One-sentence Summary

The SAMI Galaxy Survey team releases the first public dataset of 107 galaxies observed with the Sydney-AAO Multi-object Integral field spectrograph, establishing the largest integral field survey of its kind and providing early community access to stimulate research across diverse aspects of galaxy evolution.

Key Contributions

• The paper releases the first public dataset from the Sydney–AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey, providing calibrated integral field spectroscopic observations for 107 galaxies.
• This dataset establishes the SAMI Galaxy Survey as the largest active integral field spectroscopic galaxy survey, with approximately 1000 galaxies observed to date and a target sample of roughly 3400 galaxies.
• Early public access to these observations expands the measurable parameter space for galaxy evolution studies and enables the broader research community to conduct diverse astrophysical investigations.

Introduction

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Dataset

• Dataset composition and sources: The authors compile integral field spectroscopic observations from the Sydney and AAO Multi-object Integral field spectrograph mounted on the Anglo-Australian Telescope. Targets are drawn from two primary environments: a field and group sample covering the GAMA survey fields, and a dedicated cluster sample spanning eight galaxy clusters to capture higher environmental densities. The dataset is further supported by multiband ancillary data ranging from UV to radio observations.

• Key details for each subset: The overarching survey targets approximately 3400 galaxies, with roughly 1000 already observed. The Early Data Release subset contains fully calibrated datacubes for 107 galaxies selected from the GAMA regions using a tiered volume limited filtering strategy.

• Data processing and usage: Raw exposures are initially reduced using the 2DFDR software to produce row stacked spectra. A dedicated pipeline then applies flux calibration using spectrophotometric standards and corrects for telluric absorption. The authors combine approximately seven dithered frames per galaxy, resampling them onto a regular grid to generate paired blue and red datacubes. This spatially resolved dataset supports direct scientific analysis of galactic winds, star formation distributions, and stellar kinematics rather than machine learning training splits.

• Cropping strategy, metadata, and quality control: Velocity field maps are masked to retain only spaxels with a continuum signal to noise ratio exceeding five. The authors construct metadata tables listing stellar mass, effective radius, and surface brightness for each object. Rigorous quality control maintains flat field accuracy between 0.3 and 1 percent, wavelength calibration within 0.1 pixels, and a median point spread function full width at half maximum of 2.1 arcseconds.