Related papers: Spectroscopy Made Easy: Evolution
Accurately measuring the masses of white dwarf stars is crucial in many astrophysical contexts (e.g., asteroseismology and cosmochronology). These masses are most commonly determined by fitting a model atmosphere to an observed spectrum;…
We developed a scan mirror mechanism (SMM) that enable a slit-based spectrometer or spectropolarimeter to precisely and quickly map an astronomical object. The SMM, designed to be installed in the optical path preceding the entrance slit,…
As satellite networks evolve to support increasingly diverse services and artificial general intelligence (AGI), large language models (LLMs) are emerging as a critical foundation for future space systems. However, deploying LLMs on…
We are developing a brand new stellar population models with flexible chemistry (isochrones plus stellar colors and spectra) in order to set a new standard of completeness and excellence. Here we present preliminary results to assess the…
Stellar model atmospheres form the basis for any element abundance determination and hence are crucial ingredients for studies of stellar, galactic and cosmic evolution. With recent observational progress with the advent of 8m-class…
Measuring the orbits of directly-imaged exoplanets requires precise astrometry at the milliarcsec level over long periods of time due to their wide separation to the stars ($\gtrsim$10 au) and long orbital period ($\gtrsim$20 yr). To reach…
Stratospheric aerosols play an important role in the earth system and can affect the climate on timescales of months to years. However, estimating the characteristics of partially observed aerosol injections, such as those from volcanic…
One of the few ways that we can understand the environment around dusty stars and how much material they contribute back to the Universe, is by fitting their brightness at different wavelengths with models that account for how the energy…
This paper presents a practical approach for detecting non-stationarity in time series prediction. This method is called SAFE and works by monitoring the evolution of the spectral contents of time series through a distance function. This…
Mass is the most important stellar parameter, but it is not directly observable for a single star. Spherical model stellar atmospheres are explicitly characterized by their luminosity ($L_\star$), mass ($M_\star$) and radius ($R_\star$),…
Analyses of stellar spectra often begin with the determination of a number of parameters that define a model atmosphere. This work presents a prototype for an automated spectral classification system that uses a 15 nm-wide region around…
The determination of photospheric abundances in late-type stars from spectroscopic observations is a well-established field, built on solid theoretical foundations. Improving those foundations to refine the accuracy of the inferred…
Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the earth and different…
Modern stellar structure and evolution theory experiences a lack of observational calibrations for the interior physics of intermediate- and high-mass stars. This leads to discrepancies between theoretical predictions and observed phenomena…
Traditionally, a simulation of a dense stellar system required choosing an initial model, running an integrator, and analyzing the output. Almost all of the effort went into writing a clever integrator that could handle binaries, triples…
We describe the scientific motivations, the mission concept and the instrumentation of SPACE, a class-M mission proposed for concept study at the first call of the ESA Cosmic-Vision 2015-2025 planning cycle. SPACE aims to produce the…
In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a…
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…
Scanning transmission electron microscopy (STEM) has advanced rapidly in the last decade thanks to the ability to correct the major aberrations of the probe forming lens. Now atomic-sized beams are routine, even at accelerating voltages as…
The sparsity-restricted maximum likelihood estimator (SMLE) has received considerable attention for feature screening in ultrahigh-dimensional regression. SMLE is a computationally convenient method that naturally incorporates the joint…