Multi-scale mining of kinematic distributions with wavelets
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Multi-scale mining of kinematic distributions with wavelets

  • Author(s): Lillard, Ben G
  • Plehn, Tilman
  • Romero, Alexis
  • Tait, Tim MP
  • et al.
Abstract

Typical LHC analyses search for local features in kinematic distributions. Assumptions about anomalous patterns limit them to a relatively narrow subset of possible signals. Wavelets extract information from an entire distribution and decompose it at all scales, simultaneously searching for features over a wide range of scales. We propose a systematic wavelet analysis and show how bumps, bump-dip combinations, and oscillatory patterns are extracted. Our kinematic wavelet analysis kit KWAK provides a publicly available framework to analyze and visualize general distributions.

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