Quantum computing in medical physics

Development of quantum hardware and software is progressing rapidly. With the availability of firstgenerally-accessible quantum computers, their potential use for applications can increasingly beexplored. One prospective field of application is data science in the medical sector including medical physics, where quantum-enhanced AI could lead to the ability to analyze more complex patterns in the data than classical AI methods. An example is medical imaging, where frequently only limited training data is available - making the use of classical AI methods challenging. However, presently available quantum computers are still limited in the number of qubits, the connectivity and are affected by noise. Due to this, it is currently impossible to obtain a clear quantum advantage like in Grover’s or Shor’s algorithm already today. But can we still profit from the currently available Noisy-Intermediate Scale quantum (NISQ) computers now or in the near future? What are the steps to take to obtain a practical quantum advantage in academic and industrial applications? What are the potential application fields,e.g, in the medical sector? My talk will first give an introduction to quantum computing, focusing in particular on near-term quantum computing: what is a ‚practical‘ quantum advantage? Then we look towards example applications in medical physics and tune in to the question which kind of advantages quantum computers may offer.