I. F. Araujo, C. Blank, I. C. S. Araújo and A. J. da Silva, “Low-Rank Quantum State Preparation,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, doi: 10.1109/TCAD.2023.3297972.
Ubiquitous in quantum computing is the step to encode data into a quantum state. This process is called quantum state preparation, and its complexity for non-structured data is exponential on the number of qubits. Several works address this problem, for instance, by using variational methods that train a fixed depth circuit with manageable complexity. These methods have their limitations, as the lack of a back-propagation technique and barren plateaus. This work proposes an algorithm to reduce state preparation circuit depth by offloading computational complexity to a classical computer. The initialized quantum state can be exact or an approximation, and we show that the approximation is better on today’s quantum processors than the initialization of the original state. Experimental evaluation demonstrates that the proposed method enables more efficient initialization of probability distributions in a quantum state.
Israel F. Araujo, Department of Statistics and Data Science, Yonsei University, Seoul, Republic of Korea
Carsten Blank, Data Cybernetics, Landsberg am Lech, Germany
Ismael C. S. Araújo, Centro de Informática, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
Adenilton J. da Silva, Centro de Informática, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil