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Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment

Title: Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment
Authors: Jeff Hartnell; Lily Asquith; Alexander Craig Booth; Robert Kralik; Pierre Lasorak; Brett Mayes; Joshua Porter; Yibing Zhang
Publication Year: 2025
Collection: University of Sussex (US): Figshare
Subject Terms: Engineering; Physical sciences; 02 Physical Sciences; 09 Engineering; Nuclear & Particles Physics; 40 Engineering; 51 Physical sciences
Description: Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino oscillation measurements and other experimental scenarios. Monte Carlo methods can address these issues, albeit at increased computational cost. In the presence of nuisance parameters, however, the best way to implement a Monte Carlo method is ambiguous. This paper documents the method selected by the NOvA experiment, the profile construction. It presents the toy studies that informed the choice of method, details of its implementation, and tests performed to validate it. It also includes some practical considerations which may be of use to others choosing to use the profile construction.
Document Type: article in journal/newspaper
Language: unknown
Relation: 10779/uos.28359230.v1; https://figshare.com/articles/journal_contribution/Monte_Carlo_method_for_constructing_confidence_intervals_with_unconstrained_and_constrained_nuisance_parameters_in_the_NOvA_experiment/28359230
Availability: https://figshare.com/articles/journal_contribution/Monte_Carlo_method_for_constructing_confidence_intervals_with_unconstrained_and_constrained_nuisance_parameters_in_the_NOvA_experiment/28359230
Rights: CC BY 4.0
Accession Number: edsbas.7B572102
Database: BASE