displays have now reached a level of technical maturity such that they could be used to replicate or replace the functionality of most other advanced displays.
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引用次数: 0
A high performance multi-band data fusion approach for CSST based on column-oriented database
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-31 DOI: 10.1016/j.ascom.2024.100922
Zhipeng Huang (黄智鹏) , Wei Du (杜薇) , Feng Wang (王锋) , Shoulin Wei (卫守林) , Hui Deng (邓辉) , Ying Mei (梅盈) , Tianmeng Zhang (张天萌)
High-performance multi-catalog fusion or cross-matching has always been an essential issue in astronomical data processing. In this study, we focus on the fusion of multi-band catalog data in a wide-area survey for the China Space Station Telescope (CSST). We implemented a simple and efficient data fusion method based on column-oriented database technology to produce a more consistent and accurate catalog, and this method can carry out the fusion of millions of source records in a few dozen seconds. We analyze and discuss several significant issues related to data fusion, such as the spatial partitioning and indexing of the target sky regions, the efficient implementation of fusion based on joining in the database, and the segmented processing method to address the issue of missing sources at different declinations. The performance profiling results show that by employing the MergeTree table engine within ClickHouse, establishing high-speed indexes based on the spatial partition index number, adopting an appropriate partitioning strategy, and maintaining orderly storage of records in the database according to the spatial partition index number, the efficient fusion of astronomical catalogs can be accomplished through SQL statements. Performance tests show that the proposed method can fulfill CSST data processing requirements, and it is also of reference value for future work related to massive astronomical data fusion. Compared with data fusion systems such as Large Survey DataBase (LSDB), our method can achieve similar performance results with consistent results.
{"title":"A high performance multi-band data fusion approach for CSST based on column-oriented database","authors":"Zhipeng Huang (黄智鹏) ,&nbsp;Wei Du (杜薇) ,&nbsp;Feng Wang (王锋) ,&nbsp;Shoulin Wei (卫守林) ,&nbsp;Hui Deng (邓辉) ,&nbsp;Ying Mei (梅盈) ,&nbsp;Tianmeng Zhang (张天萌)","doi":"10.1016/j.ascom.2024.100922","DOIUrl":"10.1016/j.ascom.2024.100922","url":null,"abstract":"<div><div>High-performance multi-catalog fusion or cross-matching has always been an essential issue in astronomical data processing. In this study, we focus on the fusion of multi-band catalog data in a wide-area survey for the China Space Station Telescope (CSST). We implemented a simple and efficient data fusion method based on column-oriented database technology to produce a more consistent and accurate catalog, and this method can carry out the fusion of millions of source records in a few dozen seconds. We analyze and discuss several significant issues related to data fusion, such as the spatial partitioning and indexing of the target sky regions, the efficient implementation of fusion based on joining in the database, and the segmented processing method to address the issue of missing sources at different declinations. The performance profiling results show that by employing the MergeTree table engine within ClickHouse, establishing high-speed indexes based on the spatial partition index number, adopting an appropriate partitioning strategy, and maintaining orderly storage of records in the database according to the spatial partition index number, the efficient fusion of astronomical catalogs can be accomplished through SQL statements. Performance tests show that the proposed method can fulfill CSST data processing requirements, and it is also of reference value for future work related to massive astronomical data fusion. Compared with data fusion systems such as Large Survey DataBase (LSDB), our method can achieve similar performance results with consistent results.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100922"},"PeriodicalIF":1.9,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144128","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
Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-18 DOI: 10.1016/j.ascom.2024.100921
S. Rezaei , A. Chegeni , A. Javadpour , A. VafaeiSadr , L. Cao , H. Röttgering , M. Staring
This paper explores how artificial intelligence (AI) techniques can address common challenges in astronomy and (bio)medical imaging. It focuses on applying convolutional neural networks (CNNs) and other AI methods to tasks such as image reconstruction, object detection, anomaly detection, and generative modeling. Drawing parallels between domains like MRI and radio astronomy, the paper highlights the critical role of AI in producing high-quality image reconstructions and reducing artifacts. Generative models are examined as versatile tools for tackling challenges such as data scarcity and privacy concerns in medicine, as well as managing the vast and complex datasets found in astrophysics. Anomaly detection is also discussed, with an emphasis on unsupervised learning approaches that address the difficulties of working with large, unlabeled datasets. Furthermore, the paper explores the use of reinforcement learning to enhance CNN performance through automated hyperparameter optimization and adaptive decision-making in dynamic environments. The focus of this paper remains strictly on AI applications, without addressing the synergies between measurement techniques or the core algorithms specific to each field.
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引用次数: 0
BIPP: An efficient HPC implementation of the Bluebild algorithm for radio astronomy
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-15 DOI: 10.1016/j.ascom.2024.100920
E. Tolley , S. Frasch , E. Orliac , S. Krishna , M. Bianco , S. Kashani , P. Hurley , M. Simeoni , J.-P. Kneib
The Bluebild algorithm is a new technique for image synthesis in radio astronomy which decomposes the sky into distinct energy levels using functional principal component analysis. These levels can be linearly combined to construct a least-squares estimate of the radio sky, i.e. minimizing the residuals between measured and predicted visibilities. This approach is particularly useful for deconvolution-free imaging or for scientific applications that need to filter specific energy levels. We present an HPC implementation of the Bluebild algorithm for radio-interferometric imaging: Bluebild Imaging++ (BIPP). The library features interfaces to C++, C and Python and is designed with seamless GPU acceleration in mind. We evaluate the accuracy and performance of BIPP on simulated observations of the upcoming Square Kilometer Array Observatory and real data from the Low-Frequency Array (LOFAR) telescope. We find that BIPP offers accurate wide-field imaging and has competitive execution time with respect to the interferometric imaging libraries CASA and WSClean for images with 106 pixels. Furthermore, due to the energy level decomposition, images produced with BIPP can reveal information about faint and diffuse structures before any cleaning iterations. BIPP does not perform any regularization, but we suggest methods to integrate the output of BIPP with CLEAN. The source code of BIPP is publicly released.
{"title":"BIPP: An efficient HPC implementation of the Bluebild algorithm for radio astronomy","authors":"E. Tolley ,&nbsp;S. Frasch ,&nbsp;E. Orliac ,&nbsp;S. Krishna ,&nbsp;M. Bianco ,&nbsp;S. Kashani ,&nbsp;P. Hurley ,&nbsp;M. Simeoni ,&nbsp;J.-P. Kneib","doi":"10.1016/j.ascom.2024.100920","DOIUrl":"10.1016/j.ascom.2024.100920","url":null,"abstract":"<div><div>The Bluebild algorithm is a new technique for image synthesis in radio astronomy which decomposes the sky into distinct energy levels using functional principal component analysis. These levels can be linearly combined to construct a least-squares estimate of the radio sky, i.e. minimizing the residuals between measured and predicted visibilities. This approach is particularly useful for deconvolution-free imaging or for scientific applications that need to filter specific energy levels. We present an HPC implementation of the Bluebild algorithm for radio-interferometric imaging: Bluebild Imaging++ (<span>BIPP</span>). The library features interfaces to C++, C and Python and is designed with seamless GPU acceleration in mind. We evaluate the accuracy and performance of <span>BIPP</span> on simulated observations of the upcoming Square Kilometer Array Observatory and real data from the Low-Frequency Array (LOFAR) telescope. We find that <span>BIPP</span> offers accurate wide-field imaging and has competitive execution time with respect to the interferometric imaging libraries <span>CASA</span> and <span>WSClean</span> for images with <span><math><mrow><mo>≤</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>6</mn></mrow></msup></mrow></math></span> pixels. Furthermore, due to the energy level decomposition, images produced with <span>BIPP</span> can reveal information about faint and diffuse structures before any cleaning iterations. <span>BIPP</span> does not perform any regularization, but we suggest methods to integrate the output of <span>BIPP</span> with CLEAN. The source code of <span>BIPP</span> is publicly released.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100920"},"PeriodicalIF":1.9,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144112","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}
引用次数: 0
Real-bogus scores for active anomaly detection
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-11 DOI: 10.1016/j.ascom.2024.100919
T.A. Semenikhin , M.V. Kornilov , M.V. Pruzhinskaya , A.D. Lavrukhina , E. Russeil , E. Gangler , E.E.O. Ishida , V.S. Korolev , K.L. Malanchev , A.A. Volnova , S. Sreejith , SNAD team
In the task of anomaly detection in modern time-domain photometric surveys, the primary goal is to identify astrophysically interesting, rare, and unusual objects among a large volume of data. Unfortunately, artifacts — such as plane or satellite tracks, bad columns on CCDs, and ghosts — often constitute significant contaminants in results from anomaly detection analysis. In such contexts, the Active Anomaly Discovery (AAD) algorithm allows tailoring the output of anomaly detection pipelines according to what the expert judges to be scientifically interesting. We demonstrate how the introduction real-bogus scores, obtained from a machine learning classifier, improves the results from AAD. Using labeled data from the SNAD ZTF knowledge database, we train four real-bogus classifiers: XGBoost, CatBoost, Random Forest, and Extremely Randomized Trees. All the models perform real-bogus classification with similar effectiveness, achieving ROC-AUC scores ranging from 0.93 to 0.95. Consequently, we select the Random Forest model as the main model due to its simplicity and interpretability. The Random Forest classifier is applied to 67 million light curves from ZTF DR17. The output real-bogus score is used as an additional feature for two anomaly detection algorithms: static Isolation Forest and AAD. The number of artifacts detected by both algorithms decreases significantly with the inclusion of the real-bogus score in cases where the feature space regions are densely populated with artifacts. However, it remains almost unchanged in scenarios where the overall number of artifacts in the outputs is already small. We conclude that incorporating the real-bogus classifier result as an additional feature in the active anomaly detection pipeline reduces the number of artifacts in the outputs, thereby increasing the incidence of astrophysically interesting objects presented to human experts.
{"title":"Real-bogus scores for active anomaly detection","authors":"T.A. Semenikhin ,&nbsp;M.V. Kornilov ,&nbsp;M.V. Pruzhinskaya ,&nbsp;A.D. Lavrukhina ,&nbsp;E. Russeil ,&nbsp;E. Gangler ,&nbsp;E.E.O. Ishida ,&nbsp;V.S. Korolev ,&nbsp;K.L. Malanchev ,&nbsp;A.A. Volnova ,&nbsp;S. Sreejith ,&nbsp;SNAD team","doi":"10.1016/j.ascom.2024.100919","DOIUrl":"10.1016/j.ascom.2024.100919","url":null,"abstract":"<div><div>In the task of anomaly detection in modern time-domain photometric surveys, the primary goal is to identify astrophysically interesting, rare, and unusual objects among a large volume of data. Unfortunately, artifacts — such as plane or satellite tracks, bad columns on CCDs, and ghosts — often constitute significant contaminants in results from anomaly detection analysis. In such contexts, the Active Anomaly Discovery (AAD) algorithm allows tailoring the output of anomaly detection pipelines according to what the expert judges to be scientifically interesting. We demonstrate how the introduction real-bogus scores, obtained from a machine learning classifier, improves the results from AAD. Using labeled data from the SNAD ZTF knowledge database, we train four real-bogus classifiers: XGBoost, CatBoost, Random Forest, and Extremely Randomized Trees. All the models perform real-bogus classification with similar effectiveness, achieving ROC-AUC scores ranging from 0.93 to 0.95. Consequently, we select the Random Forest model as the main model due to its simplicity and interpretability. The Random Forest classifier is applied to 67 million light curves from ZTF DR17. The output real-bogus score is used as an additional feature for two anomaly detection algorithms: static Isolation Forest and AAD. The number of artifacts detected by both algorithms decreases significantly with the inclusion of the real-bogus score in cases where the feature space regions are densely populated with artifacts. However, it remains almost unchanged in scenarios where the overall number of artifacts in the outputs is already small. We conclude that incorporating the real-bogus classifier result as an additional feature in the active anomaly detection pipeline reduces the number of artifacts in the outputs, thereby increasing the incidence of astrophysically interesting objects presented to human experts.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100919"},"PeriodicalIF":1.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144116","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
RatanSunPy: A robust preprocessing pipeline for RATAN-600 solar radio observations data
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-09 DOI: 10.1016/j.ascom.2024.100918
I. Knyazeva , I. Lysov , E. Kurochkin , A. Shendrik , D. Derkach , N. Makarenko
The advancement of observational technologies and software for processing and visualizing spectro-polarimetric microwave data obtained with the RATAN-600 radio telescope opens new opportunities for studying the physical characteristics of solar plasma at the levels of the chromosphere and corona. These levels remain some difficult to detect in the ultraviolet and X-ray ranges. The development of such methods allows for more precise investigation of the fine structure and dynamics of the solar atmosphere, thereby deepening our understanding of the processes occurring in these layers. The obtained data also can be utilized for diagnosing solar plasma and forecasting solar activity. However, using RATAN-600 data requires extensive data processing and familiarity with the RATAN-600. This paper introduces RatanSunPy, an open-source Python package developed for accessing, visualizing, and analyzing multi-band radio observations of the Sun from the RATAN-600 solar complex. The package offers comprehensive data processing functionalities, including direct access to raw data, essential processing steps such as calibration and quiet Sun normalization, and tools for analyzing solar activity. This includes automatic detection of local sources, identifying them with NOAA (National Oceanic and Atmospheric Administration) active regions, and further determining parameters for local sources and active regions. By streamlining data processing workflows, RatanSunPy enables researchers to investigate the fine structure and dynamics of the solar atmosphere more efficiently, contributing to advancements in solar physics and space weather forecasting.
{"title":"RatanSunPy: A robust preprocessing pipeline for RATAN-600 solar radio observations data","authors":"I. Knyazeva ,&nbsp;I. Lysov ,&nbsp;E. Kurochkin ,&nbsp;A. Shendrik ,&nbsp;D. Derkach ,&nbsp;N. Makarenko","doi":"10.1016/j.ascom.2024.100918","DOIUrl":"10.1016/j.ascom.2024.100918","url":null,"abstract":"<div><div>The advancement of observational technologies and software for processing and visualizing spectro-polarimetric microwave data obtained with the RATAN-600 radio telescope opens new opportunities for studying the physical characteristics of solar plasma at the levels of the chromosphere and corona. These levels remain some difficult to detect in the ultraviolet and X-ray ranges. The development of such methods allows for more precise investigation of the fine structure and dynamics of the solar atmosphere, thereby deepening our understanding of the processes occurring in these layers. The obtained data also can be utilized for diagnosing solar plasma and forecasting solar activity. However, using RATAN-600 data requires extensive data processing and familiarity with the RATAN-600. This paper introduces <span>RatanSunPy</span>, an open-source Python package developed for accessing, visualizing, and analyzing multi-band radio observations of the Sun from the RATAN-600 solar complex. The package offers comprehensive data processing functionalities, including direct access to raw data, essential processing steps such as calibration and quiet Sun normalization, and tools for analyzing solar activity. This includes automatic detection of local sources, identifying them with NOAA (National Oceanic and Atmospheric Administration) active regions, and further determining parameters for local sources and active regions. By streamlining data processing workflows, <span>RatanSunPy</span> enables researchers to investigate the fine structure and dynamics of the solar atmosphere more efficiently, contributing to advancements in solar physics and space weather forecasting.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100918"},"PeriodicalIF":1.9,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144111","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
Thermodynamic topology of Hot NUT-Kerr-Newman-Kasuya-Anti-de Sitter black hole
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-09 DOI: 10.1016/j.ascom.2024.100900
M.U. Shahzad , Nazek Alessa , A. Mehmood , R. Javed
This work is devoted to studying the thermodynamic topology of Hot Nut-Kerr-Newman-Kasuya-AdS black holes (BHs). To accomplish this, we identify the critical points that play a crucial role in understanding the intricate structure of these BHs. We determine these critical points’ associated topological charges, providing important information about the underlying topology. Furthermore, we explore the concept of zero points and their corresponding winding numbers. These calculations allow us to evaluate the topological number associated with BHs and provide important information about their overall topological characteristics. One of the most important characteristics is the triple critical point. These points support the conjecture that the behavior of BHs undergoes significant transformations, presenting us with unique opportunities to observe and comprehend novel physical phenomena. A winding number of zero corresponds to a simple, connected horizon, while non-zero winding numbers indicate more complex topologies, such as multi-sheeted horizons. For comprehensive analysis, we fixed various parameters, such as the electric and magnetic charges and the electric and magnetic potentials. This approach allows us to isolate and examine specific aspects of BH topology.
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引用次数: 0
Thermodynamic topology of Phantom AdS black holes in massive gravity via non-extensive entropies
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-12-02 DOI: 10.1016/j.ascom.2024.100909
Abdelhay Salah Mohamed , M.U. Shahzad , A. Mehmood , E.E. Zotos
In this study, we explore the topological numbers associated with Phantom AdS black holes (BHs) in massive gravity using non-extensive entropies. We analyze their characteristics using various entropy measures, including the Bekenstein–Hawking entropy, Rényi entropy, Barrows entropy, Sharma-Mittal entropy, and the logarithmic-corrected entropy. We observe that the calculated topological number (T) varies across different entropy measures. Nevertheless, what is particularly intriguing is the persistent coherence in the topological classification of BH, regardless of whether we consider the Rényi entropy, the logarithmic-corrected entropy or the Bekenstein–Hawking entropy.
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引用次数: 0
New crescent moon detection using Circular Hough Transform (CHT)
IF 1.9 4区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-11-30 DOI: 10.1016/j.ascom.2024.100902
A.L.A.M. Nasir , R. Umar , W.N.J.W. Yussof , N. Ahmad , A.N. Zulkeflee , N.H. Sabri , W.M.Y.W. Chik , N.A. Mahiddin , A.H. Bely , A.I.S. Izdihar
Over 1.5 billion Muslims worldwide rely on a calendar based on the observation of the new crescent moon, particularly during the Hijri calendar months of Ramadhan, Shawal, and Zulhijjah. Accurately detecting the new crescent moon immediately after its conjunction is essential for ensuring the precision of the calendar, but it poses a technical challenge due to the low contrast between the new crescent moon and its background. This study aimed to solve the challenge of reliably identifying the new crescent moon at this critical phase, which is vital for accurately determining important dates that signify religious events. It intended to create and verify a computer vision model that would greatly improves the precision and efficiency of identifying a new crescent moon based on images. This will assist in precisely identifying important dates relevant to Muslim religious practices. The methodology employs image preprocessing techniques such as Gaussian Blur for image smoothing and Adaptive Thresholding for contrast enhancement to optimize the visibility of the crescent moon in a single image. The Circular Hough Transform (CHT) technique was used to accurately detect the new crescent moon, while the OpenCV software package helped to implement all of these methods, thus, providing a strong foundation for precisely identifying the new crescent moon. Findings of this study, which involved observations at Kolej Ugama Sultan Zainal Abidin (KUSZA) Observatory, Teluk Kemang Observatory, and Miri Observatory, indicate that the utilization of image processing techniques results in significant improvements in both the efficiency and precision of identifying and detecting the new crescent moon. These enhancements exceed the performance of conventional digital imaging methods employed during regular observations. The model’s processing rate surpasses the usual observation efficiency and showcases exceptional accuracy in distinguishing images that feature the new crescent moon from those that do not. In conclusion, the proposed model demonstrates an effective and efficient methodology for improving the precision of lunar calendar management and the quick planning of important Islamic religious events in accordance with the lunar cycle. This technological advancement offers a reliable method for accurately seeing the crescent moon, which has important implications for enhancing the precision of lunar-based calendars and coordinating important Islamic religious occasions.
{"title":"New crescent moon detection using Circular Hough Transform (CHT)","authors":"A.L.A.M. Nasir ,&nbsp;R. Umar ,&nbsp;W.N.J.W. Yussof ,&nbsp;N. Ahmad ,&nbsp;A.N. Zulkeflee ,&nbsp;N.H. Sabri ,&nbsp;W.M.Y.W. Chik ,&nbsp;N.A. Mahiddin ,&nbsp;A.H. Bely ,&nbsp;A.I.S. Izdihar","doi":"10.1016/j.ascom.2024.100902","DOIUrl":"10.1016/j.ascom.2024.100902","url":null,"abstract":"<div><div>Over 1.5 billion Muslims worldwide rely on a calendar based on the observation of the new crescent moon, particularly during the Hijri calendar months of Ramadhan, Shawal, and Zulhijjah. Accurately detecting the new crescent moon immediately after its conjunction is essential for ensuring the precision of the calendar, but it poses a technical challenge due to the low contrast between the new crescent moon and its background. This study aimed to solve the challenge of reliably identifying the new crescent moon at this critical phase, which is vital for accurately determining important dates that signify religious events. It intended to create and verify a computer vision model that would greatly improves the precision and efficiency of identifying a new crescent moon based on images. This will assist in precisely identifying important dates relevant to Muslim religious practices. The methodology employs image preprocessing techniques such as Gaussian Blur for image smoothing and Adaptive Thresholding for contrast enhancement to optimize the visibility of the crescent moon in a single image. The Circular Hough Transform (CHT) technique was used to accurately detect the new crescent moon, while the OpenCV software package helped to implement all of these methods, thus, providing a strong foundation for precisely identifying the new crescent moon. Findings of this study, which involved observations at Kolej Ugama Sultan Zainal Abidin (KUSZA) Observatory, Teluk Kemang Observatory, and Miri Observatory, indicate that the utilization of image processing techniques results in significant improvements in both the efficiency and precision of identifying and detecting the new crescent moon. These enhancements exceed the performance of conventional digital imaging methods employed during regular observations. The model’s processing rate surpasses the usual observation efficiency and showcases exceptional accuracy in distinguishing images that feature the new crescent moon from those that do not. In conclusion, the proposed model demonstrates an effective and efficient methodology for improving the precision of lunar calendar management and the quick planning of important Islamic religious events in accordance with the lunar cycle. This technological advancement offers a reliable method for accurately seeing the crescent moon, which has important implications for enhancing the precision of lunar-based calendars and coordinating important Islamic religious occasions.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100902"},"PeriodicalIF":1.9,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144108","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
期刊
Astronomy and Computing
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