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Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has…

Instrumentation and Methods for Astrophysics · Physics 2024-04-01 Verlon Etsebeth , Michelle Lochner , Mike Walmsley , Margherita Grespan

We carry out a search for strong-lens systems containing high-redshift lens galaxies with the goal of extending strong-lensing-assisted galaxy evolutionary studies to earlier cosmic time. Two strong-lens classifiers are constructed from a…

We present the first step toward deriving cosmological constraints through the abundances of galaxy clusters selected in a $510\,\mathrm{deg}^2$ weak-lensing aperture mass map, constructed with the Year-Three shear catalog from the Hyper…

How can we discover objects we did not know existed within the large datasets that now abound in astronomy? We present an outlier detection algorithm that we developed, based on an unsupervised Random Forest. We test the algorithm on more…

Astrophysics of Galaxies · Physics 2017-01-11 Dalya Baron , Dovi Poznanski

The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection method using a Wasserstein generative adversarial network…

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning…

Computational Engineering, Finance, and Science · Computer Science 2015-05-29 Isadora Nun , Karim Pichara , Pavlos Protopapas , Dae-Won Kim

Anomaly detection is the task of identifying abnormal behavior of a system. Anomaly detection in computational workflows is of special interest because of its wide implications in various domains such as cybersecurity, finance, and social…

Machine Learning · Computer Science 2023-10-03 Hongwei Jin , Krishnan Raghavan , George Papadimitriou , Cong Wang , Anirban Mandal , Ewa Deelman , Prasanna Balaprakash

We present the first results of a pilot X-ray study of 37 rich galaxy clusters at $0.1<z<1.1$ in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) field. Diffuse X-ray emissions from these clusters were serendipitously detected in…

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is a deep wide-field multi-band imaging survey consisting of three layers (Wide, Deep, and UltraDeep), with the Wide layer covering $\sim 1470$ deg$^2$ to a depth of $i \sim 26$ mag.…

Astrophysics of Galaxies · Physics 2025-11-19 Rui Zhu , Xue-Bing Wu , Yuxuan Pang , Yuming Fu

Low surface brightness substructures around galaxies, known as tidal features, are a valuable tool in the detection of past or ongoing galaxy mergers. Their properties can answer questions about the progenitor galaxies involved in the…

Astrophysics of Galaxies · Physics 2023-07-12 Alice Desmons , Sarah Brough , Francois Lanusse

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP…

This study investigates the role of large-scale environments on the fraction of spiral galaxies at $z=$ 0.3-0.6 sliced to three redshift bins of $\Delta z=0.1$. Here, we sample 276220 massive galaxies in a limited stellar mass of…

Astrophysics of Galaxies · Physics 2021-10-27 Rhythm Shimakawa , Takumi S. Tanaka , Seiji Toshikage , Masayuki Tanaka

Recently, anomaly detection and localization in multimedia data have received significant attention among the machine learning community. In real-world applications such as medical diagnosis and industrial defect detection, anomalies only…

Computer Vision and Pattern Recognition · Computer Science 2022-05-16 Chaoqin Huang , Qinwei Xu , Yanfeng Wang , Yu Wang , Ya Zhang

Every field of Science is undergoing unprecedented changes in the discovery process, and Astronomy has been a main player in this transition since the beginning. The ongoing and future large and complex multi-messenger sky surveys impose a…

Instrumentation and Methods for Astrophysics · Physics 2021-05-12 Maurizio D'Addona , Giuseppe Riccio , Stefano Cavuoti , Crescenzo Tortora , Massimo Brescia

Subaru Strategic Program with the Hyper-Suprime Cam (HSC-SSP) has proven to be successful with its extremely-wide area coverage in past years. Taking advantages of this feature, we report initial results from exploration and research of…

Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in…

Astrophysics of Galaxies · Physics 2017-12-12 A. Solarz , M. Bilicki , A. Pollo

We present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the $\sim 160$~deg$^2$ area surveyed by Hyper Suprime-Cam (HSC) as a Subaru Strategic Program. HSC is a new prime focus optical…

We present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the three-year (Y3)…

Low surface brightness substructures around galaxies, known as tidal features, are a valuable tool in the detection of past or ongoing galaxy mergers, and their properties can answer questions about the progenitor galaxies involved in the…

Astrophysics of Galaxies · Physics 2024-06-06 Alice Desmons , Sarah Brough , Francois Lanusse

Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up…

Instrumentation and Methods for Astrophysics · Physics 2023-08-03 Vanessa Böhm , Alex G. Kim , Stéphanie Juneau
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