Exploring physical reservoir computing mechanisms by ultra-thin Si nanoresonators for enhancing computational reliability

• Project/Area Number: 24K08219
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 28050:Nano/micro-systems-related
• Research Institution: Kyoto University
• Principal Investigator: BANERJEE Amit 京都大学, 工学研究科, 講師 (20894794)
• Project Period (FY): 2024-04-01 – 2027-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000); Fiscal Year 2026: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2025: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000); Fiscal Year 2024: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
• Keywords: Reservoir computing / NEMS resonator / Nonlinear dynamics

Outline of Research at the Start

Physical reservoir computing (PRC), a brain-inspired hardware-based AI method has many promising practical applications, but the underlying mechanisms of PRC are not well understood. We aim to develop a tunable PRC system to perform systematic experimental studies to gain insight on PRC mechanisms.