MadAnalysis 5, a user-friendly framework for collider phenomenology

Abstract

We present MadAnalysis 5, a new framework for phenomenological investigations at particle colliders. Based on a C++ kernel, this program allows us to efficiently perform, in a straightforward and user-friendly fashion, sophisticated physics analyses of event files such as those generated by a large class of Monte Carlo event generators. MadAnalysis 5 comes with two modes of running. The first one, easier to handle, uses the strengths of a powerful Python interface in order to implement physics analyses by means of a set of intuitive commands. The second one requires one to implement the analyses in the C++ programming language, directly within the core of the analysis framework. This opens unlimited possibilities concerning the level of complexity which can be reached, being only limited by the programming skills and the originality of the user. Program summaryProgram title: MadAnalysis 5Catalogue identifier: AENO_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENO_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: Permission to use, copy, modify and distribute this program is granted under the terms of the GNU General Public License.No. of lines in distributed program, including test data, etc.: 31087No. of bytes in distributed program, including test data, etc.: 399105Distribution format: tar.gzProgramming language: PYTHON, C++.Computer: All platforms on which Python version 2.7, Root version 5.27 and the g++ compiler are available. Compatibility with newer versions of these programs is also ensured. However, the Python version must be below version 3.0.Operating system: Unix, Linux and Mac OS operating systems on which the above-mentioned versions of Python and Root, as well as g++, are available.Classification: 11.1.External routines: ROOT (http://root.cern.ch/drupal/)Nature of problem: Implementing sophisticated phenomenological analyses in high-energy physics through a flexible, efficient and straightforward fashion, starting from event files such as those produced by Monte Carlo event generators. The event files can have been matched or not to parton-showering and can have been processed or not by a (fast) simulation of a detector. According to the sophistication level of the event files (parton-level, hadron-level, reconstructed-level), one must note that several input formats are possible.Solution method: We implement an interface allowing the production of predefined as well as user-defined histograms for a large class of kinematical distributions after applying a set of event selection cuts specified by the user. This therefore allows us to devise robust and novel search strategies for collider experiments, such as those currently running at the Large Hadron Collider at CERN, in a very efficient way.Restrictions: Unsupported event file format.Unusual features: The code is fully based on object representations for events, particles, reconstructed objects and cuts, which facilitates the implementation of an analysis.Running time: It depends on the purposes of the user and on the number of events to process. It varies from a few seconds to the order of the minute for several millions of events.