Literature DB >> 32735539

Reconstructing Quantum States With Quantum Reservoir Networks.

Sanjib Ghosh, Andrzej Opala, Michal Matuszewski, Tomasz Paterek, Timothy C H Liew.   

Abstract

Reconstructing quantum states is an important task for various emerging quantum technologies. The process of reconstructing the density matrix of a quantum state is known as quantum state tomography. Conventionally, tomography of arbitrary quantum states is challenging as the paradigm of efficient protocols has remained in applying specific techniques for different types of quantum states. Here, we introduce a quantum state tomography platform based on the framework of reservoir computing. It forms a quantum neural network and operates as a comprehensive device for reconstructing an arbitrary quantum state (finite-dimensional or continuous variable). This is achieved with only measuring the average occupation numbers in a single physical setup, without the need of any knowledge of optimum measurement basis or correlation measurements.

Year:  2021        PMID: 32735539     DOI: 10.1109/TNNLS.2020.3009716

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw Learn Syst        ISSN: 2162-237X            Impact factor:   10.451


  1 in total

1.  Natural quantum reservoir computing for temporal information processing.

Authors:  Yudai Suzuki; Qi Gao; Ken C Pradel; Kenji Yasuoka; Naoki Yamamoto
Journal:  Sci Rep       Date:  2022-01-25       Impact factor: 4.379

  1 in total

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