We present an overview of a new integral field spectroscopic survey called MaNGA (Mapping Nearby Galaxies at Apache Point Observatory), one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) that began on 2014 July 1. MaNGA will investigate the internal kinematic structure and composition of gas and stars in an unprecedented sample of 10,000 nearby galaxies. We summarize essential characteristics of the instrument and survey design in the context of MaNGA's key science goals and present prototype observations to demonstrate MaNGA's scientific potential. MaNGA employs dithered observations with 17 fiber-bundle integral field units that vary in diameter from 12 (19 fibers) to 32 (127 fibers). Two dual-channel spectrographs provide simultaneous wavelength coverage over 3600-10300Å at R∼2000. With a typical integration time of 3 hr, MaNGA reaches a target r-band signal-to-noise ratio of 4-8 (Å −1 per 2 fiber) at 23 AB mag arcsec −2 , which is typical for the outskirts of MaNGA galaxies. Targets are selected with M * 10 9 M using SDSS-I redshifts and i-band luminosity to achieve uniform radial coverage in terms of the effective radius, an approximately flat distribution in stellar mass, and a sample spanning a wide range of environments. Analysis of our prototype observations demonstrates MaNGA's ability to probe gas ionization, shed light on recent star formation and quenching, enable dynamical modeling, decompose constituent components, and map the composition of stellar populations. MaNGA's spatially resolved spectra will enable an unprecedented study of the astrophysics of nearby galaxies in the coming 6 yr.

This paper presents direct evidence for hierarchical galaxy assembly out to redshifts z ∼ 3. We identify major mergers using the model-independent CAS (concentration, asymmetry, clumpiness) physical morphological system on galaxies detected, and photometrically selected, in the WFPC2 and NICMOS Hubble Deep Field North. We specifically use the asymmetric distributions of rest-frame optical light measured through the asymmetry parameter (A) to determine the fraction of galaxies undergoing major mergers as a function of redshift (z), stellar mass (M ⋆ ), and absolute magnitude (M B ). We find that the fraction of galaxies consistent with undergoing a major merger increases with redshift for all galaxies, but most significantly, at 5 -10 σ confidence, for the most luminous and massive systems. The highest merger fractions we find are 40% -50% for galaxies with M B < −21, or M ⋆ > 10 10 M ⊙ at z > 2.5, i.e., objects identified as Lyman-break galaxies. Using these results, we model the merger fraction evolution in the form: f m (A,M ⋆ ,M B , z) = f 0 × (1 + z) mA . We find m A values ∼ 4 − 6 for the most luminous and massive galaxies, while lower mass and less luminous galaxies have smaller m A values. We use these merger fractions, combined with merger time scales calculated from N-body simulations, to derive galaxy merger rates to z ∼ 3. We also use stellar masses of HDF-N galaxies to determine the mass accretion rate of field galaxies involved in major mergers. We find an average stellar mass accretion rate ofṀ G ∼ 4 × 10 8 M ⊙ Gyr −1 galaxy −1 at z ∼ 1 for galaxies with stellar masses M ⋆ > 10 9 M ⊙ . This accretion rate changes with redshift as:Ṁ G = 1.6 × 10 8 (1 + z) 0.99±0.32 M ⊙ Gyr −1 galaxy −1 . We also find that the fraction of stellar mass density in galaxies involved in major mergers increases with redshift, with a peak mass fraction ∼ 0.5 for the brightest, M B < −21, and most massive, M ⋆ > 10 10 M ⊙ , systems near z ∼ 2.5. By comparing merger fractions predicted in Cold Dark Matter semi-analytic models with our results we find a reasonably good agreement for the largest and brightest systems, although we find more low-mass galaxy mergers at lower redshifts than what these models predict.

We describe the Sloan

We present a detailed study of rotational asymmetry in galaxies for both morphological and physical diagnostic purposes. An unambiguous method for computing asymmetry is developed, robust for both distant and nearby galaxies. By degrading real galaxy images, we test the reliability of this asymmetry measure over a range of observational conditions, e.g. spatial resolution and signal-to-noise (S/N). Compared to previous methods, this new algorithm avoids the ambiguity associated with choosing a center by using a minimization method, and successfully corrects for variations in S/N. There is, however, a strong relationship between the rotational asymmetry and physical resolution (distance at fixed spatial resolution); objects become more symmetric when less well-resolved.We further investigate asymmetry as a function of galactic radius and rotation. We find the asymmetry index has a strong radial dependence that differs vastly between Hubble types. As a result, a meaningful asymmetry index must be specified within a well-defined radius representative of the physical galaxy scale. We enumerate several viable alternatives, which excludes the use of isophotes. Asymmetry as a function of angle (A φ ) is also a useful indicator of ellipticity and higher-order azimuthal structure. In general, we show the power of asymmetry as a morphological parameter lies in the strong correlation with (B − V ) color for galaxies undergoing normal star formation, spanning all Hubble types from ellipticals to irregular galaxies. Interacting galaxies do not fall on this asymmetry-color "fiducial sequence," as these galaxies are too asymmetric for their color. We propose to use this fact to distinguish between 'normal' galaxies and galaxies undergoing an interaction or merger at high redshift.1994; Jangren et al. 1999). A different method -applicable for spirals -has been suggested by Elmegreen & Elmegreen (1982): measures of spiral arm morphology, particularly their patchiness, can be used for classification. Related attempts to classify galaxies have included the use of principle component analysis of photometric structures (Whitmore 1984;Watanabe et al. 1985;Han 1995). These systems revealed correlations of physical and morphological features of galaxies, but have not been generally adopted for practical use, and the basic Hubble (1926) system still lives on.A key element missing from recent work listed above is the connection made by Morgan between image structure and stellar content (i.e. between light concentration, or central surface-brightness, and spectral type). Ironically, in parallel to the above efforts to quantify image structure, there has been considerable effort to develop quantitative methods of spectral classification based on broad-band colors (Bershady 1995) and spectra (Connolly et al. 1995, Folkes et al. 1996, Bromley et al. 1998, Ronen et al. 1999. What is needed, then, is to go full circle to where Morgan left off, by tying together the spectral types with the quantitative classification based image structure. Here,...

Two new methods are proposed for linear regression analysis for data with measurement errors. Both methods are designed to accommodate intrinsic scatter in addition to measurement errors. The first method is a direct extension of the ordinary least squares (OLS) estimator to allow for measurement errors. It is quite general in that a) it allows for measurement errors on both variables, b) it allows the measurement errors for the two variables to be dependent, c) it allows the magnitudes of the measurement errors to depend on the measurements, and d) other 'symmetric' lines such as the bisector and the orthogonal regression can be constructed. We refer to this method as BCES estimators (for Bivariate Correlated Errors and intrinsic Scatter). The second method is a weighted least squares (WLS) estimator, which applies only in the case where the 'independent' variable is measured without error and the magnitudes of the measurement errors on the 'dependent' variable are independent from the measurements.Several applications are made to extragalactic astronomy: The BCES method, when applied to data describing the color-luminosity relations for field galaxies, yields significantly different slopes than OLS and other estimators used in the literature. Simulations with artificial data sets are used to evaluate the small sample performance of the estimators. Unsurprisingly, the least-biased results are obtained when color is treated as the dependent variable. The Tully-Fisher relation is another example where the BCES method should be used because errors in luminosity and velocity are correlated due to inclination corrections. We also find, via simulations, that the WLS method is by far the best method for the Tolman surface-brightness test, producing the smallest variance in slope by an order of magnitude. Moreover, with WLS it is not necessary to "reduce" galaxies to a fiducial surface-brightness, since this model incorporates intrinsic scatter.