Matrix properties
number of rows	14,318
number of columns	11,028
nonzeros	57,376
structural full rank?	yes
structural rank	11,028
# of blocks from dmperm	1,722
# strongly connected comp.	1
explicit zero entries	0
nonzero pattern symmetry	0%
numeric value symmetry	0%
type	real
structure	rectangular
Cholesky candidate?	no
positive definite?	no

author	Y. Cheng
editor	T. Davis
date	2007
kind	power network problem
2D/3D problem?	no

Additional fields	size and type
b	full 14318-by-1
guess	full 11028-by-1

Notes:

Power system state simulation matrix from Yunzhi Cheng, UT Arlington.
In MATLAB, the solution to x=A\b is desired, but this can be slow in 
MATLAB 7.3 because of the speed of sparse QR as compared to sparse   
Cholesky.  Using x=(A'*A)\(A'*b) is faster, but of course yields     
slightly less accurate (but still acceptable) results.  Note that an 
initial guess to the solution is provided, for use by an iterative   
method.  However, sparse Cholesky with an AMD ordering is very fast  
for this matrix and thus iterative methods are unlikely to be        
competitive.  In MATLAB 7.3 on a 3.2 Ghz Pentium 4 desktop,          
x=(A'*A)\(A'*b) takes 0.05 seconds.                                  

Ordering statistics:	result
nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD	715,497
nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD	90,200

SVD-based statistics:
norm(A)	200125
min(svd(A))	0.177926
cond(A)	1.12477e+06
rank(A)	11,028
sprank(A)-rank(A)	0
null space dimension	0
full numerical rank?	yes

singular values (MAT file):	click here
SVD method used:	s = svd (full (A)) ;
status:	ok

For a description of the statistics displayed above, click here.

Maintained by Tim Davis, last updated 12-Mar-2014.
Matrix pictures by cspy, a MATLAB function in the CSparse package.
Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.