Related papers: Linking Stochastic Self-Propagating Star Formation…
We model the spatial dynamics of a forest stand by using a special class of spatio-temporal point processes, the sequential spatial point process, where the spatial dimension is parameterized and the time component is atomic. The sequential…
We present a large sample of fully self-consistent hydrodynamical Nbody/Tree-SPH simulations of isolated dwarf spheroidal galaxies (dSphs). It has enabled us to identify the key physical parameters and mechanisms at the origin of the…
We offer a simple parameterization of the rate of star formation in galaxies. In this new approach, we make explicit and decouple the timescales associated (a) with disruptive effects the star formation event itself, from (b) the timescales…
Stochastic partition models tailor a product space into a number of rectangular regions such that the data within each region exhibit certain types of homogeneity. Due to constraints of partition strategy, existing models may cause…
All modern galaxy formation models employ stochastic elements in their sub-grid prescriptions to discretise continuous equations across the time domain. In this paper, we investigate how the stochastic nature of these models, notably star…
The time-dependent Ginzburg-Landau equation and the Swift-Hohenberg equation, both added with a stochastic term, are proposed to describe cloud pattern formation and cloud regime phase transitions of shallow convective clouds organized in…
An important class of spatio-temporal models is constructed by leveraging the hierarchical structure of dynamical (or, state-space) models. This paper proposes a new statistical dynamical model for spatio-temporal processes motivated by…
The star formation rate - stellar mass relation (SFR-M*) and its evolution (i.e., the SFR main sequence) describes the growth rate of galaxies of a given stellar mass and at a given redshift. Assuming that present-day star-forming galaxies…
Star formation in galaxies relies on the availability of cold, dense gas, which, in turn, relies on factors internal and external to the galaxies. In order to provide a simple model for how star formation is regulated by various physical…
This work proposes stochastic partial differential equations (SPDEs) as a practical tool to replicate clustering effects of more detailed particle-based dynamics. Inspired by membrane-mediated receptor dynamics on cell surfaces, we…
Feedback from supernovae is essential to understanding the self-regulation of star formation in galaxies. However, the efficacy of the process in a cosmological context remains unclear due to excessive radiative losses during the shock…
We present a novel methodology to improve predictions of galaxy formation histories by incorporating semi-stochastic corrections to account for short-timescale variability. Our paper addresses limitations in existing models that capture…
We use new and updated gas and dust-corrected SFR surface densities to revisit the integrated star formation law for local "quiescent" spiral, dwarf, and low-surface-brightness galaxies. Using UV-based SFRs with individual IR-based dust…
Since the early 1970s, stellar population modelling has been one of the basic tools for understanding the physics of unresolved systems from observation of their integrated light. Models allow us to relate the integrated spectra (or…
We analyze star formation (SF) as a function of stellar mass (M_*) and redshift z in the All Wavelength Extended Groth Strip International Survey (AEGIS), for star-forming field galaxies with M_* >~ 10^10 M_sun out to z=1.1. The data…
We present a model for the origin of the extended law of star formation in which the surface density of star formation ($\Sigma_{\rm SFR}$) depends not only on the local surface density of the gas ($\Sigma_{g}$), but also on the stellar…
We analyze new optical spectra of a sample of 502 galaxies in close pairs and n-tuples, separated by <= 50/h kpc. We extracted the sample objectively from the CfA2 redshift survey, without regard to the surroundings of the tight systems. We…
We use vertically-resolved numerical hydrodynamic simulations to study star formation and the interstellar medium (ISM) in galactic disks. We focus on outer disk regions where diffuse HI dominates, with gas surface densities Sigma_SFR=3-20…
We study the spatio-temporal prediction problem and introduce a novel point-process-based prediction algorithm. Spatio-temporal prediction is extensively studied in Machine Learning literature due to its critical real-life applications such…
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically…