Astronomy and Computing最新文献

{"title":"DCAPPSO: A novel approach for inverting asteroid rotational properties with applications to DAMIT and Tianwen-2 target asteroid","authors":"Yong-Xiong Zhang ,&nbsp;Wen-Xiu Guo ,&nbsp;Hua Zheng ,&nbsp;Wei-Lin Wang","doi":"10.1016/j.ascom.2024.100925","DOIUrl":"10.1016/j.ascom.2024.100925","url":null,"abstract":"<div><div>This paper introduces the Dynamic Coefficient Adjustment in Parallel Particle Swarm Optimization (DCAPPSO) algorithm for inverting asteroid rotational properties from lightcurve data. DCAPPSO integrates a Cellinoid shape model with Particle Swarm Optimization (PSO), dynamic coefficient adjustment, and parallel computing, offering improved efficiency and accuracy in asteroid parameter determination. The algorithm’s performance was evaluated using simulated asteroid lightcurves and applied to 24 real asteroids from the DAMIT database, including a detailed case study of asteroid (44)Nysa and an additional discussion of asteroid (433)Eros. Results show excellent consistency with established rotational periods, with uncertainties typically ranging from ± 0.000018 to ± 0.009981 h. Pole orientation determinations demonstrate good agreement, particularly for latitude components. The algorithm’s parallel implementation achieves a speedup of 48.617x with 100 workers on multicore CPUs. DCAPPSO was also applied to asteroid (469219) Kamo’oalewa, the Tianwen-2 mission target, providing new insights into its shape and rotational properties. For Kamo’oalewa, the algorithm derived a rotational period of <span><math><mrow><mn>0</mn><mo>.</mo><mn>460510</mn><mspace></mspace><mi>h</mi></mrow></math></span> (27.63 min) and a pole orientation of <span><math><mrow><mo>(</mo><mn>134</mn><mo>.</mo><mn>67</mn><mo>°</mo><mo>,</mo><mo>−</mo><mn>11</mn><mo>.</mo><mn>39</mn><mo>°</mo><mo>)</mo></mrow></math></span>. Uncertainty analysis yielded estimates of <span><math><mrow><mn>133</mn><mo>.</mo><mn>52</mn><mo>°</mo><mo>±</mo><mn>0</mn><mo>.</mo><mn>01</mn><mo>°</mo></mrow></math></span> for pole longitude, <span><math><mrow><mo>−</mo><mn>10</mn><mo>.</mo><mn>67</mn><mo>°</mo><mo>±</mo><mn>0</mn><mo>.</mo><mn>05</mn><mo>°</mo></mrow></math></span> for pole latitude, and 0.466017 ± 0.006090 h for the rotational period. Shape analysis indicates a moderately elongated form with axis ratios <span><math><mrow><mi>b</mi><mo>/</mo><mi>a</mi><mo>≈</mo><mn>0</mn><mo>.</mo><mn>67</mn></mrow></math></span> and <span><math><mrow><mi>c</mi><mo>/</mo><mi>a</mi><mo>≈</mo><mn>0</mn><mo>.</mo><mn>56</mn></mrow></math></span>. This research advances asteroid inversion techniques, offering an efficient tool to address increasing observational data volumes in planetary science.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100925"},"PeriodicalIF":1.9,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144127","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":"Cosmological behavior of a hyperbolic solution in f(Q) gravity","authors":"K. Haloi,&nbsp;R. Roy Baruah","doi":"10.1016/j.ascom.2024.100926","DOIUrl":"10.1016/j.ascom.2024.100926","url":null,"abstract":"<div><div>In this work, we study the universe’s dynamics in the context of f(Q) gravity by use of a flat FLRW model. Two particular forms are considered: <span><math><mrow><mi>f</mi><mrow><mo>(</mo><mi>Q</mi><mo>)</mo></mrow><mo>=</mo><mi>Q</mi><mo>−</mo><mi>λ</mi><mi>Q</mi></mrow></math></span> and <span><math><mrow><mi>f</mi><mrow><mo>(</mo><mi>Q</mi><mo>)</mo></mrow><mo>=</mo><mi>Q</mi><mo>−</mo><mi>λ</mi><msup><mrow><mi>Q</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span>, where Q and <span><math><mi>λ</mi></math></span> represent the nonmetricity and arbitrary constant, respectively. We take a special form for the scale factor, <span><math><mrow><mi>a</mi><mo>=</mo><mi>s</mi><mi>i</mi><mi>n</mi><mi>h</mi><msup><mrow><mrow><mo>(</mo><mi>t</mi><mo>)</mo></mrow></mrow><mrow><mfrac><mrow><mn>1</mn></mrow><mrow><mi>α</mi></mrow></mfrac></mrow></msup></mrow></math></span>, to solve the Friedmann field equations within the f(Q) formalism. The scale factor’s behavior is here determined by the model parameter <span><math><mi>α</mi></math></span>. In our model, we primarily analyze the behavior of the equation of state parameter <span><math><mi>ω</mi></math></span>. We examine the scalar field and examine the resultant solution’s energy conditions. We use a number of diagnostic techniques, including the Jerk, Om, and statefinder diagnostic tools, to validate our model. We also include the observational constraints from the BAO and Hubble databases. A thorough explanation of the outcomes and the model is given.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100926"},"PeriodicalIF":1.9,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144125","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":"Observational constraints on quark and strange quark matters in f(R,T) theory of gravity","authors":"D.D. Pawar ,&nbsp;N.G. Ghungarwar ,&nbsp;Shah Muhammad ,&nbsp;E. Zotos","doi":"10.1016/j.ascom.2024.100924","DOIUrl":"10.1016/j.ascom.2024.100924","url":null,"abstract":"<div><div>We have examined a plane symmetric cosmological model in the presence of quark and strange quark matter with the help of <span><math><mrow><mi>f</mi><mrow><mo>(</mo><mi>R</mi><mo>,</mo><mi>T</mi><mo>)</mo></mrow></mrow></math></span> theory of gravity. To find solutions for this type of space–time, we applied a power-law relationship between the scale factor and the deceleration parameter. We used a variable deceleration parameter. We applied constraints on the parameters using the <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> test and obtained the best-fit values for the Hubble parameter <span><math><mrow><mi>H</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow></mrow></math></span> using 57 observed data points, achieving an <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> value of 0.9321 and an RMSE of 11.0716. The best-fit parameters were <span><math><mrow><mi>α</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>54</mn><msubsup><mrow><mn>2</mn></mrow><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>022</mn></mrow><mrow><mo>+</mo><mn>0</mn><mo>.</mo><mn>019</mn></mrow></msubsup></mrow></math></span>, <span><math><mrow><mi>β</mi><mo>=</mo><mn>52</mn><mo>.</mo><msubsup><mrow><mn>9</mn></mrow><mrow><mo>−</mo><mn>2</mn><mo>.</mo><mn>7</mn></mrow><mrow><mo>+</mo><mn>2</mn><mo>.</mo><mn>3</mn></mrow></msubsup></mrow></math></span>, and <span><math><mrow><msub><mrow><mi>c</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>=</mo><mo>−</mo><mn>0</mn><mo>.</mo><mn>87</mn><msubsup><mrow><mn>7</mn></mrow><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>058</mn></mrow><mrow><mo>+</mo><mn>0</mn><mo>.</mo><mn>055</mn></mrow></msubsup></mrow></math></span>, resulting in <span><math><mrow><msub><mrow><mi>H</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>=</mo><mn>64</mn><mo>.</mo><mn>3</mn><msubsup><mrow><mn>9</mn></mrow><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>47</mn></mrow><mrow><mo>+</mo><mn>0</mn><mo>.</mo><mn>04</mn></mrow></msubsup><mspace></mspace><mtext>km/s/Mpc</mtext></mrow></math></span>. These results show that our model closely matches the <span><math><mi>Λ</mi></math></span>CDM model, demonstrating its accuracy in describing the universe’s expansion history across the given redshift range. We also discussed cosmological parameters such as spatial volume, the mean anisotropic parameter, the shear scalar, deceleration parameter, energy density and pressure for quark matter and strange quark matter for plane symmetric spacetime.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100924"},"PeriodicalIF":1.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144118","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":"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}

{"title":"Virtual realities: Is there only one advanced image display that astronomers need?","authors":"C.J. Fluke,&nbsp;H.K. Walsh,&nbsp;L. de Zoete Grundy,&nbsp;B. Brady","doi":"10.1016/j.ascom.2024.100896","DOIUrl":"10.1016/j.ascom.2024.100896","url":null,"abstract":"<div><div>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 <span><math><mrow><mo>∼</mo><mn>750</mn></mrow></math></span> 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.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"50 ","pages":"Article 100896"},"PeriodicalIF":1.9,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137147","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":"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}

{"title":"Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy","authors":"S. Rezaei ,&nbsp;A. Chegeni ,&nbsp;A. Javadpour ,&nbsp;A. VafaeiSadr ,&nbsp;L. Cao ,&nbsp;H. Röttgering ,&nbsp;M. Staring","doi":"10.1016/j.ascom.2024.100921","DOIUrl":"10.1016/j.ascom.2024.100921","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100921"},"PeriodicalIF":1.9,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144113","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":"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}

{"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}

{"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}