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In this paper we present the publicly available open-source spectral energy distribution (SED) fitting code SMART (Spectral energy distributions Markov chain Analysis with Radiative Transfer models). Implementing a Bayesian Markov chain…

Astrophysics of Galaxies · Physics 2024-05-29 Charalambia Varnava , Andreas Efstathiou

We introduce a new physically-motivated spectral template set for fitting the spectral energy distributions (SEDs) of high-z galaxies. We use the public galaxy formation code ARES to generate star formation histories of thirteen…

Astrophysics of Galaxies · Physics 2025-10-29 Judah Luberto , Steven Furlanetto , Jordan Mirocha

We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties on…

Instrumentation and Methods for Astrophysics · Physics 2015-06-24 Viviana Acquaviva , Anand Raichoor , Eric Gawiser

By utilizing the spatially-resolved photometry of galaxies at $0.2<z<3.0$ in the CEERS field, we estimate the resolved and unresolved stellar mass via spectral energy distribution (SED) fitting to study the discrepancy between them. We…

Astrophysics of Galaxies · Physics 2023-11-16 Jie Song , GuanWen Fang , Zesen Lin , Yizhou Gu , Xu Kong

We performed a large-scale spectral energy distribution (SED) fitting analysis for young stellar objects (YSOs) in the Orion star formation complex (OSFC) to derive key physical parameters; temperature, luminosity, mass, and age, using SED…

Solar and Stellar Astrophysics · Physics 2025-02-27 Ilknur Gezer , Gábor Marton , Julia Roquette , Marc Audard , David Hernandez , Máté Madarász , Odysseas Dionatos

Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for stellar population…

Astrophysics of Galaxies · Physics 2023-02-20 Andrew P. Hearin , Jonás Chaves-Montero , Alex Alarcon , Matthew R. Becker , Andrew Benson

We present Starduster, a supervised deep learning model that predicts the multi-wavelength SED from galaxy geometry parameters and star formation history by emulating dust radiative transfer simulations. The model is comprised of three…

Astrophysics of Galaxies · Physics 2022-05-18 Yisheng Qiu , Xi Kang

Spectral energy distribution (SED) models are widely used to infer the physical properties of galaxies from multi-wavelength photometry, but their accuracy is difficult to assess because the true properties of observed galaxies are…

Astrophysics of Galaxies · Physics 2026-03-25 Zoe R. Jones , Elisabete da Cunha , Andrew Battisti

Sophisticated spectral energy distribution (SED) models describe dust attenuation and emission using geometry parameters. This treatment is natural since dust effects are driven by the underlying star-dust geometry in galaxies. An example…

Astrophysics of Galaxies · Physics 2022-12-28 Yisheng Qiu , Xi Kang , Yu Luo

A new method is developed for estimating photometric redshifts to galaxies, using realistic template SEDs, extending over four decades in wavelength (i.e. from 0.05 micron to 1 mm). The template SEDs are constructed for four different…

Astrophysics · Physics 2007-05-23 Bahram Mobasher , Paola Mazzei

Massive stars play a critical role in the evolution of galaxies, but their formation remains poorly understood. One challenge is accurate measurement of the physical properties of massive protostars, such as current stellar mass, envelope…

Solar and Stellar Astrophysics · Physics 2025-08-19 Yao-Lun Yang , Jonathan C. Tan , Rubén Fedriani , Yichen Zhang

Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of its high efficiency. Although various methods have been developed, template fitting is still adopted as one of the most…

Cosmology and Nongalactic Astrophysics · Physics 2025-04-11 Yicheng Li , Liping Fu , Zhu Chen , Zhijian Luo , Wei Du , Yan Gong , Xianmin Meng , Junhao Lu , Zhirui Tang , Pengfei Chen , Shaohua Zhang , Chenggang Shu , Xingchen Zhou , Zuhui Fan

We present analytic radiative transfer solutions for the spectra of unresolved, spherically symmetric, centrally heated, dusty sources. We find that the dust thermal spectrum possesses scaling relations that provide a natural classification…

Astrophysics · Physics 2009-11-13 Sukanya Chakrabarti , Christopher F. McKee

In this work we incorporate the newest ISO results on the mid-infrared spectral-energy-distributions (MIR SEDs) of galaxies into models for the number counts and redshift distributions of MIR surveys. A three-component model, with…

The S\'ersic law (SL) offers a versatile functional form for the structural characterization of galaxies near and far. Whereas applying it to galaxies with a genuine SL luminosity distribution yields a robust determination of the S\'ersic…

Astrophysics of Galaxies · Physics 2019-12-18 Iris Breda , Polychronis Papaderos , Jean Michel Gomes , Stergios Amarantidis

Machine learning potential-driven molecular dynamics (MD) simulations have significantly enhanced the predictive accuracy of thermal transport properties across diverse materials. However, extracting phonon-mode-resolved insights from these…

Computational Physics · Physics 2025-09-18 Ting Liang , Wenwu Jiang , Ke Xu , Hekai Bu , Zheyong Fan , Wengen Ouyang , Jianbin Xu

In today's modern wide-field galaxy surveys, there is the necessity for parametric surface brightness decomposition codes characterised by accuracy, small degree of user intervention, and high degree of parallelisation. We try to address…

Astrophysics of Galaxies · Physics 2023-03-03 Luca Tortorelli , Amata Mercurio

Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. As there are proportionally more photometric redshift data than spectroscopic, we aim to use photometric data to improve and expand the areas…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-15 Moorits Mihkel Muru , Elmo Tempel

The European Space Agency's Euclid mission will observe approximately 14,000 $\rm{deg}^{2}$ of the extragalactic sky and deliver high-quality imaging for many galaxies. The depth and high spatial resolution of the data will enable a…

Astrophysics of Galaxies · Physics 2025-10-15 Euclid Collaboration , Abdurro'uf , C. Tortora , M. Baes , A. Nersesian , I. Kovačić , M. Bolzonella , A. Lançon , L. Bisigello , F. Annibali , M. N. Bremer , D. Carollo , C. J. Conselice , A. Enia , A. M. N. Ferguson , A. Ferré-Mateu , L. K. Hunt , E. Iodice , J. H. Knapen , A. Iovino , F. R. Marleau , R. F. Peletier , R. Ragusa , M. Rejkuba , A. S. G. Robotham , J. Román , T. Saifollahi , P. Salucci , M. Scodeggio , M. Siudek , A. van der Wel , K. Voggel , B. Altieri , S. Andreon , C. Baccigalupi , M. Baldi , S. Bardelli , A. Biviano , A. Bonchi , D. Bonino , E. Branchini , M. Brescia , J. Brinchmann , A. Caillat , S. Camera , G. Cañas-Herrera , V. Capobianco , C. Carbone , J. Carretero , S. Casas , M. Castellano , G. Castignani , S. Cavuoti , K. C. Chambers , A. Cimatti , C. Colodro-Conde , G. Congedo , L. Conversi , Y. Copin , F. Courbin , H. M. Courtois , M. Cropper , A. Da Silva , H. Degaudenzi , G. De Lucia , A. M. Di Giorgio , J. Dinis , H. Dole , F. Dubath , X. Dupac , S. Dusini , S. Escoffier , M. Farina , R. Farinelli , S. Farrens , F. Faustini , S. Ferriol , F. Finelli , S. Fotopoulou , M. Frailis , E. Franceschi , M. Fumana , S. Galeotta , B. Gillis , C. Giocoli , P. Gómez-Alvarez , J. Gracia-Carpio , A. Grazian , F. Grupp , W. Holmes , F. Hormuth , A. Hornstrup , P. Hudelot , K. Jahnke , M. Jhabvala , E. Keihänen , S. Kermiche , A. Kiessling , M. Kilbinger , B. Kubik , M. Kümmel , M. Kunz , H. Kurki-Suonio , A. M. C. Le Brun , S. Ligori , P. B. Lilje , V. Lindholm , I. Lloro , G. Mainetti , D. Maino , E. Maiorano , O. Mansutti , O. Marggraf , K. Markovic , M. Martinelli , N. Martinet , F. Marulli , R. Massey , E. Medinaceli , S. Mei , M. Melchior , Y. Mellier , M. Meneghetti , E. Merlin , G. Meylan , A. Mora , M. Moresco , L. Moscardini , S. -M. Niemi , J. W. Nightingale , C. Padilla , S. Paltani , F. Pasian , K. Pedersen , V. Pettorino , G. Polenta , M. Poncet , L. A. Popa , L. Pozzetti , F. Raison , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , E. Rossetti , R. Saglia , Z. Sakr , D. Sapone , B. Sartoris , M. Schirmer , P. Schneider , T. Schrabback , A. Secroun , E. Sefusatti , G. Seidel , S. Serrano , P. Simon , C. Sirignano , G. Sirri , L. Stanco , J. Steinwagner , P. Tallada-Crespí , A. N. Taylor , I. Tereno , S. Toft , R. Toledo-Moreo , F. Torradeflot , I. Tutusaus , L. Valenziano , J. Valiviita , T. Vassallo , G. Verdoes Kleijn , A. Veropalumbo , Y. Wang , J. Weller , G. Zamorani , E. Zucca , E. Bozzo , C. Burigana , M. Calabrese , D. Di Ferdinando , J. A. Escartin Vigo , S. Matthew , N. Mauri , M. Pöntinen , C. Porciani , V. Scottez , M. Tenti , M. Viel , M. Wiesmann , Y. Akrami , V. Allevato , S. Anselmi , M. Archidiacono , F. Atrio-Barandela , M. Ballardini , D. Bertacca , A. Blanchard , L. Blot , S. Borgani , M. L. Brown , S. Bruton , R. Cabanac , A. Calabro , A. Cappi , F. Caro , C. S. Carvalho , T. Castro , F. Cogato , T. Contini , A. R. Cooray , O. Cucciati , G. Desprez , A. Díaz-Sánchez , S. Di Domizio , A. G. Ferrari , I. Ferrero , A. Finoguenov , A. Fontana , F. Fornari , K. Ganga , J. García-Bellido , T. Gasparetto , E. Gaztanaga , F. Giacomini , F. Gianotti , G. Gozaliasl , A. Gregorio , M. Guidi , C. M. Gutierrez , A. Hall , S. Hemmati , H. Hildebrandt , J. Hjorth , M. Huertas-Company , A. Jimenez Muñoz , J. J. E. Kajava , Y. Kang , V. Kansal , D. Karagiannis , C. C. Kirkpatrick , S. Kruk , M. Lattanzi , S. Lee , J. Le Graet , L. Legrand , M. Lembo , J. Lesgourgues , T. I. Liaudat , A. Loureiro , J. Macias-Perez , M. Magliocchetti , F. Mannucci , R. Maoli , J. Martín-Fleitas , C. J. A. P. Martins , L. Maurin , R. B. Metcalf , M. Miluzio , P. Monaco , C. Moretti , G. Morgante , K. Naidoo , Nicholas A. Walton , K. Paterson , L. Patrizii , A. Pisani , V. Popa , D. Potter , I. Risso , P. -F. Rocci , M. Sahlén , E. Sarpa , A. Schneider , D. Sciotti , E. Sellentin , M. Sereno , K. Tanidis , C. Tao , G. Testera , R. Teyssier , S. Tosi , A. Troja , M. Tucci , C. Valieri , D. Vergani , G. Verza , P. Vielzeuf

Traditional spectral energy distribution (SED) fitting techniques face uncertainties due to assumptions in star formation histories and dust attenuation curves. We propose an advanced machine learning-based approach that enhances…

Instrumentation and Methods for Astrophysics · Physics 2024-02-13 Sankalp Gilda