相关论文: Machine learning-accelerated chemistry modeling of…

Interpreting the observations of exoplanet atmospheres to constrain physical and chemical properties is typically done using Bayesian retrieval techniques. Because these methods require many model computations, a compromise is made between…

The composition of planets is largely determined by the chemical and dynamical evolution of the disk during planetesimal formation and growth. To predict the diversity of exoplanet compositions, previous works modeled planetesimal…

Protoplanetary disks in massive star-forming regions may be exposed to ultraviolet radiation fields orders of magnitude stronger than the interstellar background. This intense radiation drives photoevaporative winds that fundamentally shape…

Synthesis prediction is a key accelerator for the rapid design of advanced materials. However, determining synthesis variables such as the choice of precursor materials is challenging for inorganic materials because the sequence of…

Early results from the JWST-MIRI guaranteed time programs on protostars (JOYS) and disks (MINDS) are presented. Thanks to the increased sensitivity, spectral and spatial resolution of the MIRI spectrometer, the chemical inventory of the…

Recent surveys of protoplanetary disks show that substructure in dust thermal continuum emission maps is common in protoplanetary disks. These substructures, most prominently rings and gaps, shape and change the chemical and physical…

Star formation often occurs within or nearby stellar clusters. Irradiation by nearby massive stars can photoevaporate protoplanetary disks around young stars (so-called proplyds) which raises questions regarding the ability of planet…

Observations of protoplanetary disks show that some characteristics seem recurrent, even in star formation regions that are physically distant such as surface mass density profiles varying as $r^{-1}$, or aspect ratios about 0.03 to 0.23.…

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical…

Revealing possible long-living coherence in ultrafast processes allows detecting genuine quantum mechanical effects in molecules. To investigate such effects from a quantum chemistry perspective, we have developed a method for simulating…

The distributions and abundances of molecules in protoplanetary disks are powerful tracers of the physical and chemical disk structures. The abundance ratios of HCN and its isomer HNC are known to be sensitive to gas temperature. Their line…

Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusive. This originates mostly from the fact that accurately…

Observations of molecular lines are a key tool to determine the main physical properties of prestellar cores. However, not all the information is retained in the observational process or easily interpretable, especially when a larger number…

The topic of the present study is combining a dynamic model of a protoplanetary disk with the computations of radiation transfer for obtaining synthetic spectra and disk images suitable for immediate comparison of the model with…

The upcoming new coronographs with deeper contrast limits, together with planned and current high-contrast imaging campaigns will push the detectability limit of protoplanets. These planet-hunting campaigns present a new opportunity to…

We review advances in the modeling of protoplanetary disks. This review will focus on the regions of the disk beyond the dust sublimation radius, i.e. beyond 0.1 - 1 AU, depending on the stellar luminosity. We will be mostly concerned with…

Low-temperature plasmas are partially ionized gases, where ions and neutrals coexist in a highly reactive environment. This creates a rich chemistry, which is often difficult to understand in its full complexity. In this work, we develop a…

We present a framework for accelerated iterative reconstructions using a fast and approximate forward model that is based on k-space methods for photoacoustic tomography. The approximate model introduces aliasing artefacts in the gradient…

Accurate thermal analysis of composites and porous media requires detailed characterization of local thermal properties in small scale. For some important applications such as lithium-ion batteries, changes in the properties during the…

We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…