Asymmetric Star Formation Efficiency Due to Ram Pressure Stripping
Paulina Troncoso Iribarren,
Nelson Padilla,
Sergio Contreras,
Silvio Rodriguez,
Diego García-Lambas,
Claudia del P. Lagos
Affiliations
Paulina Troncoso Iribarren
Centro de Astro-Ingeniería and Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, 782-0436 Macul, Santiago, Chile
Nelson Padilla
Centro de Astro-Ingeniería and Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, 782-0436 Macul, Santiago, Chile
Sergio Contreras
Centro de Astro-Ingeniería and Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, 782-0436 Macul, Santiago, Chile
Silvio Rodriguez
Instituto de Astronomía Teórica y Experimental, UNC-CONICET, Córdoba X5000BGR, Argentina
Diego García-Lambas
Instituto de Astronomía Teórica y Experimental, UNC-CONICET, Córdoba X5000BGR, Argentina
Claudia del P. Lagos
International Centre for Radio Astronomy Research (ICRAR), M468, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia
Previous works have shown that a dense cluster environment affects satellite galaxy properties and accelerates or truncates their evolutionary processes. In this work, we use the EAGLE simulation to study this effect, dissecting the galaxies in two halves: the one that is falling directly to the cluster (leading half) and the one behind (trailing half). Considering all galaxies within the virial radius of the most massive groups and clusters of the simulation ( M h a l o > 10 13 . 8 [ M ⊙ ] ), we find that on average the leading half presents an enhancement of the star formation rate with respect to the trailing half. We conclude that galaxies falling into the intra-cluster medium experience a boost in star-formation in their leading half due to ram pressure. Sparse observations of jellyfish galaxies have revealed visually the enhancement of the star formation in the leading half. In order to confirm this effect statistically using observations, different cases must be investigated using the simulation as a test dataset.