QAOA plus quantum subspace expansion systematically improves MIS solutions on small random graphs, with a fitted gate-count crossover extrapolated to about 75 nodes.
Quantum algorithms for generator coordinate methods
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abstract
This paper discusses quantum algorithms for the generator coordinate method (GCM) that can be used to benchmark molecular systems. The GCM formalism defined by exponential operators with exponents defined through generators of the Fermionic U(N) Lie algebra (Thouless theorem) offers a possibility of probing large sub-spaces using low-depth quantum circuits. In the present studies, we illustrate the performance of the quantum algorithm for constructing a discretized form of the Hill-Wheeler equation for ground and excited state energies. We also generalize the standard GCM formulation to multi-product extension that when collective paths are properly probed, can systematically introduce higher rank effects and provide elementary mechanisms for symmetry purification when generator states break the spatial or spin symmetries. The GCM quantum algorithms also can be viewed as an alternative to existing variational quantum eigensolvers, where multi-step classical optimization algorithms are replaced by a single-step procedure for solving the Hill-Wheeler eigenvalue problem.
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Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion
QAOA plus quantum subspace expansion systematically improves MIS solutions on small random graphs, with a fitted gate-count crossover extrapolated to about 75 nodes.