Abstract
Radiation damage significantly impacts the performance of silicon tracking detectors in Large Hadron Collider (LHC) experiments such as ATLAS and CMS, with signal reduction being the most critical effect; adjusting sensor bias voltage and detection thresholds can help mitigate these effects, generating simulated data that accurately mirror the performance evolution with the accumulation of luminosity, hence fluence, is crucial. The ATLAS and CMS collaborations have developed and implemented algorithms to correct simulated Monte Carlo (MC) events for radiation damage effects, achieving impressive agreement between collision data and simulated events. In preparation for the high-luminosity phase (HL-LHC), the demand for a faster ATLAS MC production algorithm becomes imperative due to escalating collision, events, tracks, and particle hit rates, imposing stringent constraints on available computing resources. This article outlines the philosophy behind the new algorithm, its implementation strategy, and the essential components involved. The results from closure tests indicate that the events simulated using the new algorithm agree with fully simulated events at the level of few %. The first tests on computing performance show that the new algorithm is as fast as it is when no radiation damage corrections are applied.