Determination of the current density distribution in Josephson junctions

M. Carmody; E. Landree; L. D. Marks; K. L. Merkle

doi:10.1016/S0921-4534(99)00189-6

Determination of the current density distribution in Josephson junctions

M. Carmody^*, E. Landree, L. D. Marks, K. L. Merkle

^*Corresponding author for this work

Materials Science and Engineering

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

By using a phase retrieval algorithm similar to the Gerchberg-Saxton error-reduction algorithm with a generalized projection onto sets form, it is possible to restore the phase information that is not measured when experimentally recording I_c(B) data for Josephson junctions without making any assumptions about the current density distribution j(x). In general, it is not possible to find a unique solution for the 1-D phase problem; however, it is possible with the assistance of the genetic algorithm to efficiently find all possible solutions. If multiple solutions exist for a junction, the set of all possible solutions can be compared against the boundary microstructure and the correct solution can be determined.

Original language	English (US)
Pages (from-to)	145-153
Number of pages	9
Journal	Physica C: Superconductivity and its applications
Volume	315
Issue number	3
DOIs	https://doi.org/10.1016/S0921-4534(99)00189-6
State	Published - Apr 20 1999

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Energy Engineering and Power Technology
Electrical and Electronic Engineering

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AU - Landree, E.

AU - Marks, L. D.

AU - Merkle, K. L.

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AB - By using a phase retrieval algorithm similar to the Gerchberg-Saxton error-reduction algorithm with a generalized projection onto sets form, it is possible to restore the phase information that is not measured when experimentally recording Ic(B) data for Josephson junctions without making any assumptions about the current density distribution j(x). In general, it is not possible to find a unique solution for the 1-D phase problem; however, it is possible with the assistance of the genetic algorithm to efficiently find all possible solutions. If multiple solutions exist for a junction, the set of all possible solutions can be compared against the boundary microstructure and the correct solution can be determined.

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