A precise method for visualizing dispersive features in image plots

TL;DR

This paper introduces a new curvature-based analysis method that enhances the visualization and localization of extrema in image plots, outperforming the traditional second derivative approach in accuracy and peak sharpness.

Contribution

A novel curvature-based technique for analyzing and visualizing dispersive features in image plots, improving extrema localization over existing second derivative methods.

Findings

Enhanced extrema localization in simulated data

Reduced peak broadness in experimental data

Better visualization of dispersive features

Abstract

In order to improve the advantages and the reliability of the second derivative method in tracking the position of extrema from experimental curves, we develop a novel analysis method based on the mathematical concept of curvature. We derive the formulas for the curvature in one and two dimensions and demonstrate their applicability to simulated and experimental angle-resolved photoemission spectroscopy data. As compared to the second derivative, our new method improves the localization of the extrema and reduces the peak broadness for a better visualization on intensity image plots.