We use sparse regression methods (SRMs) to build accurate and explainable models that predict the stellar mass of central and satellite galaxies as a function of properties of their host dark... Show moreWe use sparse regression methods (SRMs) to build accurate and explainable models that predict the stellar mass of central and satellite galaxies as a function of properties of their host dark matter haloes. SRMs are machine learning algorithms that provide a framework for modelling the governing equations of a system from data. In contrast with other machine learning algorithms, the solutions of SRM methods are simple and depend on a relatively small set of adjustable parameters. We collect data from 35 459 galaxies from the EAGLE simulation using 19 redshift slices between z = 0 and z = 4 to parametrize the mass evolution of the host haloes. Using an appropriate formulation of input parameters, our methodology can model satellite and central haloes using a single predictive model that achieves the same accuracy as when predicted separately. This allows us to remove the somewhat arbitrary distinction between those two galaxy types and model them based only on their halo growth history. Our models can accurately reproduce the total galaxy stellar mass function and the stellar mass-dependent galaxy correlation functions ((r)) of EAGLE. We show that our SRM model predictions of 4(r) is competitive with those from subhalo abundance matching and might be comparable to results from extremely randomized trees. We suggest SRM as an encouraging approach for populating the haloes of dark matter only simulations with galaxies and for generating mock catalogues that can be used to explore galaxy evolution or analyse forthcoming large-scale structure surveys. Show less
Borrow, J.; Schaller, M.; Bahé, Y.M.; Schaye, J.; Ludlow, A.D.; Ploeckinger, S.; ... ; Altamura, E. 2023
People cooperate every day in ways that range from largescale contributions that mitigate climatechange to simple actions such as leaving another individual with choice – known as social... Show morePeople cooperate every day in ways that range from largescale contributions that mitigate climatechange to simple actions such as leaving another individual with choice – known as social mindfulness.It is not yet clear whether and how these complex and more simple forms of cooperation relate. Priorwork has found that countries with individuals who made more socially mindful choices were linked toa higher country environmental performance – a proxy for complex cooperation. Here we replicatedthis initial finding in 41 samples around the world, demonstrating the robustness of the associationbetween social mindfulness and environmental performance, and substantially built on it to show thisrelationship extended to a wide range of complex cooperative indices, tied closely to many currentsocietal issues. We found that greater social mindfulness expressed by an individual was related toliving in countries with more social capital, more community participation and reduced prejudicetowards immigrants. Our findings speak to the symbiotic relationship between simple and morecomplex forms of cooperation in societies. Show less
Graaff, A.G. de; Trayford, J.W.; Franx, M.; Schaller, M.; Schaye, J.; Wel, A. van der 2022
