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THE GRISM LENS-AMPLIFIED SURVEY from SPACE (GLASS). VII. the DIVERSITY of the DISTRIBUTION of STAR FORMATION in CLUSTER and FIELD GALAXIES at 0.3 ≤ z ≤ 0.7

  • Author(s): Vulcani, B;
  • Treu, T;
  • Schmidt, KB;
  • Morishita, T;
  • Dressler, A;
  • Poggianti, BM;
  • Abramson, L;
  • Bradač, M;
  • Brammer, GB;
  • Hoag, A;
  • Malkan, M;
  • Pentericci, L;
  • Trenti, M
  • et al.
Abstract

Exploiting the slitless spectroscopy taken as part of the Grism Lens-Amplified Survey from Space (GLASS), we present an extended analysis of the spatial distribution of star formation in 76 galaxies in 10 clusters at 0.3 < z < 0.7. We use 85 foreground and background galaxies in the same redshift range as a field sample. The samples are well matched in stellar mass (108-1011 M⊙) and star formation rate (0.5-50 M⊙ yr-1). We visually classify galaxies in terms of broad band morphology, H? morphology, and likely physical process acting on the galaxy. Most H? emitters have a spiral morphology (41% ± 8% in clusters, 51% ± 8% in the field), followed by mergers/interactions (28% ± 8%, 31% ±7%, respectively) and early-type galaxies (remarkably as high as 29% ±8% in clusters and 15% ± 6% in the field). A diversity of H? morphologies is detected, suggesting a diversity of physical processes. In clusters, 30% ± 8% of the galaxies present a regular morphology, mostly consistent with star formation diffused uniformly across the stellar population (mostly in the disk component, when present). The second most common morphology (28% ±8%) is asymmetric/jellyfish, consistent with rampressure stripping or other non-gravitational processes in 18% ± 8% of the cases. Ram-pressure stripping appears significantly less prominent in the field (2% ± 2%), where the most common morphology/mechanism appears to be consistent with minor gas-rich mergers or clump accretion. This work demonstrates that while environmentspecific mechanisms affect galaxy evolution at this redshift, they are diverse and their effects are subtle. A full understanding of this complexity requires larger samples and detailed and spatially resolved physical models.

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