Fig. 1: Overview of the proposed machine learning algorithm.
From: Improved machine learning algorithm for predicting ground state properties
Given a vector x ∈ [−1, 1]m that parameterizes a quantum many-body Hamiltonian H(x), the algorithm uses a geometric structure to create a high-dimensional vector \(\phi (x)\in {{\mathbb{R}}}^{{m}_{\phi }}\). The ML algorithm then predicts properties or a representation of the ground state ρ(x) of Hamiltonian H(x) using the mϕ-dimensional vector ϕ(x).
