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Challenges of profile likelihood evaluation in multi-dimensional SUSY scans

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Abstract

Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist conifidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MultiNest, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration previously used in the literarture is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MultiNest configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MultiNest is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.

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Author information

Authors and Affiliations

  1. Cavendish Laboratory, JJ Thomson Avenue, Cambridge, CB3 0HE, U.K.

    Farhan Feroz & Mike Hobson

  2. Center for Cosmology and Particle Physics, New York University, Washington Place, New York, NY, 10003, U.S.A.

    Kyle Cranmer

  3. Instituto de Física Corpuscular, IFIC-UV/ CSIC, Valencia, Spain

    Roberto Ruiz de Austri

  4. Imperial College London, Blackett Laboratory, Prince Consort Road, London, SW7 2AZ, U.K.

    Roberto Trotta

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  1. Farhan Feroz
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  2. Kyle Cranmer
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  3. Mike Hobson
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  4. Roberto Ruiz de Austri
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  5. Roberto Trotta
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Correspondence to Roberto Trotta.

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Feroz, F., Cranmer, K., Hobson, M. et al. Challenges of profile likelihood evaluation in multi-dimensional SUSY scans. J. High Energ. Phys. 2011, 42 (2011). https://doi.org/10.1007/JHEP06(2011)042

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  • DOI: https://doi.org/10.1007/JHEP06(2011)042

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