Related papers: Popsynth: A generic astrophysical population synth…
Individual-level data (microdata) that characterizes a population, is essential for studying many real-world problems. However, acquiring such data is not straightforward due to cost and privacy constraints, and access is often limited to…
A theoretical approach relying on evolutionary population synthesis models could help refining the search criteria in deep galaxy surveys on the basis of a better knowledge of the expected apparent photometric properties of high-redshift…
Synthetic population generation is the process of combining multiple socioeconomic and demographic datasets from different sources and/or granularity levels, and downscaling them to an individual level. Although it is a fundamental step for…
Synthesis models predict the integrated properties of stellar populations. Several problems exist in this field, mostly related to the fact that integrated properties are distributed. To date, this aspect has been either ignored (as in…
The current state-of-the-art of population synthesis is reviewed. The field is currently undergoing major revisions with the recognition of several key processes as new critical ingredients. Stochastic effects can artificially enhance or…
We present Artificial Stellar Populations (ArtPop), an open-source Python package for synthesizing stellar populations and generating artificial images of fully populated stellar systems. The code is designed to be intuitive to use and as…
The discovery of the first two macroscopic interstellar objects (ISOs) passing through the Solar System has opened entirely new perspectives in planetary science. The exploration of these objects offers a qualitatively new insight into the…
We present a novel population-based Bayesian inference approach to model the average and population variance of spatial distribution of a set of observables from ensemble analysis of low signal-to-noise ratio measurements. The method…
In stellar astrophysics, the technique of population synthesis has been successfully used for several decades. For planets, it is in contrast still a young method which only became important in recent years because of the rapid increase of…
As observational datasets become larger and more complex, so too are the questions being asked of these data. Data simulations, i.e., synthetic data with properties (pixelization, noise, PSF, artifacts, etc.) akin to real data, are…
With the increasing number of exoplanets discovered, statistical properties of the population as a whole become unique constraints on planet formation models provided a link between the description of the detailed processes playing a role…
The planetary population synthesis method aims at comprehensively testing planet formation theories against observational evidence and providing theoretical sets of planets to help interpret observations and inform instrument development.…
The stellar population synthesis in unresolved composite objects is a very tricky problem. Indeed, it is a degenerate problem since many parameters affect the observables. The stellar population synthesis issue thus deserves a deep and…
popclass is a python package that provides a flexible, probabilistic framework for classifying the lens of a gravitational microlensing event. popclass allows a user to match characteristics of a microlensing signal to a simulation of the…
We present an extension of the pop-cosmos model for the evolving galaxy population up to redshift $z\sim6$. The model is trained on distributions of observed colors and magnitudes, from 26-band photometry of $\sim420,000$ galaxies in the…
Accurate simulation of astronomical observations is a critical element for any modern analyses, be it to measure event rates, analyses population properties, validate or train pipelines, account for selection effects, or correct biases. We…
We present pop-cosmos: a comprehensive model characterizing the galaxy population, calibrated to $140,938$ ($r<25$ selected) galaxies from the Cosmic Evolution Survey (COSMOS) with photometry in $26$ bands from the ultra-violet to the…
We present an efficient Bayesian method for estimating individual photometric redshifts and galaxy properties under a pre-trained population model (pop-cosmos) that was calibrated using purely photometric data. This model specifies a prior…
In general, synthesis models provide the mean value of the distribution of possible integrated luminosities, this distribution (and not only its mean value) being the actual description of the integrated luminosity. Therefore, to obtain the…
We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from…