Les techniques Monte Carlo par chaînes de Markov appliquées à la détermination des distributions de partons

Abstract : We have developed a new approach to determine parton distribution functions and quantify their experimental uncertainties, based on Markov Chain Monte Carlo methods.The main interest devoted to such a study is that we can replace the standard χ 2 MINUIT minimization by procedures grounded on Statistical Methods, and on Bayesian inference in particular, thus offering additional insight into the rich field of PDFs determination.After reviewing these Markov chain Monte Carlo techniques, we introduce the algorithm we have chosen to implement – namely Hybrid (or Hamiltonian) Monte Carlo. This algorithm, initially developed for lattice quantum chromodynamique, turns out to be very interesting when applied to parton distribution functions determination by global analyses ; we have shown that it allows to circumvent the technical difficulties due to the high dimensionality of the problem, in particular concerning the acceptance rate. The feasibility study performed and presented in this thesis, indicates that Markov chain Monte Carlo method can successfully be applied to the extraction of PDFs and of their experimental uncertainties.
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Yémalin Gabin Gbedo. Les techniques Monte Carlo par chaînes de Markov appliquées à la détermination des distributions de partons. Physique Nucléaire Théorique [nucl-th]. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAY059⟩. ⟨tel-01743752⟩

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