Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Moster, Benjamin"'
Autor:
O'Leary, Joseph A., Steinwandel, Ulrich P., Moster, Benjamin P., Martin, Nicolas, Naab, Thorsten
One of the primary goals when studying galaxy formation is to understand how the luminous component of the Universe, galaxies, relates to the growth of structure which is dominated by the gravitational collapse of dark matter haloes. The stellar-to-h
Externí odkaz:
http://arxiv.org/abs/2301.07122
Different properties of dark matter haloes, including growth rate, concentration, interaction history, and spin, correlate with environment in unique, scale-dependent ways. While these halo properties are not directly observable, galaxies will inheri
Externí odkaz:
http://arxiv.org/abs/2101.05280
Autor:
Sharma, Ray S., Choi, Ena, Somerville, Rachel S., Snyder, Gregory F., Kocevski, Dale D., Hirschmann, Michaela, Moster, Benjamin P., Naab, Thorsten, Narayanan, Desika, Ostriker, Jeremiah P., Rosario, David J.
We analyze a suite of $30$ high resolution zoom-in cosmological hydrodynamic simulations of massive galaxies with stellar masses $M_{\ast} > 10^{10.9} M_\odot$, with the goal of better understanding merger activity in AGN, AGN activity in merging sys
Externí odkaz:
http://arxiv.org/abs/2101.01729
Autor:
Valenzuela, Lucas M., Moster, Benjamin P., Remus, Rhea-Silvia, O'Leary, Joseph A., Burkert, Andreas
We present an empirical model for the number of globular clusters (GCs) in galaxies based on recent data showing a tight relationship between dark matter halo virial masses and GC numbers. While a simple base model forming GCs in low-mass haloes repr
Externí odkaz:
http://arxiv.org/abs/2012.09172
We introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. We aim to exploit some of thes
Externí odkaz:
http://arxiv.org/abs/2011.14135
Theoretical models are vital for exploring the galaxy merger process, which plays a crucial role in the evolution of galaxies. Recent advances in modelling have placed tight constraints on the buildup of stellar material in galaxies across cosmic tim
Externí odkaz:
http://arxiv.org/abs/2011.05341
Autor:
Behroozi, Peter, Conroy, Charlie, Wechsler, Risa H., Hearin, Andrew, Williams, Christina C., Moster, Benjamin P., Yung, L. Y. Aaron, Somerville, Rachel S., Gottlöber, Stefan, Yepes, Gustavo, Endsley, Ryan
The James Webb Space Telescope (JWST) is expected to observe galaxies at $z>10$ that are presently inaccessible. Here, we use a self-consistent empirical model, the UniverseMachine, to generate mock galaxy catalogues and lightcones over the redshift
Externí odkaz:
http://arxiv.org/abs/2007.04988
We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics using reinforcement learning. The most important halo properties to pre
Externí odkaz:
http://arxiv.org/abs/2005.12276
We explore the galaxy-galaxy merger rate with the empirical model for galaxy formation, Emerge. On average, we find that between $2$ per cent and $20$ per cent of massive galaxies ($\log_{10}(m_{*}/M_{\odot}) \geq 10.3$) will experience a major merge
Externí odkaz:
http://arxiv.org/abs/2001.02687
Autor:
Shankar, Francesco, Weinberg, David H., Marsden, Christopher, Grylls, Philip J., Bernardi, Mariangela, Yang, Guang, Moster, Benjamin, Carraro, Rosamaria, Alexander, David M., Allevato, Viola, Ananna, Tonima T., Bongiorno, Angela, Calderone, Giorgio, Civano, Francesca, Daddi, Emanuele, Delvecchio, Ivan, Duras, Federica, La Franca, Fabio, Lapi, Andrea, Lu, Youjun, Menci, Nicola, Mezcua, Mar, Ricci, Federica, Rodighiero, Giulia, Sheth, Ravi K., Suh, Hyewon, Villforth, Carolin, Zanisi, Lorenzo
The masses of supermassive black holes at the centres of local galaxies appear to be tightly correlated with the mass and velocity dispersions of their galactic hosts. However, the local Mbh-Mstar relation inferred from dynamically measured inactive
Externí odkaz:
http://arxiv.org/abs/1912.06153