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July 7, 20260 citationsOpen Access

The Wallis Weight Kernel: A Family of Soft-Cutoff Regularization Weights from the Classical Wallis Product

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JNJudsan Niyakaran

Key Points

  • This work aims to introduce Wallis Weight Kernels and demonstrate their utility in regularizing harmonic series.
  • Developed a parameterized family of Wallis Weight Kernels for s ∈ ℝ.
  • Provided closed-form evaluations of harmonic series using the Wallis Weight Kernels.
  • Compared the Wallis kernels to standard regularization methods like Zeta and Borel.
  • Validated the asymptotic behavior of Wallis Weight Kernels.
  • Closed-form evaluation results include ∑ W(n)/n = 2 ln 2 and ∑ W(n)/n² = π²/4 - 2 ln² 2.
  • Demonstrated advantages of Wallis kernels as a smooth UV cutoff compared to hard cutoff methods.

Abstract

In this paper, I introduce a family of Wallis Weight Kernels: Wₛ (n) = ∏₊=₁ⁿ (2k-s) / (2k), for s ∈ ℝ. For s = 1, this reduces to the classical Wallis product partial sequence W (n) ~ 1/√ (π n). I prove the asymptotic behavior of the general family, demonstrate its utility in regularizing higher-order harmonic series, and provide closed-form evaluations: ∑ W (n) /n = 2 ln 2∑ W (n) /n² = π²/4 - 2 ln² 2 I compare the kernel to standard regularization methods (Zeta, Hard Cutoff, Borel) and show its advantages as a smooth, algebraically natural UV cutoff. This work provides a foundational tool for the Unified Regularization Principle. Key results: - A parameterized family of Wallis kernels- Soft-cutoff UV regularization weight- Closed-form evaluations for harmonic series- Comparison with existing regularization methods

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Cite This Study

Judsan Niyakaran (2026) studied this question.

synapsesocial.com/papers/6a4c9711331bc25c9e5f4292https://doi.org/10.5281/zenodo.21208069
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