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Updated: Feb 25, 2026

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Visualizing dispersive features in 2D image via minimum gradient method.

Yu He1, Yan Wang2, Zhi-Xun Shen1

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Summary
This summary is machine-generated.

We introduce a new minimum gradient method for analyzing momentum resolved spectroscopy data. This technique enhances feature detection in 2D plots, offering improved noise resilience and contrast for scientific analysis.

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Area of Science:

  • Condensed Matter Physics
  • Materials Science
  • Spectroscopy

Background:

  • Momentum resolved spectroscopy experiments generate 2D image plots crucial for data analysis.
  • Existing methods like distribution curve (DC) and higher order derivative analyses have limitations in noise resilience and feature detection.

Purpose of the Study:

  • To develop a novel minimum gradient based method for tracking ridge features in 2D image plots.
  • To compare the performance of the new method against existing techniques.
  • To demonstrate the quantitative application of the method in analyzing experimental data.

Main Methods:

  • Development of a minimum gradient based algorithm for ridge feature tracking.
  • Analytic formulation and numerical simulations for method validation.
  • Comparison with distribution curve (DC) based and higher order derivative based analyses.
  • Proposal of an algorithm to extract 1D ridge dispersion from 2D plots.

Main Results:

  • The new minimum gradient method exhibits superior noise resilience and enhanced contrast, particularly for weak intensity features.
  • The method preserves quantitative local maxima information from raw experimental data.
  • Successful quantitative application to angle-resolved photoemission spectroscopy (ARPES) measurements on high-temperature superconductors.

Conclusions:

  • The minimum gradient based method offers a robust and effective approach for analyzing momentum resolved spectroscopy data.
  • This technique improves the ability to detect and quantify subtle features in complex datasets.
  • The method has significant potential for advancing the study of materials like high-temperature superconductors.