Solving an Industrially Relevant Quantum Chemistry Problem on Quantum Hardware
Quantum chemical calculations are among the most promising applications for quantum computing. Implementations of dedicated quantum algorithms on available quantum hardware were so far, however, mostly limited to comparatively simple systems without strong correlations. As such, they can also be add...
Saved in:
Main Authors | , , , , , , , , , , , , |
---|---|
Format | Journal Article |
Language | English |
Published |
20.08.2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Quantum chemical calculations are among the most promising applications for
quantum computing. Implementations of dedicated quantum algorithms on available
quantum hardware were so far, however, mostly limited to comparatively simple
systems without strong correlations. As such, they can also be addressed by
classically efficient single-reference methods. In this work, we calculate the
lowest energy eigenvalue of active space Hamiltonians of industrially relevant
and strongly correlated metal chelates on trapped ion quantum hardware, and
integrate the results into a typical industrial quantum chemical workflow to
arrive at chemically meaningful properties. We are able to achieve chemical
accuracy by training a variational quantum algorithm on quantum hardware,
followed by a classical diagonalization in the subspace of states measured as
outputs of the quantum circuit. This approach is particularly
measurement-efficient, requiring 600 single-shot measurements per cost function
evaluation on a ten qubit system, and allows for efficient post-processing to
handle erroneous runs. |
---|---|
DOI: | 10.48550/arxiv.2408.10801 |