CAVITY: Calar Alto Void Integral-field Treasury surveY. I. First public data release

TL;DR

CAVITY's first public data release provides high-quality, spatially resolved optical spectroscopy data for 100 galaxies in cosmic voids, enabling new research in galaxy evolution within under-dense regions.

Contribution

This paper presents the initial public data release of the CAVITY survey, including detailed data reduction procedures and data structure for studying galaxies in cosmic voids.

Findings

Data release includes 100 galaxies with diverse properties.

Provides comprehensive data reduction and quality control details.

Accessible through dedicated database for further research.

Abstract

The Calar Alto Void Integral-field Treasury surveY (CAVITY) is a legacy project aimed at characterising the population of galaxies inhabiting voids, which are the most under-dense regions of the cosmic web, located in the Local Universe. This paper describes the first public data release (DR1) of CAVITY, comprising science-grade optical data cubes for the initial 100 out of a total of $\sim$300 galaxies in the Local Universe ($0.005 < z < 0.050$). These data were acquired using the integral-field spectrograph PMAS/PPak mounted on the 3.5m telescope at the Calar Alto observatory. The DR1 galaxy sample encompasses diverse characteristics in the color-magnitude space, morphological type, stellar mass, and gas ionisation conditions, providing a rich resource for addressing key questions in galaxy evolution through spatially resolved spectroscopy. The galaxies in this study were observed with the low-resolution V500 set-up, spanning the wavelength range 3745-7500 \AA, with a spectral resolution of 6.0 \AA\ (FWHM). Here, we describe the data reduction and characteristics and data structure of the CAVITY datasets essential for their scientific utilisation, highlighting such concerns as vignetting effects, as well as the identification of bad pixels and management of spatially correlated noise. We also provide instructions for accessing the CAVITY datasets and associated ancillary data through the project's dedicated database.