Deterministic Column-Based Matrix Decomposition

In this paper, we propose a deterministic column-based matrix decomposition method. Conventional column-based matrix decomposition (CX) computes the columns by randomly sampling columns of the data matrix. Instead, the newly proposed method (termed as CX_D) selects columns in a deterministic manner, which well approximates singular value decomposition. The experimental results well demonstrate the power and the advantages of the proposed method upon three real-world data sets.

Design of slow extraction system for therapy synchrotron

Based on the optimized design of the lattice for therapy synchrotron and considering the requirement of radiation therapy, the third order resonant extraction is adopted. Using the momentum-amplitude selection method, the extraction system is designed and optimized. An extraction efficiency of more than 97% and a momentum spread less than 0.11% are obtained.