Electron-hadron shower discrimination in a liquid argon time projection chamber

By exploiting structural differences between electromagnetic and hadronic showers in a multivariate analysis we present an efficient Electron-Hadron discrimination algorithm for liquid argon time projection chambers, validated using Geant4 simulated data

Systematic event generator tuning for the LHC

In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the parameterised behaviour. Simulated experimental analysis data is obtained using the Rivet analysis toolkit. This paper presents the Professor procedure and implementation, illustrated with the application of the method to tunes of the Pythia 6 event generator to data from the LEP/SLD and Tevatron experiments. These tunes are substantial improvements on existing standard choices, and are recommended as base tunes for LHC experiments, to be themselves systematically improved upon when early LHC data is available.Comment: 28 pages. Submitted to European Physical Journal C. Program sources and extra information are available from http://projects.hepforge.org/professor

SciPy 1.0: fundamental algorithms for scientific computing in Python.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments