Compressed sensing for Hamiltonian reconstruction

TL;DR

This paper introduces a compressed sensing approach for efficiently reconstructing sparse Hamiltonians in engineered quantum systems at moderate temperatures, reducing the need for extensive measurements.

Contribution

It adapts compressed sensing techniques to quantum Hamiltonian reconstruction, enabling accurate estimation with fewer measurements for sparse Hamiltonians.

Findings

Effective at temperatures above interaction energies

Requires Hamiltonian sparsity for success

Reduces measurement complexity in quantum systems

Abstract

In engineered quantum systems, the Hamiltonian is often not completely known and needs to be determined experimentally with accuracy and efficiency. We show that this may be done at temperatures that are greater than the characteristic interaction energies, but not too much greater. The condition for this is that there are not too many interactions: the Hamiltonian is sparse in a well-defined sense. The protocol that accomplishes this is related to compressed sensing methods of classical signal processing; in this case applied to sparse rather than low-rank matrices.