The difference between doubly nonnegative and completely positive matrices

✍ Scribed by Samuel Burer; Kurt M. Anstreicher; Mirjam Dür

• Publisher: Elsevier Science
• Year: 2009
• Tongue: English
• Weight: 223 KB
• Volume: 431
• Category: Article
• ISSN: 0024-3795
• DOI: 10.1016/j.laa.2009.05.021

✦ Synopsis

The convex cone of n × n completely positive (CP) matrices and its dual cone of copositive matrices arise in several areas of applied mathematics, including optimization. Every CP matrix is doubly nonnegative (DNN), i.e., positive semidefinite and component-wise nonnegative, and it is known that, for n 4 only, every DNN matrix is CP. In this paper, we investigate the difference between 5 × 5 DNN and CP matrices. Defining a bad matrix to be one which is DNN but not CP, we: (i) design a finite procedure to decompose any n × n DNN matrix into the sum of a CP matrix and a bad matrix, which itself cannot be further decomposed; (ii) show that every bad 5 × 5 DNN matrix is the sum of a CP matrix and a single bad extreme matrix; and (iii) demonstrate how to separate bad extreme matrices from the cone of 5 × 5 CP matrices.