Related papers: Intercomparison of Brown Dwarf Model Grids and Atm…
We propose a new T, Y dwarf search model using machine learning (ML), called the "BROWn Dwarf Image Explorer (BROWDIE). Brown dwarfs (BD) are estimated to make up 25 percent of all celestial objects in the Galaxy, yet only a small number…
We present an approach to identifying and characterizing unresolved, very low mass spectral blend binaries composed of late-M, L, and T dwarfs using machine learning methodologies. We generated and evaluated a series of hierarchical random…
Brown dwarfs are commonly regarded as easily-observed templates for exoplanet studies, with comparable masses, physical sizes and atmospheric properties. There is indeed considerable overlap in the photospheric temperatures of the coldest…
Clouds seem like an every-day experience. But -- do we know how clouds form on brown dwarfs and extra-solar planets? How do they look like? Can we see them? What are they composed of? Cloud formation is an old-fashioned but still…
Brown dwarfs and exoplanets are thought to host complex atmospheric phenomena such as clouds, storms, and chemical heterogeneity, akin to weather patterns on Earth. These features can produce pronounced spectral variability.…
Quantification of forest biomass stocks and their dynamics is important for implementing effective climate change mitigation measures. The knowledge is needed, e.g., for local forest management, studying the processes driving af-, re-, and…
Atmospheric retrieval of exoplanets from spectroscopic observations requires an extensive exploration of a highly degenerate and high-dimensional parameter space to accurately constrain atmospheric parameters. Retrieval methods commonly…
Heat stress is one of the main welfare and productivity problems faced by dairy cattle in Mediterranean climates. In this study, we approach the prediction of the daily shade-seeking count as a non-linear multivariate regression problem and…
The representation of nonlinear sub-grid processes, especially clouds, has been a major source of uncertainty in climate models for decades. Cloud-resolving models better represent many of these processes and can now be run globally but…
The atmosphere of a brown dwarf or extrasolar giant planet controls the spectrum of radiation emitted by the object and regulates its cooling over time. While the study of these atmospheres has been informed by decades of experience…
Benchmark brown dwarfs in wide binary systems are crucial for characterizing substellar objects and calibrating atmospheric and evolutionary models. However, brown dwarf benchmarks with subsolar metallicity, very cool temperatures, or…
M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is…
Analysis of initial observations from near-infrared sky surveys has shown that the resulting photometric catalogues, combined with far-red optical data, provide an extremely effective method of finding isolated, very low-temperature objects…
The prediction of crop yields internationally is a crucial objective in agricultural research. Thus, this study implements 6 regression models (Linear, Tree, Gradient Descent, Gradient Boosting, K Nearest Neighbors, and Random Forest) to…
The atmospheres of brown dwarfs orbiting in close proximity to their parent white dwarf represent some of the most extreme irradiated environments known. Understanding their complex dynamical mechanisms pushes the limits of theoretical and…
Ultracool dwarf stars and brown dwarfs provide a unique probe of large-scale Galactic structure and evolution; however, until recently spectroscopic samples of sufficient size, depth, and fidelity have been unavailable. Here, we present the…
The increasing global demand for clean and environmentally friendly energy resources has caused increased interest in harnessing solar power through photovoltaic (PV) systems for smart grids and homes. However, the inherent unpredictability…
Understanding the future climate is crucial for informed policy decisions on climate change prevention and mitigation. Earth system models play an important role in predicting future climate, requiring accurate representation of complex…
Many machine learning (ML) approaches are widely used to generate bioclimatic models for prediction of geographic range of organism as a function of climate. Applications such as prediction of range shift in organism, range of invasive…
Most directly imaged giant exoplanets are fainter than brown dwarfs with similar spectra. To explain their relative underluminosity unusually cloudy atmospheres have been proposed. However, with multiple parameters varying between any two…