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We present our results from training and evaluating a convolutional neural network (CNN) to predict galaxy shapes from wide-field survey images of the first data release of the Dark Energy Survey (DES DR1). We use conventional shape…

Cosmology and Nongalactic Astrophysics · Physics 2019-09-25 Dezső Ribli , László Dobos , István Csabai

Classification of spectra (1) and anomaly detection (2) are fundamental steps to guarantee the highest accuracy in redshift measurements (3) in modern all-sky spectroscopic surveys. We introduce a new Galaxy Spectra Neural Network…

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for…

Exoplanet observations are currently analysed with Bayesian retrieval techniques. Due to the computational load of the models used, a compromise is needed between model complexity and computing time. Analysis of data from future facilities,…

Earth and Planetary Astrophysics · Physics 2022-06-29 Francisco Ardevol Martinez , Michiel Min , Inga Kamp , Paul I. Palmer

The Chinese Space Station Survey Telescope (CSST) will perform a decade-long high-precision wide-field imaging survey that relies on rigorous on-orbit calibration. This necessitates stable celestial benchmark fields to maintain photometric…

Solar and Stellar Astrophysics · Physics 2026-02-13 Chenxiaoji Ling , Juanjuan Ren , Li Shao , Zhimin Zhou , Peng Wei , Youhua Xu , Jinyu Hu , Xin Zhang , Su Yao , Hu Zhan , Chao Liu

The Chinese Space Station Survey Telescope (CSST) presents significant potential for high-precision astrometry. In this study, we show that the point spread function (PSF) modeled by the discrete PSF with Multi-Gaussian function can…

Instrumentation and Methods for Astrophysics · Physics 2025-08-15 Jialu Nie , Peng Wei , Zihuang Cao , Yibo Yan , Chao Liu , Hao Tian , Xin Zhang , Haijun Tian

Landslide susceptibility prediction has always been an important and challenging content. However, there are some uncertain problems to be solved in susceptibility modeling, such as the error of landslide samples and the complex nonlinear…

Machine Learning · Computer Science 2023-10-10 Li Zhu , Lekai Liu , Changshi Yu

The Mini-SiTian (MST) project is a pathfinder for China's next-generation large-scale time-domain survey, SiTian, aimed at discovering variable stars, transients, and explosive events. MST generates hundreds of thousands of transient alerts…

Instrumentation and Methods for Astrophysics · Physics 2025-04-03 Jing-Hang Shi , Hong-Rui Gu , Yang Huang , Yan-Xia Zhang , Peng-Liang Du

The weak gravitational lensing is a powerful tool in modern cosmology. To accurately measure the weak lensing signal, one has to control the systematic bias to a small level. One of the most difficult problems is how to correct the smearing…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-28 Q. Y. Liu , X. Z. Er , Z. H. Fan , D. Z. Liu , G. L. Li , C. L. Wei , Z. Ban , X. B. Li , D. Yue

Accurate theoretical prediction for halo mass function across a broad cosmological space is crucial for the forthcoming China Space Station Telescope (CSST) observations, which will capture cosmological information from multiple probes,…

Cosmology and Nongalactic Astrophysics · Physics 2025-08-18 Zhao Chen , Yu Yu

We developed a convolutional neural network (CNN) model to distinguish the double-lined spectroscopic binaries (SB2s) from others based on single exposure medium-resolution spectra ($R\sim 7,500$). The training set consists of a large set…

Since type Ia Supernovae (SNe) explode in galaxies, they can, in principle, be used as the same tracer of the large-scale structure as their hosts to measure baryon acoustic oscillations (BAOs). To realize this, one must obtain a dense…

Astrophysics · Physics 2009-11-13 Hu Zhan , Lifan Wang , Philip Pinto , J. Anthony Tyson

Uncertainty in biological neural systems appears to be computationally beneficial rather than detrimental. However, in neuromorphic computing systems, device variability often limits performance, including accuracy and efficiency. In this…

Neural and Evolutionary Computing · Computer Science 2026-02-10 Huannan Zheng , Jingli Liu , Kezhou Yang

We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…

Astrophysics of Galaxies · Physics 2020-10-14 Paula Tarrío , Stefano Zarattini

We present a comprehensive forecast for cosmological constraints using the joint observation of the cosmic shear signal from the Chinese Space Station Survey Telescope (CSST) and the clustering signal from the next-generation gravitational…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-24 Pengfei Su , Yan Gong , Qi Xiong , Dingao Hu , Hengjie Lin , Furen Deng , Xuelei Chen

Spectroscopic redshift surveys offer great prospects for constraining the dark sector in cosmology. Future surveys will however be both deep and wide and will thus require an analysis in 3-dimensional spherical geometry. We review and…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-19 Andrina Nicola , Alexandre Refregier , Adam Amara , Aseem Paranjape

Accurate photometric redshifts are among the key requirements for precision weak lensing measurements. Both the large size of the Sloan Digital Sky Survey (SDSS) and the existence of large spectroscopic redshift samples that are…