The Data Analysis Pipeline for the SDSS-IV MaNGA IFU Galaxy Survey: Overview (1901.00856v2)

Abstract: Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is acquiring integral-field spectroscopy for the largest sample of galaxies to date. By 2020, the MaNGA Survey --- one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) --- will have observed a statistically representative sample of 10$^4$ galaxies in the local Universe ($z\lesssim0.15$). In addition to a robust data-reduction pipeline (DRP), MaNGA has developed a data-analysis pipeline (DAP) that provides higher-level data products. To accompany the first public release of its code base and data products, we provide an overview of the MaNGA DAP, including its software design, workflow, measurement procedures and algorithms, performance, and output data model. In conjunction with our companion paper Belfiore et al., we also assess the DAP output provided for 4718 observations of 4648 unique galaxies in the recent SDSS Data Release 15 (DR15). These analysis products focus on measurements that are close to the data and require minimal model-based assumptions. Namely, we provide stellar kinematics (velocity and velocity dispersion), emission-line properties (kinematics, fluxes, and equivalent widths), and spectral indices (e.g., D4000 and the Lick indices). We find that the DAP provides robust measurements and errors for the vast majority ($>$99%) of analyzed spectra. We summarize assessments of the precision and accuracy of our measurements as a function of signal-to-noise, and provide specific guidance to users regarding the limitations of the data. The MaNGA DAP software is publicly available and we encourage community involvement in its development.

Overview of the MaNGA Data Analysis Pipeline

The academic paper titled "The Data Analysis Pipeline for the SDSS-IV MaNGA IFU Galaxy Survey: Overview" presents a comprehensive description of the Data Analysis Pipeline (DAP) developed for the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, part of the Sloan Digital Sky Survey-IV (SDSS-IV). This document explores the technical structure, objectives, and capabilities of the DAP, its role within the MaNGA project, and the implications for the astronomical community utilizing MaNGA data.

Data and Objectives

MaNGA aims to acquire integral-field spectroscopy for approximately 10,000 galaxies in the local universe. The DAP is a crucial element of this survey, designed to process and analyze the wealth of spectral data generated. It produces crucial data products by performing robust measurements with minimal model-based assumptions, including stellar kinematics, emission-line properties, and spectral indices. These outputs are integral for understanding the dynamical and compositional characteristics of galaxies.

Pipeline Structure and Functionality

The DAP executes a modular workflow—illustrated in the paper—with each module handling specific analytical tasks. A hierarchical-clustering technique optimizes the use of spectral templates to expedite computation without compromising the accuracy of the fits. The pipeline incorporates sophisticated methods to handle spatial binning, stellar kinematic measurements using the Penalized Pixel-Fitting method (pPXF), emission-line modeling, and spectral index calculations. These procedures ensure that high-quality data products are available for further scientific investigation.

Analytical Results and Validation

The paper extensively evaluates the performance of the DAP using both simulated data and repeat telescope observations. The authors demonstrate that the DAP reliably measures stellar kinematics and emission-line properties to a high degree of accuracy, with errors comparable to those expected theoretically and empirically. This evaluation is crucial for validating the robustness and scientific reliability of the DAP outputs.

Practical Implications

The DAP significantly advances the usability of MaNGA data by providing a standardized approach to the extraction of physical galaxy parameters. Researchers are encouraged to utilize the community-accessible software and contribute to its ongoing development. The pipeline's modularity and adaptability also make it a useful tool for other spectral surveys seeking to implement similar methodologies.

Future Developments

Potential enhancements to the DAP include the integration of more extensive stellar libraries, improved modeling of non-Gaussian emission-line profiles, and the development of methodologies that incorporate spatial dependencies in data analysis. These enhancements could expand the scientific reach of the MaNGA survey and improve the precision of galaxy characterization.

In conclusion, the Data Analysis Pipeline for the SDSS-IV MaNGA IFU Galaxy Survey is a sophisticated, well-evaluated tool that aids in the extraction and analysis of integral-field spectroscopy data. It provides researchers with high-quality, science-ready products that facilitate the paper of galaxy dynamics and composition, offering significant contributions to the field of astrophysics.