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Related papers: Introducing EMILI: Computer Aided Emission Line Id…

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Deep high-dispersion spectroscopy of Galactic photoionized gaseous nebulae, mainly planetary nebulae and HII regions, has revealed numerous emission lines. As a key step of spectral analysis, identification of emission lines hitherto has…

Solar and Stellar Astrophysics · Physics 2025-01-22 Zhijun Tu , Xuan Fang , Robert Williams , Jifeng Liu

In order to test the robustness and reliability of the new generation spectral-line identifier PyEMILI, as initially introduced in Paper I, in line identification and establish a reference/benchmark dataset for future spectroscopic studies,…

Solar and Stellar Astrophysics · Physics 2025-11-19 Zhijun Tu , Xuan Fang , Jorge García-Rojas , Robert Williams , Jifeng Liu

Interstellar molecules, which play an important role in astrochemistry, are identified using observed spectral lines. Despite the advent of spectral analysis tools in the past decade, the identification of spectral lines remains a tedious…

Astrophysics of Galaxies · Physics 2025-02-07 Yisheng Qiu , Tianwei Zhang , Thomas Möller , XueJian Jiang , Zihao Song , Huaxi Chen , Donghui Quan

Diagnostic diagrams of forbidden lines have been a useful tool for observers in astrophysics for many decades now. They are used to obtain information on the basic physical properties of thin gaseous nebulae. Some diagnostic diagrams are in…

Instrumentation and Methods for Astrophysics · Physics 2015-06-18 Bastian Proxauf , Silvia Oettl , Stefan Kimeswenger

Emission-line regions are key to understanding the properties of galaxies, as they trace the exchange of matter and energy between stars and the interstellar medium (ISM). In nearby galaxies, individual nebulae can be identified as HII…

We present ELSA, a new modular software package, written in C, to analyze and manage spectroscopic data from emission-line objects. In addition to calculating plasma diagnostics and abundances from nebular emission lines, the software…

Astrophysics · Physics 2009-11-11 M. D. Johnson , J. S. Levitt , R. B. C. Henry , K. B. Kwitter

Nowadays electrical impedance spectroscopy (EIS) has become an advanced experimental technique with a wide range of applications: from simple passive circuits diagnostics to semiconductor high-end device development and breakthrough…

Applied Physics · Physics 2025-06-04 Natalia A. Boitsova , Anna A. Abelit , Daniil D. Stupin

Spectroscopy in the infrared provides a means to assess important properties of the plasma in gaseous nebulae. We present some of our own work that illustrates the need for interactions between the themes of this conference - astronomical…

We present very deep CCD spectrum of the bright, medium-excitation planetary nebula NGC 7009, with a wavelength coverage from 3040 to 11000 A. Traditional emission line identification is carried out to identify all the emission features in…

Solar and Stellar Astrophysics · Physics 2015-05-27 X. Fang , X. -W. Liu

The large quantity and high quality of modern radio and infrared line observations require efficient modeling techniques to infer physical and chemical parameters such as temperature, density, and molecular abundances. We present a computer…

The detailed shapes of spectral line profiles provide valuable information about the emitting plasma, especially when the plasma contains an unresolved mixture of velocities, temperatures, and densities. As a result of finite spectral…

Solar and Stellar Astrophysics · Physics 2015-07-17 James A. Klimchuk , Spiros Patsourakos , Durgesh Tripathi

High-resolution optical integral field units (IFUs) are rapidly expanding our knowledge of extragalactic emission nebulae in galaxies and galaxy clusters. By studying the spectra of these objects -- which include classic HII regions,…

Instrumentation and Methods for Astrophysics · Physics 2021-08-31 Carter Lee Rhea , Julie Hlavacek-Larrondo , Laurie Rousseau-Nepton , Benjamin Vigneron , Louis-Simon Guité

I present the Automated Line Fitting Algorithm, ALFA, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which…

Solar and Stellar Astrophysics · Physics 2016-01-20 Roger Wesson

A Probabilistic Neural Network model has been used for automated classification of ELODIE stellar spectral library consisting of about 2000 spectra into 158 known spectro-luminosity classes. The full spectra with 561 flux bins and a PCA…

Astrophysics · Physics 2009-09-29 Mahdi Bazarghan

In the first paper of this series (Rhea et al. 2020), we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spectra taken by SITELLE at the Canada-France-Hawaii Telescope.…

The emission lines emitted from gaseous nebulae carry valuable information about the physical conditions and chemical abundances of ionized gases in these objects, as well as the interstellar extinction. "proEQUIB" is a library containing…

Instrumentation and Methods for Astrophysics · Physics 2024-12-09 Ashkbiz Danehkar

Unintended radiated emissions arise during the use of electronic devices. Identifying and mitigating the effects of these emissions is a key element of modern power engineering and associated control systems. Signal processing of the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-09 Tom Grimes , Eric Church , William Pitts , Lynn Wood

This paper presents a novel online identification algorithm for nonlinear regression models. The online identification problem is challenging due to the presence of nonlinear structure in the models. Previous works usually ignore the…

Optimization and Control · Mathematics 2022-07-21 Guang-Yong Chen , Min Gan , Jing Chen , Long Chen

We present an analysis of physical conditions in planetary nebulae (PNe) in terms of collisionally-excited line (CEL) and optical-recombination line (ORL) profiles. We aim to investigate whether line profiles could be used to study the…

Astrophysics · Physics 2009-11-13 Yong Zhang

The classical approach to linear system identification is given by parametric Prediction Error Methods (PEM). In this context, model complexity is often unknown so that a model order selection step is needed to suitably trade-off bias and…

Machine Learning · Statistics 2013-03-13 Aleksandr Y. Aravkin , James V. Burke , Gianluigi Pillonetto
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