Computational Physics
A neural network is used to train, predict, and evaluate a model to calculate the energies of 3-dimensional systems composed of Ti and O atoms. Python classes are implemented to quantify atomic interactions through symmetry functions and to…
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations,…
The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals. However, creating interatomic potentials for magnetic systems that account for both magnetic…
Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel model reduction methods, coupled with detection of abnormal modes with plasma…
The paper by No\'e et al. [F. No\'e, S. Olsson, J. K\"ohler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can produce unbiased independent samples of many-body…
Whether for shielding applications or for criticality safety studies, solving the neutron transport equation with good accuracy requires to take into account the resonant structure of cross sections in part of the Unresolved Resonance…
The Glansdorff and Prigogine General Evolution Criterion (GEC) is an inequality that holds for macroscopic physical systems obeying local equilibrium and that are constrained under timeindependent boundary conditions. The latter, however,…
We suggest new modification (we call it a noise reduction procedure) for Steinhardt parameters which are often used for detecting crystalline structures in computer simulation of solids and soft matter systems. We have also developed a new…
We explore the application of an extrapolative method that yields very accurate total and relative energies from variational and diffusion quantum Monte Carlo (VMC and DMC) results. For a trial wave function consisting of a small…
Sub-1-nm gate length $MoS_2$ transistors have been experimentally fabricated, but their device performance limit remains elusive. Herein, we explore the performance limits of the sub-1-nm gate length monolayer (ML) $MoS_2$ transistors…
Following the recent demonstration of grazing-incidence X-ray fluorescence (GIXRF) based characterization of the 3D atomic distribution of different elements and dimensional parameters of periodic nanoscale structures, this work presents a…
The system has addressed the error of "Bad character(s) in field Abstract" for no reason. Please refer to manuscript for the full abstract.
Recently, the increasing use of deep reinforcement learning for flow control problems has led to a new area of research, focused on the coupling and the adaptation of the existing algorithms to the control of numerical fluid dynamics…
Probabilistic models in physics often require from the evaluation of normalized Boltzmann factors, which in turn implies the computation of the partition function Z. Getting the exact value of Z, though, becomes a forbiddingly expensive…
We present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and manipulates atomic positions with high…
Purpose: To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen…
This work studies the performance of a novel preconditioner, designed for thermal reservoir simulation cases and recently introduced in Roy et al. (2020) and Cremon et al. (2020), on large-scale thermal CO2 injection cases. For Carbon…
Numerical simulation of multi-phase fluid dynamics in porous media is critical for many energy and environmental applications in Earth's subsurface. Data-driven surrogate modeling provides computationally inexpensive alternatives to…
The structural, dielectric, and thermodynamic properties of the hydrogen-bonded ferroelectric crystal potassium dihydrogen phosphate ($\mathbf{KH_2PO_4}$), KDP for short, differ significantly from those of DKDP ($\mathbf{KD_2PO_4}$). It is…
In the referred paper("H. Karani, C. Huber, Physical Review E, 91(2)(2015) 023304"), a total heat flux continuity condition for conjugate heat transfer problems with moving interfaces was proposed. The authors asserted both conductive and…