Density functional theory offers a very accurate way of computing materials properties from
first principles. However, it is too expensive for modeling large-scale molecular systems …

The ability in experiments to control the relative twist angle between successive layers in two-
dimensional (2D) materials offers an approach to manipulating their electronic properties; …

Abstract The Atomic Cluster Expansion (Drautz (2019)[21]) provides a framework to
systematically derive polynomial basis functions for approximating isometry and permutation …

Abstract Machine-learned interatomic potentials (MLIPs) are typically trained on datasets
that encompass a restricted subset of possible input structures, which presents a potential …

Abstract Machine learning interatomic potentials (MLIPs) provide exceptional opportunities
to accurately simulate atomistic systems and/or accelerate the evaluation of diverse physical …

Machine-learned interatomic potentials (MLIPs) and force fields (ie, interaction laws for
atoms and molecules) are typically trained on limited data-sets that cover only a very small …

We prove that the electronic density of states (DOS) for two-dimensional incommensurate
layered structures, where Bloch theory does not apply, is well-defined as the thermodynamic …

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 …

We study the polynomial approximation of symmetric multivariate functions and of multi-set
functions. Specifically, we consider $ f (x_1,\dots, x_N) $, where $ x_i\in\mathbb {R}^ d …

To make the investigation of electronic structure of incommensurate heterostructures
computationally tractable, effective alternatives to Bloch theory must be developed. In …