Related papers: The 2017 Release of Cloudy
Deep high-dispersion spectroscopy of Galactic photoionized gaseous nebulae, mainly planetary nebulae and HII regions, has revealed numerous emission lines. As a key step of spectral analysis, identification of emission lines hitherto has…
We present hydrodynamic simulations of high-velocity clouds (HVCs) traveling through the hot, tenuous medium in the Galactic halo. A suite of models was created using the FLASH hydrodynamics code, sampling various cloud sizes, densities,…
Meteorologists use shapes and movements of clouds in satellite images as indicators of several major types of severe storms. Satellite imaginary data are in increasingly higher resolution, both spatially and temporally, making it impossible…
There has been a growing request from the X-ray astronomy community for a quantitative estimate of systematic uncertainties originating from the atomic data used in plasma codes. Though there have been several studies looking into atomic…
Mobile deep vision systems play a vital role in numerous scenarios. However, deep learning applications in mobile vision scenarios face problems such as tight computing resources. With the development of edge computing, the architecture of…
The ability to analyze and forecast stratospheric weather conditions is fundamental to addressing climate change. However, our capacity to collect data in the stratosphere is limited by sparsely deployed weather balloons. We propose a…
Recent observations with the Submillimeter Wave Astronomy Satellite indicate abundances of gaseous H2O and O2 in dense molecular clouds which are significantly lower than found in standard homogeneous chemistry models. We present here…
Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets…
We analyse synthetic $^{12}$CO, $^{13}$CO, and [CII] emission maps of simulated molecular clouds of the SILCC-Zoom project, which include an on-the-fly evolution of H$_2$, CO, and C$^+$. We use simulations of hydrodynamical and…
Obtaining predictive low-order models is a central challenge in fluid dynamics. Data-driven frameworks have been widely used to obtain low-order models of aerodynamic systems; yet, resulting models tend to yield predictions that grow…
Unlike image or text domains that benefit from an abundance of large-scale datasets, point cloud learning techniques frequently encounter limitations due to the scarcity of extensive datasets. To overcome this limitation, we present…
We present new observations of [CII] fine structure line emission from an isolated molecular cloud using the upGREAT instrument onboard SOFIA. These data are analyzed together with archival CO=1-0 and HI 21 cm emission spectra to…
Version 11 of the CHIANTI database and software package is presented. Advanced ionization equilibrium models have been added for low charge states of seven elements (C, N, O, Ne, Mg, Si and S), and represent a significant improvement…
We present version 10 of the CHIANTI package. In this release, we provide updated atomic models for several helium-like ions and for all the ions of the beryllium, carbon and magnesium isoelectronic sequences that are abundant in…
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…
Because of new telescopes that will dramatically improve our knowledge of the interstellar medium, chemical models will have to be used to simulate the chemistry of many regions with diverse properties. To make these models more robust, it…
We present a new method aimed at improving the efficiency of component by component ionization modeling of intervening quasar absorption line systems. We carry out cloud-by-cloud, multiphase modeling making use of CLOUDY and Bayesian…
A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning-based parameterizations using output from global storm-resolving models. While neural networks…
Cloud-based software has many advantages. When services are divided into many independent components, they are easier to update. Also, during peak demand, it is easier to scale cloud services (just hire more CPUs). Hence, many organizations…
With the advancement of technology, the data generated in our lives is getting faster and faster, and the amount of data that various applications need to process becomes extremely huge. Therefore, we need to put more effort into analyzing…