kMap.py: A Python program for simulation and data analysis in photoemission tomography

TL;DR

kMap.py is a Python software tool that simulates and compares photoemission momentum maps of molecular orbitals, aiding the analysis of organic/metal interfaces in photoemission tomography experiments.

Contribution

It introduces a user-friendly Python program with GUI for simulating and analyzing photoemission momentum maps based on density functional calculations.

Findings

Enables direct comparison between simulated and experimental data

Allows variation of parameters like molecular orientation and light polarization

Facilitates automatic optimization of molecular structural parameters

Abstract

For organic molecules adsorbed as well-oriented ultra-thin films on metallic surfaces, angle-resolved photoemission spectroscopy has evolved into a technique called photoemission tomography (PT). By approximating the final state of the photoemitted electron as a free electron, PT uses the angular dependence of the photocurrent, a so-called momentum map or k-map, and interprets it as the Fourier transform of the initial state's molecular orbital, thereby gains insights into the geometric and electronic structure of organic/metal interfaces. In this contribution, we present kMap.py which is a Python program that enables the user, via a PyQt-based graphical user interface, to simulate photoemission momentum maps of molecular orbitals and to perform a one-to-one comparison between simulation and experiment. Based on the plane wave approximation for the final state, simulated momentum maps are computed numerically from a fast Fourier transform of real space molecular orbital distributions, which are used as program input and taken from density functional calculations. The program allows the user to vary a number of simulation parameters such as the final state kinetic energy, the molecular orientation or the polarization state of the incident light field. Moreover, also experimental photoemission data can be loaded into the program enabling a direct visual comparison as well as an automatic optimization procedure to determine structural parameters of the molecules or weights of molecular orbitals contributions. With an increasing number of experimental groups employing photoemission tomography to study adsorbate layers, we expect kMap.py to serve as an ideal analysis software to further extend the applicability of PT.