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Michael LeBlanc1, Aya Nawano1, Wendelin J Wright2,3

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Low time resolution in microplasticity data can distort avalanche size distributions. New methods are proposed to accurately recover avalanche distributions from low-resolution data, overcoming limitations of traditional analysis.

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Area of Science:

  • Materials Science
  • Physics
  • Data Analysis

Background:

  • Extracting avalanche distributions from microplasticity data is crucial for understanding material behavior.
  • Limited time resolution in experimental data acquisition poses a significant challenge to accurate analysis.

Purpose of the Study:

  • To investigate the impact of low time resolution on avalanche size distributions.
  • To develop and validate new methods for analyzing low-resolution microplasticity data.

Main Methods:

  • Simulating the effects of reduced time resolution on avalanche distributions.
  • Developing novel analytical techniques for low-resolution stress-time series.
  • Testing proposed methods on downsampled simulation and experimental data.

Main Results:

  • Low time resolution can lead to incorrect power-law exponents and scaling in avalanche size distributions.
  • Traditional analysis methods fail to accurately represent underlying avalanche behavior at low resolution.
  • Proposed methods successfully recover correct critical exponents from low-resolution data.

Conclusions:

  • Accurate analysis of microplasticity requires careful consideration of data acquisition rates.
  • The developed methods provide a robust solution for analyzing low-resolution data, enabling reliable extraction of avalanche distributions.