MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yr SDSS-IV (Sloan Digital Sky Survey IV) survey that will obtain resolved spectroscopy from 3600 to 10 300 Å for a representative sample of over 10 000 nearby galaxies. In this paper, we derive spatially resolved stellar population properties and radial gradients by performing full spectral fitting of observed galaxy spectra from P-MaNGA, a prototype of the MaNGA instrument. These data include spectra for 18 galaxies, covering a large range of morphological type. We derive age, metallicity, dust, and stellar mass maps, and their radial gradients, using high spectral-resolution stellar population models, and assess the impact of varying the stellar library input to the models...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
C.L. acknowledges the support of the 100 Talents Program of Chinese Academy of Sciences (CAS). This ...
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yr SDSS-IV (Sloan Digital Sky Sur...
MC acknowledges support from a Royal Society University Research Fellowship.MaNGA (Mapping Nearby Ga...
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yearSDSS-IV survey that will obta...
We present an analysis of the data produced by the MaNGA prototype run (P-MaNGA), aiming to test how...
We study the internal gradients of stellar population properties within 1.5 Re for a representative ...
We present an analysis of the data produced by the MaNGA prototype run (P-MaNGA), aiming to test how...
We perform full spectrum fitting stellar population analysis and Jeans Anisotropic modelling (JAM) o...
We study the internal gradients of stellar population propertieswithin 1.5 Re for a representative s...
We study the internal gradients of stellar population properties within 1.5 Re for a representative ...
AW acknowledges support from a Leverhulme Early Career Fellowship.We study the internal radial gradi...
The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs...
We study the internal radial gradients of stellar population properties within 1.5 Re and analyse th...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
C.L. acknowledges the support of the 100 Talents Program of Chinese Academy of Sciences (CAS). This ...
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yr SDSS-IV (Sloan Digital Sky Sur...
MC acknowledges support from a Royal Society University Research Fellowship.MaNGA (Mapping Nearby Ga...
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yearSDSS-IV survey that will obta...
We present an analysis of the data produced by the MaNGA prototype run (P-MaNGA), aiming to test how...
We study the internal gradients of stellar population properties within 1.5 Re for a representative ...
We present an analysis of the data produced by the MaNGA prototype run (P-MaNGA), aiming to test how...
We perform full spectrum fitting stellar population analysis and Jeans Anisotropic modelling (JAM) o...
We study the internal gradients of stellar population propertieswithin 1.5 Re for a representative s...
We study the internal gradients of stellar population properties within 1.5 Re for a representative ...
AW acknowledges support from a Leverhulme Early Career Fellowship.We study the internal radial gradi...
The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs...
We study the internal radial gradients of stellar population properties within 1.5 Re and analyse th...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
We study the internal gradients of stellar population properties within 1.5Re for a representative s...
C.L. acknowledges the support of the 100 Talents Program of Chinese Academy of Sciences (CAS). This ...