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March 17, 2026Black Sea Journal of Engineering and Science2 citationsOpen Access

Halving the Error in Second Order Adams-Bashforth Methods via a Simple Time Filter

AGAhmet GuzelBatman University

Key Points

  • To improve the accuracy and stability of second order Adams-Bashforth methods using a simple time filter.
  • Implemented a time filter by adding a new code line to the existing algorithm.
  • Modeled the system using a unified linear multistep method framework.
  • Applied the Jury stability criterion to verify stability of the modified scheme.
  • Conducted a local truncation error analysis to assess performance.
  • The time filter halves the leading error coefficient compared to the original method.
  • Numerical stability is achieved with roots of the characteristic polynomial within the unit circle.
  • The enhanced method provides superior accuracy with minimal computational cost.

Abstract

This paper presents the implementation and rigorous analysis of a simple time filter applied to the second order Adams-Bashforth family of explicit numerical integration schemes. Although the implementation is remarkably straightforward—requiring the modular addition of just a single line of code—the resulting mathematical benefits are substantial, making it highly attractive for legacy scientific codebases. By theoretically modeling the coupled system as a unified linear multistep method, we are able to apply standard stability frameworks to the modified scheme. Specifically, we verify numerical stability using the Jury stability criterion, ensuring that the roots of the characteristic polynomial remain within the unit circle for the desired parameter range. Furthermore, we perform a detailed local truncation error analysis. Our results demonstrate that the filter acts to dampen the parasitic computational mode and effectively halves the leading error coefficient compared to the unfiltered method. This provides a robust enhancement to the original algorithm, yielding superior accuracy with negligible computational cost, as it avoids the expensive function evaluations associated with higher-order or implicit methods.

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Cite This Study

Ahmet Guzel (2026) studied this question.

synapsesocial.com/papers/69b8f13ddeb47d591b8c648fhttps://doi.org/10.34248/bsengineering.1870475
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