%0 Journal Article
%A Teo, Yong Siah
%A Struchalin, G. I.
%A Kovlakov, E. V.
%A Ahn, Daekun
%A Jeong, Hyunseok
%A Straupe, S. S.
%A Kulik, S. P.
%A Leuchs, Gerd
%A Sánchez Soto, Luis Lorenzo
%T Objective compressive quantum process tomography
%D 2020
%@ 2469-9926
%U https://hdl.handle.net/20.500.14352/6114
%X We present a compressive quantum process tomography scheme that fully characterizes any rank-deficient completely positive process with no spurious a priori information. It uses randomly chosen input states and adaptive output von Neumann measurements. Both entangled and tensor-product configurations are flexibly employable in our scheme, the latter of which are especially compatible with many-body quantum computing. Two main features of this scheme are the certification protocol that verifies whether the accumulated data uniquely characterize the quantum process and a compressive reconstruction method for the output states. We emulate multipartite scenarios with high-order transverse modes and optical fibers to demonstrate that, in terms of measurement resources, our assumption-free compressive strategy can reconstruct quantum processes almost equally efficiently using all types of input states and basis measurements.
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