The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

This Perspective focuses on the several overlaps between quantum algorithms and Monte
Carlo methods in the domains of physics and chemistry. We will analyze the challenges and …

The famous, yet unsolved, Fermi-Hubbard model for strongly-correlated electronic systems
is a prominent target for quantum computers. However, accurately representing the Fermi …

Establishing the nature of the ground state of the Heisenberg antiferromagnet (HAFM) on the
kagome lattice is well-known to be a prohibitively difficult problem for classical computers …

Variational algorithms require architectures that naturally constrain the optimisation space to
run efficiently. In geometric quantum machine learning, one achieves this by encoding group …

Quantum state preparation is a key step in all digital quantum simulation algorithms. Here
we propose methods to initialize on a gate-based quantum computer a general class of …

Volume 54 of the Advances in Atomic, Molecular, and Optical Physics Series contains ten
contributions, covering a diversity of subject areas in atomic, molecular and optical physics …

We propose a quantum protocol that allows preparing a ground state (GS) of the honeycomb
Kitaev model. Our approach efficiently uses underlying symmetries and techniques from …

We study the electronic orders at the lower van Hove filling in the kagome lattice. In the weak
limit of the Hubbard interaction U versus the hopping parameter t, we find that the system …

The ground state properties of the two-dimensional J 1-J 2-model are very challenging to
analyze via classical numerical methods due to the high level of frustration. This makes the …