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Tomography by Design: An Algebraic Approach to Low-Rank Quantum States

Published 16 Feb 2026 in quant-ph, cs.AI, eess.SP, math.NA, and stat.CO | (2602.15202v1)

Abstract: We present an algebraic algorithm for quantum state tomography that leverages measurements of certain observables to estimate structured entries of the underlying density matrix. Under low-rank assumptions, the remaining entries can be obtained solely using standard numerical linear algebra operations. The proposed algebraic matrix completion framework applies to a broad class of generic, low-rank mixed quantum states and, compared with state-of-the-art methods, is computationally efficient while providing deterministic recovery guarantees.

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