2021 Suematsu Award "Fundamentals and Developments of Digital Technology" Winners Announced

Award winners (from left in middle row) Kenichi Kawabe, Takayuki Miki, and Jun Yoneda with Honorary Professor Yasuharu Suematsu (third from left in top row) at the online award ceremony

Research Outline:

The excitation control systems of synchronous generators have played an important role in maintaining the stability of the generators in power systems. However, the conventional excitation systems may fail to maintain the stability because of unexpected electric power flow condition with large amount of renewable energy sources, which can lead to a large-scale blackout. In this study, the researcher works on the development of a novel excitation control method using advanced digital technologies such as a wide-area measurement system consisting of GPS-based measurement units and high-speed communication technologies. It is expected that the proposed excitation control system enables us to integrate large amount of renewable energy sources while maintaining stable power supply.

Research Outline:

In the field of drug discovery, peptide drugs with high target specificity and low side effects have been attracting attention. In the initial stage of the peptide-based drug discovery, there is a screening step for lead peptides, which will be the core structures for drug development. The phage display is one of the methods used for this screening. In this method, peptides that bind to the target molecule are selected from a peptide library consisting of randomized amino acid sequences. However, this method has a critical issue: it is difficult to apply to membrane proteins. Since membrane proteins are hard to be isolated and purified, peptide selection must be performed against membrane proteins present on the cell surface. In addition, the crude context containing various molecules on the cell surface makes the selection extremely difficult. Therefore, the author developed a method that combines next-generation sequencing and statistical analysis to establish a strategy for searching for lead peptides targeting membrane proteins on the cell membrane.

Research Outline:

Quantum dots in silicon are a nanostructure that can confine an electron spin in a quantum-mechanical superposition state for a relatively long time and are highly compatible with silicon technology. This makes the system a promising platform to realize a quantum computer – a computer that may initiate a new era of information society. It has recently been found that the performance of silicon quantum dots as quantum devices is limited by charge noise. In this research proposal, we will introduce the spatial aspect in the problem of charge noise in silicon devices by monitoring the spatial distribution of electrical fluctuations. Our goal is to establish the characterization method of noise correlations between quantum bits that influence the efficiency of quantum correcting codes crucial for digital quantum computation, offering a way to obtain one of the key metrics in the design of a large-scale quantum computer based on silicon quantum devices.