Algorithms and image formation in orbital tomography

Abstract

Orbital tomography has recently been established as a technique to reconstruct molecular orbitals directly from photoemission data using iterative phase retrieval algorithms. In this work, we present a detailed description of steps for processing of the photoemission data followed by an improved iterative phase retrieval procedure and the interpretation of reconstructed two-dimensional orbital distributions. We address the issue of background subtraction by suggesting a signal restoration routine based on the maximization of mutual information algorithm and solve the problem of finding the geometrical center in the reconstruction by using a tight-centered object support in a two-step phase retrieval procedure. The proposed image processing and improved phase retrieval procedures are used to reconstruct the highest occupied molecular orbital of pentacene on Ag(110), using photoemission data only. The results of the reconstruction agree well with the density functional theory simulation, modified to comply with the experimental conditions. By comparison with photoelectron holography, we show that the reconstructed two-dimensional orbital distribution can be interpreted as a superposition of the in-focus orbital distribution evaluated at the z = 0 plane and out-of-focus distributions evaluated at other z = const planes. Three-dimensional molecular orbital distributions could thus be reconstructed directly from two-dimensional photoemission data, provided the axial resolution of the imaging system is high enough.

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• A minimalist approach to 3D photoemission orbital tomography: algorithms and data requirements
• kMap.py: A Python program for simulation and data analysis in photoemission tomography
• Photoemission orbital tomography based on tight-binding approach: method and application to $\pi$-conjugated molecules