Data Products

ALMA Proposal Strategy

Observation Method

ALMaQUEST consists of 47 unique galaxies selected from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA survey), which span a wide range of specific star-formation rates (including the green valley, main sequence, and all the way up to the starburst regime). ALMA 12CO(1-0) (restframe 115.271204 GHz)) were collected from four individual ALMA programs: 2015.1.01225.S, 2017.1.01093.S, 2018.1.00558.S (PIs: Lin), and 2018.1.00541.S (PI: Ellison).

All ALMA observations were taken C43-2 configuration (synthesized beam ~2.5″) to match the resolution of the MaNGA survey. A single pointing field of view of 50″ was employed, and thus the largest structure ALMaQUEST is sensitive to is approximately 14 kpc. Integration time for objects ranged from 0.2 – 2.5 hours to ensure a signal-to-noise greater than 3 for more than 50% of spatial pixels (spaxels) where the Hα signal-to-noise is also greater than 3.

Reduction Method & Matching MaNGA

All data is calibrated using the ALMA reduction package CASA (Common Astronomy Software Applications; McMullin et al. 2007).  28 out of 46 galaxies achieved an effective beamsize comparable to the PSF of MaNGA (2.5″), 14 galaxies have beamsize less than 2.3″ , and 4 have beamsizes ~2.8″. From measurements of the CO(1-0) line, integrated over a region of 1.5 effective radii, 0-2 moment maps (integrated intensity, intensity-weighted velocity, and intensity-weighted velocity dispersion respectively) were constructed with the aid of the CASA task IMMOMENTS.

To ease comparison between MaNGA and ALMA measurements, ALMaQUEST adopts a specified pixel size of 0.5″ and a restoring beam size of 2.5″x2.5″ such that the intensity map matches the image grid and spatial resolution of MaNGA. Thus, for each spectral pixel (spaxel) provided by MaNGA, ALMaQUEST can supply a corresponding CO(1-0) line intensity. The final cubes have an rms noise of 0.2 – 2 mJy per beam. More details on ALMA observation / reduction methods can be found in the ALMaQUEST survey paper (Lin et al. in prep).

Derived Data Products

The CO luminosity can be used to infer a molecular gas surface density with the use of a conversion factor αCO. The main dataproducts available in ALMaQUEST assume a constant αCO = 4.3 M☉ pc-2 (K km/s)-1 . Alternatively, we offer some dataproducts computed with a metallicity dependent αCO = 4.35 (Z/Z☉)-1.6 M☉ pc-2 (K km/s)-1 .

Star-formation rates (SFR) are computed from the Hα emission line flux provided by the MaNGA observations (processed by the PIPE3D pipeline, see Sánchez et al. 2016 for details), using the conversion from Hα luminosity of SFR proposed by Kennicutt et al. 1998 and assuming a Salpeter IMF. For every spaxel that has a measured SFR and molecular gas surface density, we divide the former by the later to discern the star-formation efficiency (SFE) of each spaxel.

MaNGA PIPE3D also provides a stellar mass surface density (Σ*) for each spaxel. This, along with the molecular gas surface density, are used to compute the molecular gas fraction fH2 = ΣH2 / (Σ*+ΣH2). By comparing the excess amount of gas in a spaxel (fH2) to the efficiency at which gas is converted to stars (SFE), we can evaluate which physical scenario is shaping the star-formation and stellar population properties of a region in a galaxy.

A catalogue of all these derived properties for ALMaQUEST can be found here.

Offsets from Resolved Relations

The three kpc-scale relations that regulate star-formation, as measured with the ALMaQUEST survey in Lin et al. 2019.

Three spatially resolved relationships shape the kpc variations in SFR: The star-forming main sequence (SFMS, tracing the enhanced SFR surface density ΣSFR with increased stellar mass surface density), the Kennicutt-Schmidt relation (the correlation between ΣH2 and ΣSFR), and the molecular gas main sequence (MGMS, which demonstrates the correlation between ΣH2 and Σ*). We can use these relationships to define a “normal” SFR at a fixed stellar mass or molecular gas surface density. We quantify any offset from this “normal” behaviour as a Δ value.

  • ΔΣSFR: an offset from the SFMS, indicating enhanced star-formation for the given Σ*.
  • ΔSFE: an offset from the Kennicutt-Schmidt relation, indicating an enhanced efficiency in star-formation.
  • ΔfH2: an offset from the MGMS, indicating an enhanced gas fraction for a given Σ*.

Δ properties are optimal for studying spatially resolved changes in particular populations of galaxies, such as starbursts or mergers, from regular star-forming galaxies.

An example of Δ properties for an ALMaQUEST starburst galaxy, from Ellison et al. 2020. Notice the variation within the galaxy, in particular that all three Δ values vary in spatial distribution and magnitude of offset from the corresponding kpc-scale relation.

Data Access

Moment 0, moment 1, and moment 2 maps from ALMaQUEST, as well as other derived data products, are currently still proprietary within the team. Any inquiries regarding pre-release access should be addressed to the survey PI (contact here).