研究目的
To study the role of the environment on galaxy evolution and understand the origin of the red sequence in dense environments using a sample of galaxies in the Virgo cluster and its surrounding regions.
研究成果
The study concludes that the most massive galaxies in the Virgo cluster are slow rotators formed by major merging events at early epochs. Low-mass star-forming systems are transformed into quiescent dwarf ellipticals through ram pressure stripping, which removes their interstellar medium and quenches star formation. The kinematic properties of these galaxies remain similar to those of star-forming systems.
研究不足
The study is limited by the completeness and depth of the GALEX observations, especially in the periphery of the cluster where observations are shallower. The determination of stellar masses might be affected by systematic errors due to the use of standard recipes not optimized for perturbed galaxies.
1:Experimental Design and Method Selection:
The study uses a sample of 868 galaxies selected from the GALEX Ultraviolet Virgo Cluster Survey (GUViCS), covering a wide range in morphological types and stellar masses. Multifrequency data including UV, optical, mid- and far-infrared imaging data, as well as optical and HI spectroscopic data, were collected.
2:Sample Selection and Data Sources:
The sample includes galaxies with recessional velocity lower than 3500 km s?1, selected from the Virgo Cluster Catalogue (VCC) and other main catalogues included in NED.
3:List of Experimental Equipment and Materials:
GALEX for UV data, SDSS for optical data, WISE for mid-infrared data, Herschel for far-infrared data, and ALFALFA for HI data.
4:Experimental Procedures and Operational Workflow:
The study identifies dynamical substructures of the Virgo cluster, calculates local galaxy density, and analyzes the distribution of galaxies in the red sequence, green valley, and blue cloud.
5:Data Analysis Methods:
The analysis includes comparing observational results with multizone chemo-spectrophotometric models of galaxy evolution to understand the effects of the cluster environment.
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