3 papers
cond-mat.str-el2025
Leveraging recurrence in neural network wavefunctions for large-scale simulations of Heisenberg antiferromagnets on the triangular lattice
M. Schuyler Moss, Roeland Wiersema, Mohamed Hibat-Allah +2
Variational Monte Carlo simulations have been crucial for understanding quantum many-body systems, especially when the Hamiltonian is frustrated and the ground-state wavefunction h…
cond-mat.str-el2025
Leveraging recurrence in neural network wavefunctions for large-scale simulations of Heisenberg antiferromagnets on the square lattice
M. Schuyler Moss, Roeland Wiersema, Mohamed Hibat-Allah +2
Machine-learning-based variational Monte Carlo simulations are a promising approach for targeting quantum many-body ground states, especially in two dimensions and in cases where t…
quant-ph2024
RydbergGPT
David Fitzek, Yi Hong Teoh, Hin Pok Fung +5
We introduce a generative pretained transformer (GPT) designed to learn the measurement outcomes of a neutral atom array quantum computer. Based on a vanilla transformer, our encod…