AI RESEARCH
Tomography by Design: An Algebraic Approach to Low-Rank Quantum States
arXiv CS.AI
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ArXi:2602.15202v2 Announce Type: replace-cross 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.