Why is Dimensionality Reduction Important in Nanotechnology?
The significance of dimensionality reduction in nanotechnology lies in its ability to handle the vast amounts of data generated at the nanoscale. Techniques such as Principal Component Analysis (PCA) and t-SNE are often employed to reduce the number of variables and reveal underlying patterns in the data. This simplification can lead to better understanding of nanoscale phenomena, improved material properties, and more efficient nanodevices.
