Shallow Quantum Circuit

Shallow quantum circuits, comprised of a limited number of quantum gates, are a central focus in near-term quantum computing research due to their feasibility on current hardware. Current research emphasizes developing efficient algorithms for designing and learning these circuits, often employing variational methods, memetic optimization, and quantum-inspired classical algorithms to address challenges like noise and the efficient estimation of probability distributions. These efforts aim to unlock the potential of shallow quantum circuits for applications such as quantum machine learning, solving partial differential equations, and anomaly detection, bridging the gap between theoretical quantum advantage and practical implementation.