Abstract

We establish methods for quantum state tomography based on compressed sensing. These methods are specialized for quantum states that are fairly pure, and they offer a significant performance improvement on large quantum systems. In particular, they are able to reconstruct an unknown density matrix of dimension d and rank r using O(rdlog²d) measurement settings, compared to standard methods that require d² settings. Our methods have several features that make them amenable to experimental implementation: they require only simple Pauli measurements, use fast convex optimization, are stable against noise, and can be applied to states that are only approximately low rank. The acquired data can be used to certify that the state is indeed close to pure, so no a priori assumptions are needed.

Keywords

Quantum tomographyQuantum statePauli exclusion principleQuantumCompressed sensingComputer scienceTomographyDimension (graph theory)A priori and a posterioriRank (graph theory)POVMDensity matrixStatistical physicsState (computer science)AlgorithmQuantum operationPhysicsQuantum mechanicsMathematicsOpen quantum systemOpticsPure mathematics

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Publication Info

Year
2010
Type
article
Volume
105
Issue
15
Pages
150401-150401
Citations
1071
Access
Closed

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Cite This

David Groß, Yi-Kai Liu, Steven T. Flammia et al. (2010). Quantum State Tomography via Compressed Sensing. Physical Review Letters , 105 (15) , 150401-150401. https://doi.org/10.1103/physrevlett.105.150401

Identifiers

DOI
10.1103/physrevlett.105.150401