Related papers: Linking Stochastic Self-Propagating Star Formation…
Spatio-temporal point process (STPP) is a stochastic collection of events accompanied with time and space. Due to computational complexities, existing solutions for STPPs compromise with conditional independence between time and space,…
Spatio-temporal Hawkes point processes are a particularly interesting class of stochastic point processes for modeling self-exciting behavior, in which the occurrence of one event increases the probability of other events occurring. These…
Galaxy formation and evolution involves a variety of effectively stochastic processes that operate over different timescales. The Extended Regulator model provides an analytic framework for the resulting variability (or `burstiness') in…
We present a model of chemical and spectrophotometric evolution of disk galaxies based on a stochastic self-propagating star formation scenario. The model incorporates galaxy formation through the process of accretion, chemical and…
We study the spatio-temporal prediction problem, which has attracted the attention of many researchers due to its critical real-life applications. In particular, we introduce a novel approach to this problem. Our approach is based on the…
We present a framework for modelling the star-formation histories of galaxies as a stochastic process. We define this stochastic process through a power spectrum density with a functional form of a broken power-law. Star-formation histories…
Understanding the diversity of star formation histories (SFHs) of galaxies is key to reconstructing their evolutionary paths. Traditional models often assume parametric forms such as delayed-tau or exponentially declining models, which may…
Star-formation rates (SFR) of disk galaxies strongly correlate with stellar mass, with a small dispersion in SSFR at fixed mass, sigma~0.3 dex. With such small scatter this star-formation main sequence (SFMS) has been interpreted as…
Galactic scaling relations between the (surface densities of) the gas mass and the star formation (SF) rate are known to develop substantial scatter or even change form when considered below a certain spatial scale. We quantify how this…
We investigate spatio-temporal event analysis using point processes. Inferring the dynamics of event sequences spatiotemporally has many practical applications including crime prediction, social media analysis, and traffic forecasting. In…
We have incorporated star formation algorithms into a hybrid N-body/smoothed particle hydrodynamics code (TREESPH) in order to describe the star forming properties of disk galaxies over timescales of a few billion years. The models employ a…
The problem of chemical and dynamical evolution of galaxies is one of the most attracting and complex problems of modern astrophysics. Within the framework of the given work the standard dynamic Smoothed Particle Hydrodynamics (SPH) code…
We report on the discovery of a relation between the number of star formation (SF) peaks per unit time, $\nu_{\rm peak}$, and the size of the temporal smoothing window function, $\Delta t$, used to define the peaks: $\nu_{\rm…
We present a new method for deriving the stellar birth function (SBF) of resolved stellar populations. The SBF (stars born per unit mass, time, and metallicity) is the combination of the initial mass function (IMF), the star-formation…
Spatiotemporal point processes (STPPs) are probabilistic models for events occurring in continuous space and time. Real-world event data often exhibit intricate dependencies and heterogeneous dynamics. By incorporating modern deep learning…
Using a cosmological galactic evolutionary approach to model the Milky Way, we calculate the star formation history (SFH) of the solar neighborhood. The good agreement we obtain with the observational inferences suggests that our physical…
Self-exciting spatio-temporal point process models predict the rate of events as a function of space, time, and the previous history of events. These models naturally capture triggering and clustering behavior, and have been widely used in…
Marked temporal point processes (MTPPs) model sequences of events occurring at irregular time intervals, with wide-ranging applications in fields such as healthcare, finance and social networks. We propose the state-space point process…
Many events occur in the world. Some event types are stochastically excited or inhibited---in the sense of having their probabilities elevated or decreased---by patterns in the sequence of previous events. Discovering such patterns can help…
We present a novel method to model galactic scale star formation and the resulting emission from star clusters and the multi-phase interstellar medium. We combine global parameters, such as SFR and CMF, with {\sc warpfield} which provides a…