Informationally Incomplete Quantum Tomography

Abstract

In quantum-state tomography on sources with quantum degrees of freedom of large Hilbert spaces, inference of quantum states of light for instance, a complete characterization of the quantum states for these sources is often not feasible owing to limited resources. As such, the concepts of informationally incomplete state estimation becomes important. These concepts are ideal for applications to quantum channel/process tomography, which typically requires a much larger number of measurement settings for a full characterization of a quantum channel. Some key aspects of both quantum-state and quantum-process tomography are arranged together in the form of a tutorial review article that is catered to students and researchers who are new to the field of quantum tomography, with focus on maximum-likelihood related techniques as instructive examples to illustrate these ideas.

23 pages, 5 figures

References in corpus (1)

• Optimal error regions for quantum state estimation

Cited by in corpus (8)

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• Adaptive quantum tomography
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• Error suppression in multicomponent cat codes with photon subtraction and teleamplification
• Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
• Direct measurement of large-scale quantum states
• Benchmarking Single-Qubit Gates on a Neutral Atom Quantum Processor