Related papers: Flow-Based Generative Emulation of Grids of Stella…
Stellar granulation arises from near-surface convection and is imprinted in stellar photometric time series, yet links between granulation observables and fundamental stellar properties remain underexploited. We aim to establish a…
In this work we combine information from solar-like oscillations, high-resolution spectroscopy and Gaia astrometry to derive stellar ages, chemical abundances and kinematics for a group of seven metal-poor Red Giants and characterise them…
A generative model based on a continuous-time normalizing flow between any pair of base and target probability densities is proposed. The velocity field of this flow is inferred from the probability current of a time-dependent density that…
Mass changes due to strong stellar winds and binary mass transfer have a dramatic impact on the consequent evolution of stars. This is generally not accounted for in population synthesis codes which are built using single star evolution…
The performance of flow matching and diffusion models can be greatly improved at inference time using reward alignment algorithms, yet efficiency remains a major limitation. While several algorithms were proposed, we demonstrate that a…
Flow-based generative models have highly desirable properties like exact log-likelihood evaluation and exact latent-variable inference, however they are still in their infancy and have not received as much attention as alternative…
We present a multi-epoch analysis of the galaxy populations formed within the cosmological hydrodynamical simulations presented in Vogelsberger et al. (2013). These simulations explore the performance of a recently implemented feedback…
Red giants are evolved stars that have exhausted the supply of hydrogen in their cores and instead burn hydrogen in a surrounding shell. Once a red giant is sufficiently evolved, the helium in the core also undergoes fusion. Outstanding…
The demographics of Kepler planets provide a key testbed for models of planet formation and evolution, particularly for explaining the radius valley separating super-Earths and sub-Neptunes. A primordial interpretation based on differences…
By means of our own cosmological-hydrodynamical simulation and semi-analytical model we studied galaxy population properties in clusters and groups, spanning over 10 different bands from UV to NIR, and their evolution since redshift z=2. We…
Accurate simulation of granular flow dynamics is crucial for assessing various geotechnical risks, including landslides and debris flows. Granular flows involve a dynamic rearrangement of particles exhibiting complex transitions from…
The cornerstone mission Gaia, together with complementary surveys, will revolutionize our understanding of the formation and history of our Galaxy, providing accurate stellar masses, radii, ages, distances, as well as chemical properties…
Asteroseismic parameters allow us to measure the basic stellar properties of field giants observed far across the Galaxy. Most of such determinations are, up to now, based on simple scaling relations involving the large frequency…
We compile a number of observations to estimate the time-averaged rate of formation or buildup of red sequence galaxies, as a function of mass and redshift. Comparing this with the mass functions of mergers and quasar hosts, and…
Normalizing flows are a powerful tool to create flexible probability distributions with a wide range of potential applications in cosmology. Here we are studying normalizing flows which represent cosmological observables at field level,…
We develop a novel method based on machine learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-D parameter space. A deep neural network is trained on a precomputed…
We introduce a framework for simultaneously investigating the structure and luminosity evolution of early-type gravitational lens galaxies. The method is based on the fundamental plane, which we interpret using the aperture mass-radius…
This paper presents the first results from a model for chemical evolution that can be applied to N-body cosmological simulations and quantitatively compared to measured stellar abundances from large astronomical surveys. This model…
Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions. However, a central challenge in video prediction is that the future is…
A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo and Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stochastic…