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Researchers have reduced the shot count scaling for nonorthogonal quantum eigensolvers from cubic to linear by filtering out low-overlap reference states that drive computational error. This advancement directly addresses a primary bottleneck in variational algorithms, making near-term simulations of larger molecular systems significantly more feasible on noisy hardware.

Source coveringQuantum Zeitgeist

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Researchers Bound Quantum Eigensolver Shots to Linear Scaling

Quantum ZeitgeistAugust 17, 20265 min read

The per-matrix-element shot count needed for accurate molecular simulations has fallen from a scaling of O(M³) to O(M). This reduction, achieved with a new thresholding scheme within the nonorthogonal quantum eigensolver, promises to bring near-term quantum simulations of materials and drugs closer to reality. Controlling eigenvalue sensitivity via the overlap matrix condition number unlocks this improved efficiency.

Scientists are developing quantum subspace diagonalization methods as promising algorithms for quantum chemistry on near-term quantum computers. These methods can estimate low-lying energies of molecular systems using shallow quantum circuits. This estimation requires many circuit repetitions to determine the projection. A significant reduction in the per-matrix-element shot count needed for accurate quantum calculations has been achieved, improving the scaling from O(M³) to O(M), where M represents the number of reference states. This represents an advancement in the field of quantum computational chemistry, as the computational cost associated with determining molecular energies has historically been a major impediment to simulating larger systems. The…

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