Recursive Alternating Amplitude Embedding: A Hybrid Quantum Circuit Architecture for Balanced Depth and Width
Abstract: Transforming classical data into quantum states is an important step in quantum information processing and quantum machine learning. Among various encoding methods, Amplitude Embedding is particularly attractive due to its exponential compression capability, allowing exponentially many classical values to be encoded using only a linear number of qubits. However, existing state preparation methods exhibit […]

