SciPost Submission Page

Multi-scale Mining of Kinematic Distributions with Wavelets

by Ben G. Lillard, Tilman Plehn, Alexis Romero, Tim M. P. Tait

Submission summary

As Contributors: Benjamin Lillard · Tilman Plehn · Tim Tait
Arxiv Link: https://arxiv.org/abs/1906.10890v3
Date accepted: 2020-02-14
Date submitted: 2020-02-05
Submitted by: Lillard, Benjamin
Submitted to: SciPost Physics
Discipline: Physics
Subject area: High-Energy Physics - Phenomenology
Approaches: Theoretical, Experimental

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.

Current status:
Publication decision taken: accept

Editorial decision: For Journal SciPost Physics: Publish
(status: Editorial decision fixed and (if required) accepted by authors)



Author comments upon resubmission

In our resubmitted manuscript, we have made a few changes to the text, most notably to emphasize the utility of the fixed resolution global significance (FRGS) as a model-independent analysis tool. We have also made modifications to the text and figures to address typos and to add clarity to certain sections.

List of changes

1. In Fig.1, Fig.4 and Fig.5 we have added the original injected signal in the second panel of each plot.

2. In Section 2.1 we have added text to clarify that the discrete signal "f_j" and the function "f(x)" represent the same distribution.

3. We have added a paragraph in Sec. 2.3. to introduce the fixed resolution global significance (FRGS) in the body of the paper.

4. In Section 3.1 on page 10 we add a paragraph describing how the fraction of wavelet coefficients to use in the signal reconstruction in Fig.4 provides primarily a qualitative description of the excess signal, and that the choice to use 3%, 5%, 10% or some other fraction does not affect the statistical analysis.

Submission & Refereeing History

Resubmission 1906.10890v3 on 5 February 2020
Submission 1906.10890v2 on 28 August 2019

Reports on this Submission

Anonymous Report 1 on 2020-2-7 Invited Report

Report

The new draft is noticeably improved, easier to read, and more useful as a reference.

  • validity: top
  • significance: good
  • originality: high
  • clarity: high
  • formatting: good
  • grammar: perfect

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