Speed-up of Neuromorphic Adiabatic Quantum Computation by Local Adiabatic Evolution

• Published in: 2011 41st IEEE International Symposium on Multiple-Valued Logic pp. 302 - 306
• Main Authors: Kinjo, M., Shimabukuro, K.
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.05.2011
• Subjects: Adiabatic Quantum Computation; Artificial neural networks; Hafnium; Heuristic algorithms; Loacl Adiabatic Evolution; Neural Network; Neuromorphics; Neurons; Quantum computing; Stationary state
• ISBN: 145770112X; 9781457701122
• ISSN: 0195-623X
• DOI: 10.1109/ISMVL.2011.63

Farhi et al. have proposed an adiabatic quantum computation (AQC), which can be applied to NP-problems if one can know an appropriate Hamiltonian for a target problem. We have proposed a neuromorphic adiabatic quantum computation (NAQC) as the AQC with energy dissipation and an efficient method for designing a final Hamiltonian in consideration of the analogy with a neural network. The NAQC can be applied to optimization problems if its cost function can be expressed in a quadratic form. And successful operations have been confirmed by numerical simulations. In addition, local adiabatic evolution for quantum search have proposed by Roland et al. in order to speed-up the calculation time. In this paper, we show preliminary results for NAQC with local adiabatic evolution by numerical simulations.