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Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by…

Materials Science · Physics 2021-06-03 Nik Dennler , Antonio Foncubierta-Rodriguez , Titus Neupert , Marilyne Sousa

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep…

Dense depth estimation from a single image is a key problem in computer vision, with exciting applications in a multitude of robotic tasks. Initially viewed as a direct regression problem, requiring annotated labels as supervision at…

Computer Vision and Pattern Recognition · Computer Science 2019-11-20 Vitor Guizilini , Jie Li , Rares Ambrus , Sudeep Pillai , Adrien Gaidon

Metallic mesh is a transparent electromagnetic shielding film with a fine metal line structure. However, it can develop defects that affect the optoelectronic performance whether in the production preparation or in actual use. The…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Zhengang Lu , Hongsheng Qin , Jing Li , Ming Sun , Jiubin Tan

Although measuring the gas metallicity in galaxies at various redshifts is crucial to constrain galaxy evolutionary scenarios, only rest-frame optical emission lines have been generally used to measure the metallicity. This has prevented us…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Tohru Nagao , Roberto Maiolino , Alessandro Marconi , Hideo Matsuhara

The China Space Station Telescope (CSST) will conduct a deep and wide imaging survey in the NUV-, u-, g-, r-, i-, z-, and y-bands. In this work, using theoretical data synthesized from the BOSZ spectra of Bohlin et al. (2017), along with…

Solar and Stellar Astrophysics · Physics 2025-11-04 Xue Lu , Haibo Yuan , Kai Xiao , Bowen Huang , Ruoyi Zhang , Lin Yang , Timothy C. Beers , Shuai Xu

We study the problem of supervised learning a metric space under discriminative constraints. Given a universe $X$ and sets ${\cal S}, {\cal D}\subset {X \choose 2}$ of similar and dissimilar pairs, we seek to find a mapping $f:X\to Y$, into…

Computational Geometry · Computer Science 2019-03-20 Diego Ihara Centurion , Neshat Mohammadi , Anastasios Sidiropoulos

Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method's efficiency, but also to understand what…

Astrophysics of Galaxies · Physics 2023-01-25 L. E. Suelves , W. J. Pearson , A. Pollo

Local measurements of the Hubble constant ($H_0$) based on Cepheids e Type Ia supernova differ by $\approx 5 \sigma$ from the estimated value of $H_0$ from Planck CMB observations under $\Lambda$CDM assumptions. In order to better…

Cosmology and Nongalactic Astrophysics · Physics 2023-07-07 Carlos Bengaly , Maria Aldinez Dantas , Luciano Casarini , Jailson Alcaniz

Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is…

Instrumentation and Methods for Astrophysics · Physics 2025-06-03 Ibrahim A. Almosallam , Sam N. Lindsay , Matt J. Jarvis , Stephen J. Roberts

We present an analysis of a general machine learning technique called 'stacking' for the estimation of photometric redshifts. Stacking techniques can feed the photometric redshift estimate, as output by a base algorithm, back into the same…

Instrumentation and Methods for Astrophysics · Physics 2016-07-27 Roman Zitlau , Ben Hoyle , Kerstin Paech , Jochen Weller , Markus Michael Rau , Stella Seitz

The relativley large spread in the derived metallicities ([Fe/H]) of M dwarfs shows that various approaches have not yet converged to consistency. The presence of strong molecular features, and incomplete line lists for the corresponding…

Solar and Stellar Astrophysics · Physics 2015-06-03 Anna Önehag , Ulrike Heiter , Bengt Gustafsson , Nikolai Piskunov , Bertrand Plez , Ansgar Reiners

We present a novel technique to measure $\sigma_8$, by measuring the dependence of the second-order bias of a density field on $\sigma_8$ using two separate techniques. Each technique employs area-averaged angular correlation functions…

Astrophysics · Physics 2011-04-20 Ashley J. Ross , Robert J. Brunner , Adam D. Myers

Metric learning makes it plausible to learn distances for complex distributions of data from labeled data. However, to date, most metric learning methods are based on a single Mahalanobis metric, which cannot handle heterogeneous data well.…

Machine Learning · Statistics 2012-01-04 Caiming Xiong , David Johnson , Ran Xu , Jason J. Corso

JWST's Early Release Observations of the lensing cluster SMACS J0723.3-7327 have given an unprecedented spectroscopic look into the high-redshift universe. These observations reveal five galaxies at z > 5. All five have detectable…

Astrophysics of Galaxies · Physics 2022-09-13 A. J. Taylor , A. J. Barger , L. L. Cowie

Measuring the physical properties of galaxies such as redshift frequently requires the use of Spectral Energy Distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space.…

Instrumentation and Methods for Astrophysics · Physics 2017-12-13 J. Bryce Kalmbach , Andrew J. Connolly

In a series of three papers, we investigate the current status of published metallicities for open clusters that were derived from a variety of photometric and spectroscopic methods. The current article focuses on spectroscopic methods. The…

Astrophysics of Galaxies · Physics 2014-01-10 U. Heiter , C. Soubiran , M. Netopil , E. Paunzen

As an integral part of contemporary manufacturing, monitoring systems obtain valuable information during machining to oversee the condition of both the process and the machine. Recently, diverse algorithms have been employed to detect tool…

Machine Learning · Computer Science 2024-10-10 Zongshuo Li , Markus Meurer , Thomas Bergs

We analyze a sample of tens of thousands of spectra of halo turnoff stars, obtained with the optical spectrographs of the Sloan Digital Sky Survey (SDSS), to characterize the stellar halo population "in situ" out to a distance of a few tens…

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