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Author (up) Bridges, M.; Cranmer, K.; Feroz, F.; Hobson, M.; Ruiz de Austri, R.; Trotta, R.
Title A coverage study of the CMSSM based on ATLAS sensitivity using fast neural networks techniques Type Journal Article
Year 2011 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 03 Issue 3 Pages 012 - 23pp
Keywords Supersymmetry; Phenomenology
Abstract We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of similar to 10(4) with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.
Address [Bridges, Michael; Feroz, Farhan; Hobson, Mike] Univ Cambridge, Cavendish Lab, Astrophys Grp, Cambridge CB3 0HE, England, Email: mb435@mrao.cam.ac.uk
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1126-6708 ISBN Medium
Area Expedition Conference
Notes ISI:000289295200012 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 610
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Author (up) Feroz, F.; Cranmer, K.; Hobson, M.; Ruiz de Austri, R.; Trotta, R.
Title Challenges of profile likelihood evaluation in multi-dimensional SUSY scans Type Journal Article
Year 2011 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 06 Issue 6 Pages 042 - 23pp
Keywords Supersymmetry Phenomenology
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 confidence 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.
Address [Feroz, F; Hobson, M] Univ Cambridge, Cavendish Lab, Cambridge CB3 0HE, England, Email: f.feroz@mrao.cam.ac.uk
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1126-6708 ISBN Medium
Area Expedition Conference
Notes WOS:000293136500042 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ elepoucu @ Serial 745
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Author (up) Johannesson, G.; Ruiz de Austri, R.; Vincent, A.C.; Moskalenko, I.V.; Orlando, E.; Porter, T.A.; Strong, A.W.; Trotta, R.; Feroz, F.; Graff, P.; Hobson, M.P.
Title Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion Type Journal Article
Year 2016 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.
Volume 824 Issue 1 Pages 16 - 19pp
Keywords astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical
Abstract We present the results of the most complete scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine-learning package. This is the first study to separate out low-mass isotopes (p, (p) over bar and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit p, (p) over bar, and He data are significantly different from those that fit light elements, including the B/C and Be-10/Be-9 secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests that each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best-fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update.
Address [Johannesson, G.] Univ Iceland, Inst Sci, Dunhaga 3, IS-107 Reykjavik, Iceland
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-637x ISBN Medium
Area Expedition Conference
Notes WOS:000377937300016 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2727
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Author (up) Strege, C.; Bertone, G.; Feroz, F.; Fornasa, M.; Ruiz de Austri, R.; Trotta, R.
Title Global fits of the cMSSM and NUHM including the LHC Higgs discovery and new XENON100 constraints Type Journal Article
Year 2013 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.
Volume 04 Issue 4 Pages 013 - 40pp
Keywords dark matter theory; supersymmetry and cosmology
Abstract We present global fits of the constrained Minimal Supersymmetric Standard Model (cMSSM) and the Non-Universal Higgs Model (NUHM), including the most recent CMS constraint on the Higgs boson mass, 5.8 fb(-1) integrated luminosity null Supersymmetry searches by ATLAS, the new LHCb measurement of B R ((B) over bar (s) -> mu(+) mu(-)) and the 7-year WMAP dark matter relic abundance determination. We include the latest dark matter constraints from the XENON100 experiment, marginalising over astrophysical and particle physics uncertainties. We present Bayesian posterior and profile likelihood maps of the highest resolution available today, obtained from up to 350M points. We find that the new constraint on the Higgs boson mass has a dramatic impact, ruling out large regions of previously favoured cMSSM and NUHM parameter space. In the cMSSM, light sparticles and predominantly gaugino-like dark matter with a mass of a few hundred GeV are favoured. The NUHM exhibits a strong preference for heavier sparticle masses and a Higgsino-like neutralino with a mass of 1 TeV. The future ton-scale XENON1T direct detection experiment will probe large portions of the currently favoured cMSSM and NUHM parameter space. The LHC operating at 14 TeV collision energy will explore the favoured regions in the cMSSM, while most of the regions favoured in the NUHM will remain inaccessible. Our best-fit points achieve a satisfactory quality-of-fit, with p-values ranging from 0.21 to 0.35, so that none of the two models studied can be presently excluded at any meaningful significance level.
Address Univ London Imperial Coll Sci Technol & Med, Blackett Lab, Astrophys Grp, London SW7 2AZ, England, Email: charlotte.strege09@imperial.ac.uk;
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1475-7516 ISBN Medium
Area Expedition Conference
Notes WOS:000318556200013 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 1445
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