Flow-based Sampling for Entanglement Entropy and the Machine Learning of Defects

no code implementations • 18 Oct 2024 • Andrea Bulgarelli, Elia Cellini, Karl Jansen, Stefan Kühn, Alessandro Nada, Shinichi Nakajima, Kim A. Nicoli, Marco Panero

We introduce a novel technique to numerically calculate R\'enyi entanglement entropies in lattice quantum field theory using generative models.

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

1 code implementation • NeurIPS 2023 • Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima

In this paper, we propose a novel and powerful method to harness Bayesian optimization for Variational Quantum Eigensolvers (VQEs) -- a hybrid quantum-classical protocol used to approximate the ground state of a quantum Hamiltonian.

Bayesian Optimization Inductive Bias