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Simple MATLAB and Python scripts for multi-exponential analysis.

Armin Afrough1,2, Rasoul Mokhtari1, Karen L Feilberg1

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Summary
This summary is machine-generated.

This study presents simple MATLAB and Python code for analyzing multi-exponential decay, crucial in magnetic resonance applications. The software efficiently transforms decay data into lifetime distributions, aiding complex fluid and porous material analysis.

Keywords:
1HNMRexponential decayinverse problemsmagnetic resonance relaxationmulti‐exponential analysis

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Area of Science:

  • Physics
  • Chemistry
  • Data Science

Background:

  • Multi-exponential decay is a common phenomenon in magnetic resonance (MR) spectroscopy, relaxation, and imaging.
  • Analyzing such complex decay patterns is essential for understanding various physical systems.

Purpose of the Study:

  • To develop and present simple, efficient MATLAB and Python functions for regularized multi-exponential analysis.
  • To provide robust tools for transforming exponential decay data into distributions of decay lifetimes.

Main Methods:

  • Implementation of regularized least-squares solutions for 1D and 2D data inversion.
  • Development of concise code (~5 lines for 1D, ~20 lines for 2D) with robust stopping rules.
  • Application of the methods to real-world examples including crude oil and porous material fluid mixtures.

Main Results:

  • Production-quality outputs for multi-exponential analysis using minimal code.
  • Successful transformation of complex decay data into meaningful lifetime distributions.
  • Demonstration of the software's utility in analyzing magnetic resonance relaxation of diverse samples.

Conclusions:

  • The developed software offers a simple, open-architecture solution for multi-exponential analysis.
  • The code is readily usable or incorporable into other research software for magnetic resonance and other fields.
  • This work facilitates deeper insights into physical phenomena characterized by multi-exponential decay.