High-dimensional methods for quantum homodyne tomography

被引：1
|
作者：
Mosco, Nicola
Maccone, Lorenzo [1 ]
机构：
[1] Univ Pavia, Dip Fis, Via Bassi 6, I-27100 Pavia, Italy
来源：
PHYSICS LETTERS A | 2022年 / 449卷
关键词：
Quantum tomography; Homodyne detection; Pattern functions; Julia language; DENSITY-MATRIX; PHOTON STATISTICS; WIGNER FUNCTION; RECONSTRUCTION; JULIA;
D O I：
10.1016/j.physleta.2022.128339
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
We provide optimized recursion relations for homodyne tomography. We improve previous methods by mitigating the divergences intrinsic in the calculation of the pattern functions used previously, and detail how to implement the data analysis through Monte Carlo simulations. Our refinements are necessary for the reconstruction of excited quantum states which populate a high-dimensional subspace of the electromagnetic field Hilbert space. (C) 2022 Elsevier B.V. All rights reserved.
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页数：8
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