Understanding Chi-Squared Plots & CP Violation Ranges

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    Chi-squared Plots
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Discussion Overview

The discussion focuses on understanding chi-squared plots, specifically relating to CP violation ranges and their connection to statistical significance levels (3 and 5 sigma). The context includes theoretical and experimental aspects of particle physics, particularly in neutrino oscillation experiments.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant seeks clarification on how to relate chi-squared plots to CP violation ranges and sigma levels.
  • Another participant notes that assumptions about the behavior of the chi-squared distribution are necessary for applying Wilks' theorem, which is crucial for determining if the delta chi-squared is chi-squared distributed.
  • This participant mentions that an alternative approach could involve Monte Carlo simulations, but indicates that this is not the method used in the referenced plots.
  • It is pointed out that the plots represent sensitivity rather than definitive limits, as actual experimental data may lead to fluctuations that affect the results.
  • References to relevant papers on the sensitivity of oscillation experiments and CP violation are provided to support the discussion.

Areas of Agreement / Disagreement

Participants express differing views on the applicability of the chi-squared distribution in this context, indicating that the discussion remains unresolved regarding the assumptions needed for its use.

Contextual Notes

Limitations include the need for specific assumptions about the chi-squared behavior and the potential discrepancies between sensitivity plots and actual experimental outcomes.

kimmm
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Would you please help me to understand the chi-squared plot the third plot in the bellow list.
How can I relate the cp violation ranges to the 3 and 5 sigma?
(http://inspirehep.net/record/1473193/plots)

 
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A priori, you cannot, you need to make some assumptions on how the ##\chi^2## behaves. Essentially you need the conditions of Wilks' theorem to apply so that the ##\Delta \chi^2## is actually ##\chi^2## distributed. The aternative is deducing the distribution from a Monte Carlo simulation but that is not what is done here.

This question (whether you can use the ##\chi^2## distribution or not) was rather heatedly debated in the neutrino community 4-5 years ago. I wrote several papers on the subject, the most relevant to your question being:
 
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Also, it should be mentioned that these are sensitivity plots. They tell you the typical result you would expect from the experiment. The actual limits will later be set by the actual data, which may have up- or down-fluctuations.
 
Orodruin said:
Thank you so much for the references.
 
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