Edge-On Starbursts


Picture of Kate Rubin
Kate Rubin
San Diego State University


We will observe ~57 edge-on galaxies having high specific star formation rates (log sSFR > -9.375 [yr-1]) with the MaNGA 127-fiber bundles. The fortuitous orientation of these systems, drawn from the main MaNGA target sample, provide an ideal geometry for study of the morphology and ionization state of material driven from the galactic disks in large-scale outflows and traced by nebular emission lines (i.e., Hα, [NII], [OIII]). As galaxies with such high sSFRs are rare, this program ensures that MaNGA will observe those objects which may in principle exhibit the most powerful outflows, while the proposed large bundles maximize MaNGA’s sensitivity to the full spatial extent of wind material, providing unprecedented constraints on wind energetics in a large galaxy sample. When combined with MaNGA’s baseline sample of edge-on galaxies, these observations will assess the spatial extent and ionization state of winds over the full range in sSFR exhibited by star-forming galaxies for the first time in the local universe. We have provided a list of 138 targets appropriate for this program, 57 of which will ultimately be observed.

We will also observe three small supplementary samples as follows:

  • 15 galaxies with UV-bright background QSOs at small impact parameters. These QSOs have already been observed with HST/COS.
  • 3 edge-on galaxies with SDSS QSOs at very small impact parameters (i.e., within less than 2.7 times the half-light Petrosian diameter).
  • 10 Hα-selected starbursts.

We have requested that each of these 28 specific targets be observed by the time MaNGA is complete. Together, the 57 edge-on starbursts, the 18 galaxies with close background QSOs, and the 10 Hα-selected starbursts fill our allocation of 85 IFUs.

Finding Targets

An object whose MANGA_TARGET3 or MNGTARG3 value includes one or more of the bitmasks in the following table was targeted for spectroscopy as part of this ancillary target program. See SDSS bitmasks to learn how to use these values to identify objects in this ancillary target program.

Program (bit name) Bit number Target Description Target Density (deg-2)
EDGE_ON_WINDS 6 Edge-on starbursts (138), galaxies with close-projected b/g QSOs (18), or Hα-selected starbursts (10) 0.02


  1. Winds in Edge-On Starbursts

    Galactic-scale gaseous outflows are a common feature of models of galaxy formation and the interface between galaxies and the intergalactic medium (IGM). However, traditional absorption-line studies of these flows provide little information on gas morphology or the radial extent of the flow, such that the mass and energy carried by this material remains poorly constrained. However, studies of optical line emission from the warm, dense phase of this gas around systems with fortuitous edge-on orientations permit a direct measure of the radial extent of the wind, along with constraints on the density and ionization state of the material. Several studies have demonstrated via narrow-band imaging of such systems, primarily in Hα, that these flows can extend up to ~20 kpc from the galaxy (Lehnert et al. 1999, Veilleux et al. 2003). More recently, the SAMI IFU survey has reported the detection of wind emission in a number of transitions (Ha, [NII], [SII], etc.) extending to 6″ from a single edge-on object, providing diagnostics of the ionization state of the wind as a function of distance (Fogarty et al. 2012).

    While these studies demonstrate the power of emission-line detection techniques, they are limited by very small samples (tens of galaxies) and have typically focused on extreme starburst systems. MaNGA’s main target sample will include >800 star-forming galaxies (log sSFR > -11 [yr-1]) having inclinations > 75 degrees, providing a dramatic improvement over studies in the literature both in terms of sample size and in coverage of galaxies having a wide range of star formation properties. However, because of the low sky density of objects with the highest sSFR (log sSFR > -9 [yr-1]) at z~0, in combination with the need for a narrow range in galaxy orientation (> 75 degrees), MaNGA will by default observe only a handful of such galaxies. Here we prioritize observations of a total of ~57 high-sSFR, edge-on systems drawn from the main MaNGA target sample, and request that they be assigned the large-format 127 fiber bundles.

    The uniquely large (2″) fibers in use with the BOSS spectrograph are ideal for observations of the extended, low surface-brightness emission we target, and are unavailable on competing instruments (e.g., Gemini/GMOS, WHT/SAURON, AAT/SAMI). Taking advantage of this valuable asset, this program will ensure coverage of those galaxies which may in principle exhibit the most powerful outflows, maximizing MaNGA’s sensitivity to the full spatial extent of the wind material and providing unprecedented constraints on wind energetics in a large galaxy sample. When combined with MaNGA’s main targets, these observations will assess the spatial extent and ionization state of wind material over the full range in sSFR exhibited by star-forming galaxies in the local universe.

  2. Galaxies with close-projected, UV-bright background QSOs

    Briefly, we will observe 15 galaxies with UV-bright background QSOs which have archival HST-COS observations. This will permit comparison of multi-phase gas kinematics, chemical enrichment and spatial geometry of the circumgalactic medium to the resolved morphology, orientation, kinematics, star formation rate and metallicities of the host galaxies.

  3. Galaxies with close-projected SDSS QSOs

    We will also observe 3 edge-on galaxies with SDSS QSOs at very small impact parameters.

  4. Hα-selected starbursts

    Finally, we will observe 10 starbursts selected based on their Hα surface brightness for comparison to high-redshift starburst samples.

Target Selection

Our primary selection criteria make use of (1) the sSFR and (2) the inclination of each object. To calculate sSFR, we start by using WISE photometry from Lang et al. (2016) to estimate the 22 micron flux (Fν(22um)) of every object in the baseline MaNGA targeting catalog. In performing this estimation, we adopt a factor 0.92 correction for objects having W2-W3 > 1.3 (with W2 and W3 the magnitudes measured in the WISE passbands at 4.6um and 12um, respectively) as advised in Jarrett et al. (2013). We then use a calibration from Cluver et al. (2014) to convert 22 micron luminosity (Lν(22um)) to total SFR_IR, log SFR_IR = 0.82 * log (ν Lν) – 7.3.

To calculate the inclination for each target, we use the relation inclination = arccos(SERSICBA), where SERSICBA is the axis ratio SERSIC_BA listed in the targeting catalog.

We then select all objects having log sSFR > -8.75 and inclination > 75 deg to define our initial sample for consideration. We additionally demand that each galaxy has W1-W2 < 0.8 (with W1 the WISE passband at 3.4um) to minimize contamination from AGN-dominated objects (Stern et al. 2012). We then visually inspect each target to check for nearby bright stars, overlapping objects, and to make sure they have the correct orientation, trimming the final sample to 138 targets. We note that 35 of these targets overlap with those in the catalog published by Bizyaev et al. (2014), and thus have been previously verified to be almost exactly edge-on.

We have additionally supplemented our sample with a handful of targets satisfying alternative selection criteria. First, we include 15 galaxies from the MaNGA targeting catalog located within 100 kpc (in projection) of background UV-bright QSOs having archival COS spectroscopy. Second, we include 3 galaxies having inclinations > 70 deg which lie within 15″ of a background QSO with existing SDSS spectroscopy. Finally, we include 10 objects which have extreme Hα luminosities as measured within the 3″ SDSS fiber observation of each galaxy (i.e., L(Hα) > 1041 erg/s/fiber).


Bizyaev et al. 2014, ApJ, 787, 24
Cluver et al. 2014, ApJ, 782, 90
Fogarty et al. 2012, ApJ, 761, 169
Jarrett et al. 2013, AJ, 145, 6
Lang et al. 2016, AJ, 151, 36
Lehnert et al. 1999, ApJ, 523, 575
Stern et al. 2012, ApJ, 753, 30
Veilleux et al. 2003, AJ, 126, 2185