相关论文: Sensitivity analyses of dense cloud chemical model…
Estimation of model parameters of computer simulators, also known as calibration, is an important topic in many engineering applications. In this paper, we consider the calibration of computer model parameters with the help of engineering…
Water (H2O) ice is an important solid constituent of many astrophysical environments. To comprehend the role of such ices in the chemistry and evolution of dense molecular clouds and comets, it is necessary to understand the freeze-out,…
In heavy-ion collisions, nuclear matter is subjected to extreme conditions in a highly dynamical, rapidly evolving environment. This poses a tremendous challenge for calculating jet quenching observables. Current approaches rely on…
Massive young stellar objects in the Magellanic Clouds show infrared absorption features corresponding to significant abundances of CO, CO$_2$ and H$_2$O ice along the line of sight, with the relative abundances of these ices differing…
Accurate measurements of fundamental cosmological parameters, especially the Hubble constant (H_0) and present-day matter density (\Omega_{m0}), are crucial for constraining dark energy (DE) evolution. We analyze the sensitivities of…
In order to optimize the performance of gas-jet targets for future nuclear reaction measurements, a detailed understanding of the dependence of the gas-jet properties on experiment design parameters is required. Common methods of gas-jet…
We provide an efficient method to approximate the covariance between decision variables and uncertain parameters in solutions to a general class of stochastic nonlinear complementarity problems. We also develop a sensitivity metric to…
This paper continues our previous work on a nanostructural evolution model for Fe-C alloys under irradiation, using Object Kinetic Monte Carlo modeling techniques. We here present a number of sensitivity studies of parameters of the model,…
The observed gas-phase molecular inventory of hot cores is believed to be significantly impacted by the products of chemistry in interstellar ices. In this study, we report the construction of a full macroscopic Monte Carlo model of both…
Computational studies of chemical reactions in complex environments such as proteins, nanostructures, or on surfaces require accurate and efficient atomistic models applicable to the nanometer scale. In general, an accurate parametrization…
We employ the Delta-variance analysis and study the turbulent gas dynamics of simulated molecular clouds (MCs). Our models account for a simplified treatment of time-dependent chemistry and the non-isothermal nature of the gas. We…
The IceCube Neutrino Observatory is highly sensitive to neutrino bursts of $\mathcal{O}$(10) MeV energy that are would be generated by core collapse supernovae in our Galaxy. It will resolve temporal structures in supernova light curves…
A weak-rate library aimed at investigating the sensitivity of astrophysical environments to variations of electron-capture rates on medium-heavy nuclei has been developed. With this library, the sensitivity of the core-collapse and early…
The COBE microwave background temperature fluctuations and the abundance of local rich clusters of galaxies provide the two most powerful constraints on cosmological models. When all variants of the standard cold dark matter (CDM) model are…
We have extensively mapped a sample of dense molecular clouds (L1512, TMC-1C, L1262, Per 7, L1389, L1251E) in lines of HC3N, CH3OH, SO and C^{18}O. We demonstrate that a high degree of chemical differentiation is present in all of the…
We present the chemistry, temperature, and dynamical state of a sample of 193 dense cores or core candidates in the Perseus Molecular cloud and compare the properties of cores associated with young stars and clusters with those which are…
Investigating star formation requires precise knowledge of the properties of the dense molecular gas. The low metallicity and wide range of star formation activity of the Large and Small Magellanic Clouds make them prime laboratories to…
Chemical space which encompasses all stable compounds is unfathomably large and its dimension scales linearly with the number of atoms considered. The success of machine learning methods suggests that many physical quantities exhibit…
The propagation of uncertainties in reaction cross sections and rates of neutron-, proton-, and $\alpha$-induced reactions into the final isotopic abundances obtained in nucleosynthesis models is an important issue in studies of…
We formulate an optimization problem to estimate probability densities in the context of multidimensional problems that are sampled with uneven probability. It considers detector sensitivity as an heterogeneous density and takes advantage…