Student Posters Repository

Kohn-Sham Density Functional Theory is commonly used for addressing the ab initio electronic structure calculation. Ab initio electronic structure calculation enables us to understand the microscopic behaviors of materials due to quantum effects. However, the computational costs and the scaling with systems for performing DFT calculations is extremely high with O(N^3) for the most widely used plane wave basis function, where N accounts for the number of electrons. It thus becomes important to improve the efficiency of the calculation by reducing the order of the scaling and floating point arithmetic cost. In our research, we used the tensor algorithm to construct a set of basis with a resemblance to the exact solution to reduce the scaling with the system size to sublinear. In the same time, we construct a set of localized basis function representing the same eigenspace of the basis. The localized basis thus improves the sparsity of the resulting matrix to be solved with spectrum decomposition and reduces the floating point operations. With the tensor-structured technique, we could bring the DFT calculation to sublinear scaling and improves the arithmetic performance of the calculation.