Nuclear and high energy physics facilities, such as CERN, Jefferson Lab, RHIC, and the forthcoming EIC, have been built around the world to study the visible universe at the fermi scale. They are already producing exabytes of data. This unprecedented amount of data holds the promise of solving many of the mysteries in elementary particle interactions such as QCD in the nonperturbative regime. However, extracting the required information is an extremely challenging task, as there is no available analytic solution to interpret data. Solving this challenge requires nuclear and particle physics to develop and adopt methods from data science, AI/ML, applied mathematics, and large-scale computing and adapt them to this goal. Digital twins, in particular, can simulate and model complex nuclear and elementary particle processes, providing a virtual replica that enhances understanding and predictive capabilities. This multidisciplinary approach, fostering cross-field collaboration and the exchange of ideas, is still in its infancy. The integration of digital twins into nuclear and particle physics could revolutionize how we approach and solve these complex challenges.
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