TY - CHAP A1 - Franz, Maja A1 - Zurita, Pía A1 - Diefenthaler, Markus A1 - Mauerer, Wolfgang T1 - Co-Design of Quantum Hardware and Algorithms in Nuclear and High Energy Physics T2 - EPJ Web of Conferences N2 - Quantum computing (QC) has emerged as a promising technology, and is believed to have the potential to advance nuclear and high energy physics (NHEP) by harnessing quantum mechanical phenomena to accelerate computations. In this paper, we give a brief overview of the current state of quantum computing by highlighting challenges it poses and opportunities it offers to the NHEP community. Noisy intermediate-scale quantum (NISQ) computers, while limited by imperfections and small scale, may hold promise for near-term quantum advantages when coupled with co-designed quantum algorithms and special-purpose quantum processing units (QPUs). We explore various applications in NHEP, including quantum simulation, event classification, and realtime experiment control, emphasising the potential of variational quantum circuits and related techniques. To identify current interests of the community, we perform an analysis of recent literature in NHEP related to QC. Y1 - 2024 U6 - https://doi.org/10.1051/epjconf/202429512002 VL - 295 PB - EDP Sciences ER - TY - JOUR A1 - Franz, Maja A1 - Schönberger, Manuel A1 - Strobl, Melvin A1 - Kühn, Eileen A1 - Streit, Achim A1 - Zurita, Pía A1 - Diefenthaler, Markus A1 - Mauerer, Wolfgang T1 - From Hope to Heuristic: Realistic Runtime Estimates for Quantum Optimisation in NHEP JF - EPJ Web of Conferences; 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024) N2 - Noisy Intermediate-Scale Quantum (NISQ) computers, despite their limitations, present opportunities for near-term quantum advantages in Nuclear and High-Energy Physics (NHEP) when paired with specially designed quantum algorithms and processing units. This study focuses on core algorithms that solve optimization problems through the quadratic Ising or Quadratic Unconstrained Binary Optimisation model, specifically Quantum Annealing and the Quantum Approximate Optimisation Algorithm (QAOA). In particular, we estimate runtimes and scalability for the task of particle Track Reconstruction (TR), a key computing challenge in NHEP, and investigate how the classical parameter space in QAOA, along with techniques like a Fourieranalysis based heuristic, can facilitate future quantum advantages. The findings indicate that lower frequency components in the parameter space are crucial for effective annealing schedules, suggesting that heuristics can improve resource efficiency while achieving near-optimal results. Overall, the study highlights the potential of NISQ computers in NHEP and the significance of co-design approaches and heuristic techniques in overcoming challenges in quantum algorithms. Y1 - 2025 U6 - https://doi.org/10.1051/epjconf/202533701282 N1 - Corresponding author der OTH Regensburg: Maja Franz VL - 337 PB - EDP Sciences ER -