Speaker
Description
ACTS is an experiment independent toolkit for track reconstruction, which is designed from the ground up for thread-safety and high performance. It is built to accommodate different experiment deployment scenarios, and also serves as community platform for research and development of new approaches and algorithms.
The Event Data Model (EDM) is a critical piece of the tracking library that is visible to clients. Until this point, ACTS was mostly focused on an internal EDM, targeting data interchange betweens various components in the toolkit.
This contribution reports on a new and improved client EDM for ACTS. For an experiment-agnostic toolkit like ACTS, this requires strong abstractions of potentially experiment-specific details, including event context data like sensor alignments, and tracking inputs like measurements. By applying similar abstraction strategies, the presented EDM can be an expressive, low-overhead abstraction over experiment-specific backends, and seamlessly integrates into an experiment framework and IO model.
The presented EDM includes the ACTS track class, the main data type which tracking clients interact with. It is designed to be interfaced with different IO backends, and also flexible enough to support dynamic information required by various track fitters. At the same time, careful design ensures it can seamlessly serve as a key data object in experiment reconstruction data flows.
In this contribution, the interaction of this centerpiece of the example workflows in ACTS with the standalone ROOT IO, as well as the integration with the EDM4hep package will be shown, and key performance characteristics discussed.
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