Work

Modern compressive tomography for quantum information science

Year: 2021

Type: article

Abstract: This review serves as a concise introductory survey of modern compressive tomography developed since 2019. These are schemes meant for characterizing arbitrary low-rank quantum objects, be it an unknown state, a process or detector, using minimal measuring resources (hence compressive) without any a priori assumptions (rank, sparsity, eigenbasis, etc.) about the quantum object. This paper contains a reasonable amount of technical details for the quantum-information community to start applying the methods discussed here. To facilitate the understanding of formulation logic and physics of compressive tomography, the theoretical concepts and important numerical results (both new and cross-referenced) shall be presented in a pedagogical manner.

Source: International Journal of Quantum Information

DOI: 10.1142/s0219749921400037

Authors: Yong Siah Teo, Luis L. Sánchez-Soto

Institutions: Seoul National University, Universidad Complutense de Madrid, Max Planck Institute for the Science of Light

Language: English

Topic: Quantum Information and Cryptography

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Research Foundation of Korea, Ministerio de Ciencia e Innovación, Horizon 2020

Awards: G2283859857, G4670007224, G586508345, G6333487577, G6789448499