AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (425.6 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

The Pauli problem and wave function lifting: reconstruction of quantum states from physical observables

Chinese Academy of Science, No. 55, Zhongguancun Est. Rd., Haidian District, Beijing 100190, China
Show Author Information

Abstract

In this paper we consider the problem to determine a unique quantum state from given distribution of position (density) and momentum density of particles, namely the so called Pauli problem in quantum physics. In the first part, we will review the method of wave function lifting developed in [4,5] to construct a complex wave function ψHs(Rd), s=1,2, associated to given density and momentum density. The second part is focused on the dynamical version of the wave function lifting, namely we study the relation between solutions to quantum fluid models and wave functions solving the nonlinear Schrödinger equation. The uniqueness of the lifted wave function is essentially related to the structure of vacuum regions of the position density.

References

【1】
【1】
 
 
Mathematics in Engineering
Pages 648-675

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Zheng H. The Pauli problem and wave function lifting: reconstruction of quantum states from physical observables. Mathematics in Engineering, 2024, 6(4): 648-675. https://doi.org/10.3934/mine.2024025

194

Views

1

Downloads

1

Crossref

1

Web of Science

1

Scopus

Received: 24 January 2024
Revised: 11 August 2024
Accepted: 26 August 2024
Published: 15 August 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)