4.8 Article

Experimental Investigation of Spectra of Dynamical Maps and their Relation to non-Markovianity

Journal

PHYSICAL REVIEW LETTERS
Volume 120, Issue 6, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevLett.120.060406

Keywords

-

Funding

  1. National Key Research and Development Program of China [2017YFA0304100, 2016YFA0302700]
  2. National Natural Science Foundation of China [11674304, 61327901, 61490711, 11474267, 11325419, 91321313]
  3. Youth Innovation Promotion Association of Chinese Academy of Sciences [2017492]
  4. Foundation for Scientific Instrument and Equipment Development of Chinese Academy of Sciences [YJKYYQ20170032]
  5. Key Research Program of Frontier Sciences of the Chinese Academy of Sciences [QYZDY-SSW-SLH003]
  6. Fundamental Research Funds for the Central Universities [WK2470000026]
  7. EU Collaborative project QuProCS [641277]

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The spectral theorem of von Neumann has been widely applied in various areas, such as the characteristic spectral lines of atoms. It has been recently proposed that dynamical evolution also possesses spectral lines. As the most intrinsic property of evolution, the behavior of these spectra can, in principle, exhibit almost every feature of this evolution, among which the most attractive topic is non-Markovianity, i.e., the memory effects during evolution. Here, we develop a method to detect these spectra, and moreover, we experimentally examine the relation between the spectral behavior and non-Markovianity by engineering the environment to prepare dynamical maps with different non-Markovian properties and then detecting the dynamical behavior of the spectral values. These spectra will lead to a witness for essential non-Markovianity. We also experimentally verify another simplified witness method for essential non-Markovianity. Interestingly, in both cases, we observe the sudden transition from essential non-Markovianity to something else. Our work shows the role of the spectra of evolution in the studies of non-Makovianity and provides the alternative methods to characterize non-Markovian behavior.

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