From the 1 of 6 linked papers with an AI index.
6 papers
Excited state optimization for strongly correlated quantum defects using ensemble variational Monte Carlo
Kevin G. Kleiner, Lucas K. Wagner
The paper applies ensemble variational Monte Carlo to optimize excited‑state wavefunctions of strongly correlated point defects such as NV and SiV centers in diamond and Fe/Cr impu…
Particle-hole asymmetric phases in doped twisted bilayer graphene
Run Hou, Shouvik Sur, Lucas K. Wagner +1
Despite much theoretical work, developing a comprehensive ab initio model for twisted bilayer graphene (TBG) has proven challenging due to the inherent trade-off between accurately…
Expressivity of determinantal ansatzes for neural network wave functions
Ni Zhan, William A. Wheeler, Gil Goldshlager +3
Neural network wave functions have shown promise as a way to achieve high accuracy on the many-body quantum problem. These wave functions most commonly use a determinant or sum of…
Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water-methane dimer
Flaviano Della Pia, Benjamin X. Shi, Yasmine S. Al-Hamdani +30
Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely-trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and mol…
Graphene-hBN interlayer interactions from quantum Monte Carlo
Kittithat Krongchon, Tawfiqur Rakib, Daniel Palmer +3
The interaction between graphene and hexagonal boron nitride (hBN) plays a pivotal role in determining the electronic and structural properties of graphene-based devices. In this w…
Quantum Monte Carlo assessment of embedding for for strongly correlated defects: interplay between mean-field starting point and interactions
Kevin G. Kleiner, Sonali Joshi, Rohan Joshi +5
Point defects are of interest for many applications, from quantum sensing to modifying bulk properties of materials. Because of their localized orbitals, the electronic states are…