Mega Science Research
Many international science experiment projects are becoming larger in scale and the volumes of experimental data produced from such efforts are becoming gigantic. This is the reason why deep learning is increasingly finding an important role in the analysis of scientific data.
For the success of International Mega Science Projects that concern scientific experiments using gravitational-wave detectors and the like, NIMS has collected scientific data through collaborative research among domestic and overseas researchers and performed research and development of data analysis methods for scientific experiment based on deep learning.
Key Research Content
- Deep learning applications to the data analysis of LIGO gravitational-wave detector data, an International Mega Science Project
- Research of data analysis methods and the mitigation of gravity gradient noise during next generation gravitational-wave observation experiments
- Mitigation methods of low-frequency band seismic noise including application of metamaterials and feasibility study on earthquake early detection using gravity change signal
- Development of non-linear correlation catching algorithms for the detection of anomaly and noise source of time series data
- Scientific research on gravitational-wave through international collaboration with KAGRA, Virgo, LIGO and research institutions and universities in Korea