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The development and operation of Liquid-Argon Time-Projection Chambers forneutrino physics has created a need for new approaches to pattern recognitionin order to fully exploit the imaging capabilities offered by this technology.Whereas the human brain can excel at identifying features in the recordedevents, it is a significant challenge to develop an automated, algorithmicsolution. The Pandora Software Development Kit provides functionality to aidthe design and implementation of pattern-recognition algorithms. It promotesthe use of a multi-algorithm approach to pattern recognition, in whichindividual algorithms each address a specific task in a particular topology.Many tens of algorithms then carefully build up a picture of the event and,together, provide a robust automated pattern-recognition solution. This paperdescribes details of the chain of over one hundred Pandora algorithms and toolsused to reconstruct cosmic-ray muon and neutrino events in the MicroBooNEdetector. Metrics that assess the current pattern-recognition performance arepresented for simulated MicroBooNE events, using a selection of final-stateevent topologies.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector