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Measurements of Quantum Hamiltonians with Locally-Biased Classical Shadows
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Obtaining precise estimates of quantum observables is a crucial step of variational quantum algorithms. We consider the problem of estimating expectation values of molecular Hamiltonians, obtained on states prepared on a quantum computer. We propose a novel estimator for this task, which is locally optimised with knowledge of the Hamiltonian and a classical approximation to the underlying quantum state. Our estimator is based on the concept of classical shadows of a quantum state, and has the important property of not adding to the circuit depth for the state preparation. We test its performance numerically for molecular Hamiltonians of increasing size, finding a sizable reduction in variance with respect to current measurement protocols that do not increase circuit depths.
Forward citations
Cited by 2 Pith papers
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Improved Classical Shadow Tomography Using Quantum Computation
A quantum-to-classical-to-quantum protocol prepares states from classical shadows and measures observables directly, achieving exponential space savings for Clifford shadows and faster post-processing.
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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information
An adaptive estimator based on empirical Bernstein stopping reduces the number of measurements needed to estimate ground-state energies with rigorous error bounds, by up to an order of magnitude in numerical benchmarks.
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