  Magnetic molecules, modelled as finite-size spin systems, are test-beds for
quantum phenomena and could constitute key elements in future spintronics
devices, long-lasting nanoscale memories or noise-resilient quantum computing
platforms. Inelastic neutron scattering is the technique of choice to probe
them, characterizing molecular eigenstates on atomic scales. However, although
large magnetic molecules can be controllably synthesized, simulating their
dynamics and interpreting spectroscopic measurements is challenging because of
the exponential scaling of the required resources on a classical computer.
Here, we show that quantum computers have the potential to efficiently extract
dynamical correlations and the associated magnetic neutron cross-section by
simulating prototypical spin systems on a quantum hardware. We identify the
main gate errors and show the potential scalability of our approach. The
synergy between developments in neutron scattering and quantum processors will
help design spin clusters for future applications.
