Matrix: Priebel/130bit
Description: Quadratic sieve; factoring a 130bit number. D. Priebel, Tenn. Tech Univ
(bipartite graph drawing) |
Matrix properties | |
number of rows | 584 |
number of columns | 575 |
nonzeros | 6,120 |
structural full rank? | no |
structural rank | 566 |
# of blocks from dmperm | 45 |
# strongly connected comp. | 9 |
explicit zero entries | 0 |
nonzero pattern symmetry | 0% |
numeric value symmetry | 0% |
type | binary |
structure | rectangular |
Cholesky candidate? | no |
positive definite? | no |
author | D. Priebel |
editor | T. Davis |
date | 2009 |
kind | combinatorial problem |
2D/3D problem? | no |
Additional fields | size and type |
factor_base | full 575-by-1 |
smooth_number | full 584-by-20 |
solution | full 261-by-1 |
Notes:
Each column in the matrix corresponds to a number in the factor base less than some bound B. Each row corresponds to a smooth number (able to be completely factored over the factor base). Each value in a row binary vector corresponds to the exponent of the factor base mod 2. For example: factor base: 2 7 23 smooth numbers: 46, 28, 322 2^1 * 23^1 = 46 2^2 * 7^1 = 28 2^1 * 7^1 * 23^1 = 322 Matrix: 101 010 111 A solution to the matrix is considered to be a set of rows which when combined in GF2 produce a null vector. Thus, if you multiply each of the smooth numbers which correspond to that particular set of rows you will get a number with only even exponents, making it a perfect square. In the above example you can see that combining the 3 vectors results in a null vector and, indeed, it is a perfect square: 644^2. Problem.A: A GF(2) matrix constructed from the exponents of the factorization of the smooth numbers over the factor base. A solution of this matrix is a kernel (nullspace). Such a solution has a 1/2 chance of being a factorization of N. Problem.aux.factor_base: The factor base used. factor_base(j) corresponds to column j of the matrix. Note that a given column may or may not have nonzero elements in the matrix. Problem.aux.smooth_number: The smooth numbers, smooth over the factor base. smooth_number(i) corresponds to row i of the matrix. Problem.aux.solution: A sample solution to the matrix. Combine, in GF(2) the rows with these indicies to produce a solution to the matrix with the additional property that it factors N (a matrix solution only has 1/2 probability of factoring N). Problem specific information: n = 787911249838484617926390474950774839909 (130-bits) passes primality test, n is composite, continuing... 1) Initial bound: 10000, pi(10000) estimate: 1085, largest found: 8707 (actual bound) 2) Number of quadratic residues estimate: 725, actual number found: 574 3) Modular square roots found: 1148(2x residues) 4) Constructing smooth number list [sieving] (can take a while)... Sieving for: 584 5. Constructing a matrix of size: 584x575 Matrix solution found with: 261 combinations Divisor: 23850290715477455017 (probably prime) Divisor: 33035708421246870877 (probably prime)
Ordering statistics: | result |
nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD | 56,434 |
nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD | 64,716 |
SVD-based statistics: | |
norm(A) | 30.5208 |
min(svd(A)) | 7.22461e-17 |
cond(A) | 4.22456e+17 |
rank(A) | 566 |
sprank(A)-rank(A) | 0 |
null space dimension | 9 |
full numerical rank? | no |
singular value gap | 8.13682e+12 |
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.