Related papers: Seismic Inference using Genetic Algorithms
Estimates of seismic wave speeds in the Earth (seismic velocity models) are key input parameters to earthquake simulations for ground motion prediction. Owing to the non-uniqueness of the seismic inverse problem, typically many velocity…
Our understanding of exoplanet demographics partly depends on their corresponding host star parameters. With the majority of exoplanet-host stars having only atmospheric constraints available, robust inference of their parameters is…
In a series of papers, we have recently demonstrated that it is possible to construct stellar structure models that robustly mimic the stratification of multi-dimensional radiative magneto-hydrodynamic simulations at every time-step of the…
Gravitational wave observatories have always been affected by tele-seismic earthquakes leading to a decrease in duty cycle and coincident observation time. In this analysis, we leverage the power of machine learning algorithms and archival…
We present a machine learning method to assign stellar parameters (temperature, surface gravity, metallicity) to the photometric data of large photometric surveys such as SDSS and SKYMAPPER. The method makes use of our previous effort in…
How important is an independent diameter measurement for the determination of stellar parameters of solar-type stars? When coupled with seismic observables, how well can we determine the stellar mass? If we can determine the radius of the…
Core overshoot is a large source of uncertainty in constructing stellar models. Whether the amount of overshoot is constant or mass dependent is not completely known, even though models sometimes assume a mass-based trend. In this work we…
Context. Generative models open up the possibility to interrogate scientific data in a more data-driven way. Aims: We propose a method that uses generative models to explore hypotheses in astrophysics and other areas. We use a neural…
The unprecedented amount and the excellent quality of lensing data that the upcoming ground- and space-based surveys will produce represent a great opportunity to shed light on the questions that still remain unanswered concerning our…
High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of…
Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience foundation models (GFMs) emerge as a paradigm-shifting…
For many years, astronomers interested in white dwarf stars have promised that the study of these relatively simple compact objects would ultimately lead to useful information about the physics under extreme conditions of temperature and…
The goal of AIMS (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To…
The relations between observable stellar parameters are usually assumed to be deterministic. That is, given an infinitely precise measurement of independent variable, `$x$', and some model, the value of dependent variable, `$y$' can be…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
The study of fundamental properties (such as temperatures, radii, masses, and ages) and interior processes (such as convection and angular momentum transport) of stars has implications on various topics in astrophysics, ranging from the…
During this last decade our knowledge of the evolutionary properties of stars has significantly improved. This result has been achieved thanks to our improved understanding of the physical behavior of stellar matter in the thermal regimes…
Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…
Gravitational waves (GWs) cause the apparent position of distant stars to oscillate with a characteristic pattern on the sky. Astrometric measurements (e.g. those made by Gaia) therefore provide a new way to search for GWs. The main…
The growth of sky surveys and the large amount of stellar spectra in the current databases, has generated the necessity of developing new methods to estimate atmospheric parameters, a fundamental task on stellar research. In this work we…