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20062026
most citedGalaxy and Mass Assembly (GAMA): survey diagnostics and core data release

1.1k citations · 20.7k across the 326 of their papers we have counts for

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Showing 2015Show all

17 papers · 1 filter

astro-ph.GA2015★ 98 cited

Galaxy And Mass Assembly (GAMA): the Stellar Mass Budget by Galaxy Type

Amanda J. Moffett, Stephen A. Ingarfield, Simon P. Driver +16

We report an expanded sample of visual morphological classifications from the Galaxy and Mass Assembly (GAMA) survey phase two, which now includes 7,556 objects (previously 3,727 i…

astro-ph.GA2015★ 21 cited

H-ATLAS/GAMA: The nature and characteristics of optically red galaxies detected at submillimetre wavelengths

A. Dariush, S. Dib, S. Hony +39

We combine Herschel/SPIRE sub-millimeter (submm) observations with existing multi-wavelength data to investigate the characteristics of low redshift, optically red galaxies detecte…

astro-ph.GA2015★ 63 cited

Galaxy And Mass Assembly (GAMA): growing up in a bad neighbourhood - how do low-mass galaxies become passive?

L. J. M. Davies, A. S. G. Robotham, S. P. Driver +13

Both theoretical predictions and observations of the very nearby Universe suggest that low-mass galaxies (log[M/M]<9.5) are likely to remain star-forming unl…

astro-ph.GA2015★ 72 cited

Galaxy and Mass Assembly (GAMA): Projected Galaxy Clustering

D. J. Farrow, Shaun Cole, Peder Norberg +11

We measure the projected 2-point correlation function of galaxies in the 180 deg equatorial regions of the GAMA II survey, for four different redshift slices between z = 0.0 an…

astro-ph.GA2015★ 22 cited

Galaxy And Mass Assembly (GAMA): The Bright Void Galaxy Population in the Optical and Mid-IR

S. J. Penny, M. J. I. Brown, K. A. Pimbblet +22

We examine the properties of galaxies in the Galaxies and Mass Assembly (GAMA) survey located in voids with radii Mpc. Utilising the GAMA equatorial survey, 592 void g…

astro-ph.IM2015★ 107 cited

Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties

A. S. G. Robotham, D. Obreschkow

Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimen…