| 研究実績の概要 |
During FY2022, we created a quantum annealing algorithm for simulating the assembly of surface-adsorbed molecules. During FY2023, we carried on this work as follows: (i) creation of a realistic intermolecular potential for the case of porphyrin molecules adsorbed to a (100) surface, using density functional theory and machine learning; (ii) programming of a quantum Monte Carlo (QMC) algorithm to predict the molecular assembly; (iii) extensive numerical simulations to evaluate QMC performance. It was confirmed that the QMC algorithm performs poorly compared to classical parallel tempering Monte Carlo over a variety of parameter regimes.
|
