All Outputs (7)

The Three Hundred Project: Connection between star formation quenching and dynamical evolution in and around simulated galaxy clusters (2022)
Journal Article
Hough, T., Cora, S. A., Haggar, R., Vega-Martinez, C., Kuchner, U., Pearce, F., Gray, M., Knebe, A., & Yepes, G. (2023). The Three Hundred Project: Connection between star formation quenching and dynamical evolution in and around simulated galaxy clusters. Monthly Notices of the Royal Astronomical Society, 518(2), 2398-2417. https://doi.org/10.1093/mnras/stac3209

In this work, we combine the semi-analytic model of galaxy formation and evolution SAG with the 102 relaxed simulated galaxy clusters from THE THREE HUNDRED project, and we study the link between the quenching of star formation (SF) and the physical... Read More about The Three Hundred Project: Connection between star formation quenching and dynamical evolution in and around simulated galaxy clusters.

The Three Hundred project: Galaxy groups do not survive cluster infall (2022)
Journal Article
Haggar, R., Kuchner, U., Gray, M. E., Pearce, F. R., Knebe, A., Yepes, G., & Cui, W. (2023). The Three Hundred project: Galaxy groups do not survive cluster infall. Monthly Notices of the Royal Astronomical Society, 518(1), 1316-1334. https://doi.org/10.1093/mnras/stac2809

Galaxy clusters grow by accreting galaxies as individual objects, or as members of a galaxy group. These groups can strongly impact galaxy evolution, stripping the gas from galaxies, and enhancing the rate of galaxy mergers. However, it is not clear... Read More about The Three Hundred project: Galaxy groups do not survive cluster infall.

Forecasting the success of the WEAVE Wide-Field Cluster Survey on the extraction of the cosmic web filaments around galaxy clusters (2022)
Journal Article
Cornwell, D. J., Kuchner, U., Aragón-Salamanca, A., Gray, M. E., Pearce, F. R., Aguerri, J. A. L., Cui, W., Méndez-Abreu, J., de Arriba, L. P., & Trager, S. C. (2022). Forecasting the success of the WEAVE Wide-Field Cluster Survey on the extraction of the cosmic web filaments around galaxy clusters. Monthly Notices of the Royal Astronomical Society, 517(2), 1678–1694. https://doi.org/10.1093/mnras/stac2777

Next-generation wide-field spectroscopic surveys will observe the infall regions around large numbers of galaxy clusters with high sampling rates for the first time. Here we assess the feasibility of extracting the large-scale cosmic web around clust... Read More about Forecasting the success of the WEAVE Wide-Field Cluster Survey on the extraction of the cosmic web filaments around galaxy clusters.

The Three Hundred project: The gizmo-simba run (2022)
Journal Article
Cui, W., Dave, R., Knebe, A., Rasia, E., Gray, M., Pearce, F., Power, C., Yepes, G., Anbajagane, D., Ceverino, D., Contreras-Santos, A., de Andres, D., De Petris, M., Ettori, S., Haggar, R., Li, Q., Wang, Y., Yang, X., Borgani, S., Dolag, K., …Gianfagna, G. (2022). The Three Hundred project: The gizmo-simba run. Monthly Notices of the Royal Astronomical Society, 514(1), 977-996. https://doi.org/10.1093/mnras/stac1402

We introduce gizmo-simba, a new suite of galaxy cluster simulations within The Three Hundred project. The Three Hundred consists of zoom re-simulations of 324 clusters with M 200≳ 1014.8, M ⊙ drawn from the MultiDark-Planck N-body simulation, run usi... Read More about The Three Hundred project: The gizmo-simba run.

A Simulation-driven Deep Learning Approach for Separating Mergers and Star-forming Galaxies: The Formation Histories of Clumpy Galaxies in All of the CANDELS Fields (2022)
Journal Article
Ferreira, L., Conselice, C. J., Kuchner, U., & Tohill, C.-B. (2022). A Simulation-driven Deep Learning Approach for Separating Mergers and Star-forming Galaxies: The Formation Histories of Clumpy Galaxies in All of the CANDELS Fields. Astrophysical Journal, 931(1), Article 34. https://doi.org/10.3847/1538-4357/ac66ea

Being able to distinguish between galaxies that have recently undergone major-merger events, or are experiencing intense star formation, is crucial for making progress in our understanding of the formation and evolution of galaxies. As such, we have... Read More about A Simulation-driven Deep Learning Approach for Separating Mergers and Star-forming Galaxies: The Formation Histories of Clumpy Galaxies in All of the CANDELS Fields.

The Value of ArtScience: improving the balance in collaboration practices between artists and scientists can impact knowledge production (2022)
Journal Article
Kuchner, U. (2022). The Value of ArtScience: improving the balance in collaboration practices between artists and scientists can impact knowledge production. Writing Visual Culture, 10.0, 23-42

In a time in which scientific knowledge is in danger of being discredited, we return to the responsibility of art and science. There is widespread optimism that collaborations between artists and scientists can develop solutions to complex problems,... Read More about The Value of ArtScience: improving the balance in collaboration practices between artists and scientists can impact knowledge production.

Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models (2022)
Journal Article
Bretonnière, H., Huertas-Company, M., Boucaud, A., Lanusse, F., Jullo, E., Merlin, E., Tuccillo, D., Castellano, M., Brinchmann, J., Conselice, C. J., Dole, H., Cabanac, R., Courtois, H. M., Castander, F. J., Duc, P. A., & Kuchner, U. (2022). Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models. Astronomy and Astrophysics, 657, Article A90. https://doi.org/10.1051/0004-6361/202141393

We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method combines a control on galaxy sha... Read More about Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models.