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Author (up) Costantini, M.N.; Mantani, L.; Moore, J.M.; Schütze Sanchez, V.; Ubiali, M. url  doi
openurl 
  Title A new tool for fast-flying PDF fits Type Journal Article
  Year 2026 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 86 Issue 1 Pages 22 - 19pp  
  Keywords  
  Abstract We present Colibri, an open-source Python code that provides a general and flexible tool for PDF fits. The code is built so that users can implement their own PDF model, and use the built-in functionalities of Colibri for a fast computation of observables. It grants easy access to experimental data, several error propagation methodologies, including the Hessian method, the Monte Carlo replica method, and an efficient numerical Bayesian sampling algorithm. To demonstrate the capabilities of Colibri, we consider its simplest application: a polynomial PDF parametrisation. We perform closure tests using a full set of DIS data and compare the results of Hessian and Monte Carlo fits with those from a Bayesian fit. We further discuss how the functionalities illustrated in this example can be extended to more complex PDF parametrisations. In particular, the Bayesian framework in Colibri provides a principled approach to model selection and model averaging, making it a valuable tool for benchmarking and combining different PDF parametrisations on solid statistical grounds.  
  Address [Costantini, Mark N.; Sanchez, Valentina Schutze; Ubiali, Maria] Univ Cambridge, DAMTP, Wilberforce Rd, Cambridge CB3 0WA, England, Email: mnc33@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 1434-6044 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001661525500003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 7028  
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