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Real space iterative reconstruction for vector tomography (RESIRE-V).

Minh Pham1,2,3, Xingyuan Lu4,5, Arjun Rana4

  • 1Department of Physics and Astronomy and California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA. minhrose@ucla.edu.

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|April 25, 2024
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Summary
This summary is machine-generated.

A new vector tomography method, RESIRE-V, reconstructs 3D vector fields like magnetic fields. This iterative algorithm accurately reconstructs simulated and real-world data, revealing magnetic defects.

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Area of Science:

  • Physical Sciences
  • Biological Sciences
  • Medical Sciences

Background:

  • Tomography is vital across scientific disciplines, primarily for 3D scalar reconstructions.
  • Vector tomography is essential for reconstructing 3D vector fields (e.g., electric, magnetic) in critical applications.

Purpose of the Study:

  • Introduce and validate REal Space Iterative REconstruction for Vector tomography (RESIRE-V).
  • Provide a robust method for 3D vector field reconstruction using multiple projection tilt series.

Main Methods:

  • RESIRE-V employs an iterative approach with forward/backward steps using the Radon transform and its transpose.
  • Gradient descent updates the object, incorporating a 3D support constraint to minimize projection error.
  • The algorithm refines tilt angles for improved 3D reconstruction accuracy.

Main Results:

  • Validated on simulated 3D magnetization vector fields, RESIRE-V accurately reconstructed all components.
  • Applied to a ferromagnetic meta-lattice, RESIRE-V revealed topological magnetic defects with positive and negative charges.
  • Quantitative analysis confirmed high agreement between reconstructed and ground-truth vector fields.

Conclusions:

  • RESIRE-V offers a powerful and accessible tool for 3D vector tomography.
  • The method is adaptable for various imaging modalities and vector field types.
  • Open-source code and data are available, promoting broader scientific use.