This work package focuses on an enhancement of the already ambitious upgrade of the ATLAS experiment’s trigger and data acquisition system for the High Luminosity Phase of the LHC (HL-LHC) scheduled to start in 2029. Novel approaches to trigger event selection will be developed that will extend the ATLAS physics potential, in particular exploiting state-of-the-art Machine Learning techniques. Efficient use of acceleration technologies will be investigated to extend the capabilities of the trigger and data acquisition system, while improving the system’s energy efficiency. A successful implementation of this work package will result in the collection of richer collision events, extend the experiment’s sensitivity to a broader range of new physics beyond the Standard Model scenarios, and enable ATLAS to exploit state-of-the-art processing architectures in its online event selection to achieve the best possible physics performance at HL-LHC.

WP2 is composed of a range of specific interdisciplinary tasks connecting different activities within the ATLAS experiment and other project tasks.