The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations (1707.02989v1)

Abstract: We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing S/N, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on i-band absolute magnitude ($M_i$), or, for a small subset of our sample, $M_i$ and color (NUV-i). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to $M_i$ and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (Re), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color-magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range $5\times10^8 \leq M_* \leq 3\times10^{11} M_{\odot}$ and are sampled at median physical resolutions of 1.37 kpc and 2.5 kpc for the Primary and Secondary samples respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume limited sample.

• The paper outlines the optimized design of the MaNGA survey, detailing target selection based on redshift and color-magnitude criteria.
• It describes the strategic allocation of IFU sizes to maximize spatial resolution, with samples extending to 1.5 and 2.5 effective radii.
• The study establishes robust methods to minimize biases and sets a benchmark for future spatially resolved spectroscopic surveys.

An Analysis of the SDSS-IV MaNGA Sample Design

The paper "The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations" by Wake et al. provides a comprehensive overview of the sample design for the SDSS-IV Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. This survey aims to employ integral field spectroscopy to investigate the detailed properties of approximately 10,000 nearby galaxies. The meticulous design and optimization of the MaNGA survey addressed multiple parameters, including sample size, spatial resolution, radial coverage, and fit within the constraints of available telescope and spectrograph resources.

Sample Selection and IFU Optimization

The MaNGA survey's primary objective was to optimize the design for efficient spatial coverage, spectral signal-to-noise ratio (S/N), and sample size within the constraints of the BOSS spectrographs and the SDSS 2.5m telescope's field of view. The design process involved multiple strategic choices, including the selection of targets from a well-characterized set of galaxies known as the NASA-Sloan Atlas (NSA). Redshift dependent selection criteria based on $i$-band absolute magnitude and, for a subset, $NUV-i$ color, ensured a uniform angular size distribution across varying galaxy luminosities.

The survey comprises three principal samples: the Primary sample, the Secondary sample, and the Color-Enhanced supplement. The Primary sample emphasizes uniform spatial coverage to 1.5 effective radii ($R_e$) for a flat distribution across $i$-band magnitudes, whereas the Secondary sample extends the coverage to 2.5 $R_e$. The Color-Enhanced supplement enhances the representation of certain color-magnitude regions by extending redshift limits based on color criteria. These samples cover a broad stellar mass range from $$5 \times 10^8 \leq M_* \leq 3 \times 10^{11} M_\odot$$.

The optimal allocation strategy involved determining a range of integral field unit (IFU) sizes fitting within practical fiber constraints—favoring a 2,4,4,2,5 distribution of IFUs ranging from 19 to 127 fibers. This distribution closely matched the galaxy angular sizes derived from the target catalog, maximizing the number of galaxies covered to their required $R_e$.

Implications and Future Developments

MaNGA's design showcases an intricate balance between survey scale, angular resolution, and spectral quality, making it a valuable benchmark for future integral field surveys. The meticulous optimization of IFUs and strategic sample selection criteria sets a precedent for incorporating pre-existing observational infrastructures with minor modifications to achieve ambitious scientific objectives.

Practically, the choice to define samples through simple redshift limits, governed by observable properties minimized experimental errors and systematic uncertainties, paving the way for robust statistical analyses of environmental and intrinsic galaxy properties. The implementation of volume weights to counteract selection biases—particularly relevant given the stratified mass and color selection—further underscores the survey's rigor in addressing potential pitfalls associated with observational biases.

Looking forward, the MaNGA survey will likely inform theoretical models on galaxy formation and evolution by providing spatially resolved spectroscopic data over a statistically meaningful range of galaxy types and environments. This strategic approach and its resulting data set the stage for subsequent developments in astrophysical modeling and interpretation, potentially driving advancements in knowledge regarding stellar population synthesis, dark matter mapping within galaxies, and the evolution of galaxy morphology across cosmic time.

In conclusion, the SDSS-IV MaNGA survey exemplifies how targeted design and strategic planning contribute to achieving scientific aims within boundary conditions posed by extant observational resources. The impact of MaNGA's innovative sample design strategies will echo through future survey plans, influencing forthcoming explorations into multifaceted cosmic phenomena.