JOURNAL ARTICLE

Passive Quantum Measurement: Arrival Time, Quantum Zeno Effect and Gambler's Fallacy.

  • Published In: Fortschritte der Physik / Progress of Physics, 2023, v. 71, n. 10/11. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jurić, Tajron; Nikolić, Hrvoje 3 of 3

Abstract

Classical measurements are passive, in the sense that they do not affect the physical properties of the measured system. Normally, quantum measurements are not passive in that sense. In the infinite dimensional Hilbert space, however, it is found that quantum projective measurement can be passive in a way which is impossible in finite dimensional Hilbert spaces. Specifically, it is found that expectation value of a hermitian Hamiltonian can have an imaginary part in the infinite dimensional Hilbert space and that such an imaginary part implies a possibility to avoid quantum Zeno effect, which can physically be realized in quantum arrival experiments. The avoidance of quantum Zeno effect can also be understood as avoidance of a quantum version of gambler's fallacy, leading to the notion of passive quantum measurement that updates information about the physical system without affecting its physical properties. The arrival time probability distribution of a particle is found to be given by the flux of the probability current. Possible negative fluxes correspond to regimes at which there is no arrival at all, physically understood as regimes at which the particle departs rather than arrives. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Fortschritte der Physik / Progress of Physics. 2023/11, Vol. 71, Issue 10/11, p1
  • Document Type:Article
  • Subject Area:Sports and Leisure
  • Publication Date:2023
  • ISSN:0015-8208
  • DOI:10.1002/prop.202300014
  • Accession Number:173456019
  • Copyright Statement:Copyright of Fortschritte der Physik / Progress of Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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