Direct reconstruction of the quantum density matrix elements with classical shadow tomography
Yu Wang

TL;DR
This paper presents a new classical shadow tomography method, DMP-ST, for efficiently reconstructing multiple elements of a quantum state's density matrix with high accuracy, reducing sample complexity and measurement configurations.
Contribution
The authors introduce DMP-ST, a scalable, measurement-efficient framework for direct quantum state element estimation, outperforming traditional methods in sample complexity and measurement reduction.
Findings
Estimates K off-diagonal elements with (K/^2) samples
Achieves near-optimal sample complexity for full state tomography
Biased MUB measurements further reduce sample complexity
Abstract
We introduce a direct estimation framework for reconstructing multiple density matrix elements of an unknown quantum state using classical shadow tomography. Traditional direct measurement protocols (DMPs), while effective for individual elements, suffer from poor scalability due to post-selection losses and the need for element-specific measurement configurations. In contrast, our method, DMP-ST, leverages random Clifford or biased mutually unbiased basis measurements to enable global estimation: a single dataset suffices to estimate arbitrary off-diagonal entries with high accuracy. We prove that estimating \(K\) off-diagonal matrix elements up to additive error \(\epsilon\) requires only \(\mathcal{O}(\log K/\epsilon^2)\) samples, achieving exponential improvement over conventional DMPs. The number of required measurement configurations can also be exponentially reduced for large K.…
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Taxonomy
TopicsQuantum optics and atomic interactions · Advanced Optical Imaging Technologies · Cold Atom Physics and Bose-Einstein Condensates
