Related papers: Gaussian Process Model for Collision Dynamics of C…
We develop a new numerical algorithm to model collisional cascades in debris disks. Because of the large dynamical range in particle masses, we solve the integro-differential equations describing erosive and catastrophic collisions in a…
Planetary-scale collisions are common during the last stages of formation of solid planets, including the Solar system terrestrial planets. The problem of growing planets has been divided into studying the gravitational interaction of…
We introduce the ideal Gaussian glass-forming system as a model to describe the thermodynamics and dynamics of supercooled liquids on a local scale in terms of the properties of the potential energy landscape (PEL). The first ingredient is…
Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing…
The theoretical investigation of gas adsorption, storage, separation, diffusion and related transport processes in porous materials relies on a detailed knowledge of the potential energy surface of molecules in a stationary environment. In…
We apply Bayesian techniques to compare a simple, empirical model for jet-quenching in heavy-ion collisions to centrality-dependent jet-$R_{AA}$ measured by ATLAS for Pb+Pb collisions at $\sqrt{s_{NN}}=5.02$~TeV. We find that the $R_{AA}$…
Carbon monoxide is a simple molecule present in many astrophysical environments, and collisional excitation rate coefficients due to the dominant collision partners are necessary to accurately predict spectral line intensities and extract…
Motivated by environmental policy questions, we address the challenges of estimation, change point detection, and uncertainty quantification of a causal exposure-response function (CERF). Under a potential outcome framework, the CERF…
Gaussian processes are a powerful framework for uncertainty-aware function approximation and sequential decision-making. Unfortunately, their classical formulation does not scale gracefully to large amounts of data and modern hardware for…
Learning uncertain dynamics models using Gaussian process~(GP) regression has been demonstrated to enable high-performance and safety-aware control strategies for challenging real-world applications. Yet, for computational tractability,…
Six-dimensional quantum dynamical calculations of the scattering of H_2 from a Pd(100) surface using a potential energy surface derived from density-functional theory calculations are presented. Due to the corrugation and anisotropy of the…
Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…
Gaussian process regression (GPR) is a useful technique to predict composition--property relationships in glasses as the method inherently provides the standard deviation of the predictions. However, the technique remains restricted to…
Energy transfer through quantum coherences plays an essential role in diverse natural phenomena and technological applications, such as human vision, light-harvesting complexes, quantum heat engines, and quantum information and computing.…
We derive a quasiclassical expression for the density of states (DOS) of an arbitrary, ultracold, $N$-atom collision complex, for a general potential energy surface (PES). We establish the accuracy of our quasiclassical method by comparing…
A statistical-type model is developed to describe the ion production and electron emission in collisions of (molecular) ions with atoms. The model is based on the Boltzmann population of the bound electronic energy levels of the quasi…
The heavy quark collisional scattering on partons of the quark gluon plasma (QGP) is studied in a QCD medium at finite temperature and chemical potential. We evaluate the effects of finite parton masses and widths, finite temperature $T$…
The quality of data taken at RHIC and LHC as well as the success and sophistication of computational models for the description of ultra-relativistic heavy-ion collisions have advanced to a level that allows for the quantitative extraction…
Heavy-ion collisions provide a window into the properties of many-body systems of deconfined quarks and gluons. Understanding the collective properties of quarks and gluons is possible by comparing models of heavy-ion collisions to…
A theoretical scheme for the treatment of an open molecular system with electrons and nuclei is proposed. The idea is based on the Grand Canonical description of a quantum region embedded in a classical reservoir of molecules. Electronic…