activity
20072026
most citedThe Sydney-AAO Multi-object Integral field spectrograph (SAMI)

570 citations · 4.1k across the 70 of their papers we have counts for

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Showing 2016Show all

7 papers · 1 filter

astro-ph.GA2016★ 163 cited

The SAMI Galaxy Survey: Revisiting Galaxy Classification Through High-Order Stellar Kinematics

Jesse van de Sande, Joss Bland-Hawthorn, Lisa M. R. Fogarty +36

Recent cosmological hydrodynamical simulations suggest that integral field spectroscopy can connect the high-order stellar kinematic moments h3 (~skewness) and h4 (~kurtosis) in ga…

astro-ph.GA2016★ 35 cited

The SAMI Galaxy Survey: Asymmetry in Gas Kinematics and its links to Stellar Mass and Star Formation

J. V. Bloom, L. M. R. Fogarty, S. M. Croom +23

We study the properties of kinematically disturbed galaxies in the SAMI Galaxy Survey using a quantitative criterion, based on kinemetry (Krajnovic et al.). The approach, similar t…

astro-ph.GA2016★ 23 cited

The SAMI galaxy survey: Galaxy Interactions and Kinematic Anomalies in Abell 119

Sree Oh, Sukyoung K. Yi, Luca Cortese +25

Galaxy mergers are important events that can determine the fate of a galaxy by changing its morphology, star-formation activity and mass growth. Merger systems have commonly been i…

astro-ph.IM2016

AAO Starbugs: software control and associated algorithms

Nuria P. F. Lorente, Minh V. Vuong, Keith Shortridge +7

The Australian Astronomical Observatory's TAIPAN instrument deploys 150 Starbug robots to position optical fibres to accuracies of 0.3 arcsec, on a 32 cm glass field plate on the f…

astro-ph.GA2016★ 173 cited

The SAMI Galaxy Survey: the link between angular momentum and optical morphology

L. Cortese, L. M. R. Fogarty, K. Bekki +34

We investigate the relationship between stellar and gas specific angular momentum , stellar mass and optical morphology for a sample of 488 galaxies extracted from the S…

astro-ph.IM2016★ 27 cited

Using an Artificial Neural Network to Classify Multi-component Emission Line Fits

Elise J Hampton, Brent Groves, Anne Medling +11

We present The Machine, an artificial neural network (ANN) capable of differentiating between the numbers of Gaussian components needed to describe the emission lines of Integral F…