Year: 2020
Type: article
Abstract: 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.
Source: Physical Review A
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funders: National Research Foundation, Russian Foundation for Basic Research, Ministry of Education, Ministry of Education and Science of the Russian Federation, Ministry of Science, ICT and Future Planning, National Research Foundation of Korea, Ministry of Education, India, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España
OpenAlex ID: W2989320269