Accurately solving the Schrödinger equation for intricate systems remains a prominent challenge in physical sciences. Here we present QiankunNet, a neural network quantum state (NNQS) framework that ...
Neural-network-based variational quantum states, particularly autoregressive models, are powerful tools for describing complex many-body wave functions. However, their performance depends on the ...
This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...