Projects

Learning Quantum Wavefunctions with RNNs

Extending recent work pioneered at PiQuIL in approximating the groundstate wavefunction of a quantum lattice system using Recurrent Neural Networks: Investigated the affect of error and noisiness of the quantum data on the accuracy of the wavefunction and other physical quantities.

Supervisors: Professor Roger Melko, Schuyler Moss.

Learning Quantum Wavefunctions with RNNs