DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science
In this paper, the history, present status, and future of density-functional theory (DFT) is
informally reviewed and discussed by 70 workers in the field, including molecular scientists …
informally reviewed and discussed by 70 workers in the field, including molecular scientists …
Smooth, exact rotational symmetrization for deep learning on point clouds
Point clouds are versatile representations of 3D objects and have found widespread
application in science and engineering. Many successful deep-learning models have been …
application in science and engineering. Many successful deep-learning models have been …
Probing the effects of broken symmetries in machine learning
Symmetry is one of the most central concepts in physics, and it is no surprise that it has also
been widely adopted as an inductive bias for machine-learning models applied to the …
been widely adopted as an inductive bias for machine-learning models applied to the …
[PDF][PDF] DFTK: A Julian approach for simulating electrons in solids
Density-functional theory (DFT) is a widespread method for simulating the quantum-
chemical behaviour of electrons in matter. It provides a first-principles description of many …
chemical behaviour of electrons in matter. It provides a first-principles description of many …
[BOOK][B] Solving Nonlinear Equations with Iterative Methods: Solvers and Examples in Julia
CT Kelley - 2022 - SIAM
This book on solvers for nonlinear equations is a user-oriented guide to algorithms and
implementation. It is a sequel to [111], which used MATLAB for the solvers and examples …
implementation. It is a sequel to [111], which used MATLAB for the solvers and examples …
NQCDynamics. jl: A Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase
Accurate and efficient methods to simulate nonadiabatic and quantum nuclear effects in high-
dimensional and dissipative systems are crucial for the prediction of chemical dynamics in …
dimensional and dissipative systems are crucial for the prediction of chemical dynamics in …
Body-ordered approximations of atomic properties
We show that the local density of states (LDOS) of a wide class of tight-binding models has a
weak body-order expansion. Specifically, we prove that the resulting body-order expansion …
weak body-order expansion. Specifically, we prove that the resulting body-order expansion …
Predictive mixing for density functional theory (and other fixed-point problems)
LD Marks - Journal of Chemical Theory and Computation, 2021 - ACS Publications
Density functional theory calculations use a significant fraction of current supercomputing
time. The resources required scale with the problem size, the internal workings of the code …
time. The resources required scale with the problem size, the internal workings of the code …
A robust and efficient line search for self-consistent field iterations
We propose a novel adaptive dam** algorithm for the self-consistent field (SCF) iterations
of Kohn-Sham density-functional theory, using a backtracking line search to automatically …
of Kohn-Sham density-functional theory, using a backtracking line search to automatically …
Numerical methods for Kohn–Sham models: Discretization, algorithms, and error analysis
Numerical Methods for Kohn–Sham Models: Discretization, Algorithms, and Error Analysis |
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