activity
20182021
most citedThe tidal evolution of dark matter substructure -- I. Subhalo density profiles

70 citations · 157 across the 3 of their papers we have counts for

collaborators

9 papers

astro-ph.GA2021

The tidal evolution of dark matter substructure -- II. The impact of artificial disruption on subhalo mass functions and radial profiles

Sheridan B. Green, Frank C. van den Bosch, Fangzhou Jiang

Several recent studies have indicated that artificial subhalo disruption (the spontaneous, non-physical disintegration of a subhalo) remains prevalent in state-of-the-art dark matt…

astro-ph.GA2020

SatGen: a semi-analytical satellite galaxy generator -- I. The model and its application to Local-Group satellite statistics

Fangzhou Jiang, Avishai Dekel, Jonathan Freundlich +5

We present a semi-analytic model of satellite galaxies, SatGen, which can generate large samples of satellite populations for a host halo of desired mass, redshift, and assembly hi…

astro-ph.CO2020

Scatter in Sunyaev--Zel'dovich effect scaling relations explained by inter-cluster variance in mass accretion histories

Sheridan B. Green, Han Aung, Daisuke Nagai +1

X-ray and microwave cluster scaling relations are immensely valuable for cosmological analysis. However, their power is limited by astrophysical systematics that bias mass estimate…

astro-ph.GA2020

Dynamical self-friction: how mass loss slows you down

Tim B. Miller, Frank C. van den Bosch, Sheridan B. Green +1

We investigate dynamical self-friction, the process by which material that is stripped from a subhalo torques its remaining bound remnant, which causes it to lose orbital angular m…

astro-ph.GA201970 cited

The tidal evolution of dark matter substructure -- I. Subhalo density profiles

Sheridan B. Green, Frank C. van den Bosch

Accurately predicting the abundance and structural evolution of dark matter subhaloes is crucial for understanding galaxy formation, modeling galaxy clustering, and constraining th…

astro-ph.CO201934 cited

Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning

Sheridan B. Green, Michelle Ntampaka, Daisuke Nagai +4

We present a machine learning approach for estimating galaxy cluster masses, trained using both Chandra and eROSITA mock X-ray observations of 2,041 clusters from the Magneticum si…