Measurement optimization techniques for excited electronic states in near-term quantum computing algorithms
Seonghoon Choi, Artur F. Izmaylov

TL;DR
This paper evaluates and compares various measurement optimization techniques for excited state VQE algorithms in quantum computing, demonstrating that tailored methods can significantly reduce measurement requirements.
Contribution
It adapts and assesses measurement techniques for excited state VQE algorithms, providing guidance on their effectiveness and measurement efficiency improvements.
Findings
Hamiltonian and wavefunction data-based methods excel in multi-state contraction.
Randomized measurements are more suitable for quantum subspace expansion.
Multi-state contraction requires fewer measurements than quantum subspace expansion.
Abstract
The variational quantum eigensolver (VQE) remains one of the most popular near-term quantum algorithms for solving the electronic structure problem. Yet, for its practicality, the main challenge to overcome is improving the quantum measurement efficiency. Numerous quantum measurement techniques have been developed recently, but it is unclear how these state-of-the-art measurement techniques will perform in extensions of VQE for obtaining excited electronic states. Assessing the measurement techniques' performance in the excited state VQE is crucial because the measurement requirements in these extensions are typically much greater than in conventional VQE, as one must measure the expectation value of multiple observables in addition to that of the electronic Hamiltonian. Here, we adapt various measurement techniques to two widely used excited state VQE algorithms: multi-state…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Neural Networks and Reservoir Computing
