Application of data visualisation in particle physics
- Event time: 2:30pm until 3:30pm
- Event date: 9th November 2006
- Speaker: Stephen Watts (Brunel University)
- Location: Room 4309, James Clerk Maxwell Building (JCMB) James Clerk Maxwell Building Peter Guthrie Tait Road Edinburgh EH9 3FD GB
Visualisation of data in particle physics currently involves event displays, histograms, line graphs and scatterplots. Since 1975 there has been an explosion of techniques for data visualisation driven by highly interactive computer systems and ideas from statistical graphics. This field has been driven by demands for data mining of large databases and genomics. Two key areas are direct manipulation of visual data and new methods for visualising high-dimensional data. The first area has seen the use of linked views, brushing and pruning. The second area has seen the introduction of methods such as parallel coordinates and the grand tour. In this talk, these ideas are applied to particle physics data to evaluate their ability to reduce data analysis time and improve pattern recognition. In particular, parallel coordinates will be used to analyse a sample of K-short Monte Carlo events. It will be shown that this graphical technique significantly reduces the time taken to determine the key variables for event selection.
The talk will also give a brief review of some data mining techniques and show how visualisation can help one to understand the effectiveness (or not) of some of these methods.
The talk will describe some publicly available software tools that include many of the new statistical graphics techniques and conclude that no single tool includes all the most powerful new techniques and argue that urgent work is required to integrate these ideas into data analysis tools for particle physics.
The experimental particle physics seminar series invites speakers from all over Europe to discuss the latest developments at the LHC, accelerator and non-accelerator based neutrino physics, hardware R&D and astroparticle physics. .