activity
20132021
most citedSDSS-IV MaNGA PyMorph Photometric and Deep Learning Morphological Catalogs and implications for bulge properties and stellar angular momentum

104 citations · 474 across the 11 of their papers we have counts for

collaborators
Showing astro-ph.GAShow all

9 papers · 1 filter

astro-ph.GA2021★ 32 cited

SDSS-IV MaNGA: drivers of stellar metallicity in nearby galaxies

Justus Neumann, Daniel Thomas, Claudia Maraston +12

The distribution of stellar metallicities within and across galaxies is an excellent relic of the chemical evolution across cosmic time. We present a detailed analysis of spatially…

astro-ph.GA2018★ 104 cited

SDSS-IV MaNGA PyMorph Photometric and Deep Learning Morphological Catalogs and implications for bulge properties and stellar angular momentum

J. -L. Fischer, H. Domínguez Sánchez, M. Bernardi

We describe the SDSS-IV MaNGA PyMorph Photometric (MPP-VAC) and MaNGA Deep Learning Morphology (MDLM-VAC) Value Added Catalogs. The MPP-VAC provides photometric parameters from Sér…

astro-ph.GA2018★ 92 cited

Transfer learning for galaxy morphology from one survey to another

H. Domínguez Sánchez, M. Huertas-Company, M. Bernardi +56

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorit…

astro-ph.GA2018

A simultaneous search for High- LAEs and LBGs in the SHARDS survey

P. Arrabal Haro, J. M. Rodríguez Espinosa, C. Muñoz-Tuñón +15

We have undertaken a comprehensive search for both Lyman Alpha Emitters (LAEs) and Lyman Break Galaxies (LBGs) in the SHARDS Survey of the GOODS-N field. SHARDS is a deep imaging s…

astro-ph.GA2018★ 14 cited

Star-forming galaxies at low-redshift in the SHARDS survey

A. Lumbreras-Calle, C. Muñoz-Tuñón, J. Méndez-Abreu +13

The physical processes driving the evolution of star formation (SF) in galaxies over cosmic time still present many open questions. Recent galaxy surveys allow now to study these p…

astro-ph.GA2017★ 87 cited

Deep learning for galaxy surface brightness profile fitting

D. Tuccillo, M. Huertas-Company, E. Decencière +3

Numerous ongoing and future large area surveys (e.g. DES, EUCLID, LSST, WFIRST), will increase by several orders of magnitude the volume of data that can be exploited for galaxy mo…

astro-ph.GA2015★ 19 cited

SHARDS: A global view of the star formation activity at z~0.84 and z~1.23

Antonio Cava, Pablo G. Pérez-González, M. Carmen Eliche-Moral +22

In this paper, we present a comprehensive analysis of star-forming galaxies (SFGs) at intermediate redshifts (z~1). We combine the ultra-deep optical spectro-photometric data from…

astro-ph.GA2015★ 48 cited

Pathways to quiescence: SHARDS view on the Star Formation Histories of massive quiescent galaxies at 1.0 < z < 1.5

Helena Domínguez Sánchez, Pablo G. Pérez-González, Pilar Esquej +12

We present Star Formation Histories (SFHs) for a sample of 104 massive (stellar mass M > 10 M) quiescent galaxies (MQGs) at =1.0-1.5 from the analysis of spectr…

astro-ph.GA2014★ 20 cited

Herschel Far-IR counterparts of SDSS galaxies: Analysis of commonly used Star Formation Rate estimates

H. Domínguez Sánchez, A. Bongiovanni, M. A. Lara-López +13

We study a hundred of galaxies from the spectroscopic Sloan Digital Sky Survey with individual detections in the Far-Infrared Herschel PACS bands (100 or 160 m) and in the GALEX…