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7.2. COMPUTING THE GLOBAL MINIMUM USING TARGET SELECTION 113<br />
Table 7.4: Polynomial test cases of various complexities<br />
# n 2d Matrix size Global minimum Terms<br />
1 2 8 49 −7.259 11<br />
2 2 8 49 −4.719 7<br />
3 2 10 81 −20.71 19<br />
4 2 10 81 −24.85 19<br />
5 4 4 81 −24.45 13<br />
6 4 4 81 −37.41 17<br />
7 2 12 121 −3.711 × 10 4 22<br />
8 2 12 121 −52.77 23<br />
9 3 6 125 −20.63 21<br />
10 3 6 125 −142.9 19<br />
11 2 14 169 − 6116 36<br />
12 2 14 169 − 1115 33<br />
13 2 16 225 −2.927 × 10 6 46<br />
14 2 16 225 − 2258 40<br />
15 3 8 343 − 2398 34<br />
16 3 8 343 −884.9 42<br />
17 2 24 529 −1.944 × 10 4 78<br />
18 2 24 529 −1.062 × 10 7 88<br />
19 3 10 729 −1.218 × 10 4 57<br />
20 3 10 729 −1.349 × 10 4 72<br />
21 3 12 1331 −8.138 × 10 5 115<br />
22 3 12 1331 −1.166 × 10 6 112<br />
that is used is given in Table 7.5. The heuristic method used here <strong>to</strong> compute the<br />
matrix-vec<strong>to</strong>r products is the least-increments method and the target selection of the<br />
iterative solvers is chosen such that the smallest real eigenvalues are computed first.<br />
Table 7.5: Settings for JD and JDQZ<br />
JD<br />
JDQZ<br />
# Eigenvalues : 1 # Eigenvalues : 1<br />
Tolerance : 5 × 10 −8 · (2d − 1) n Tolerance : 5 × 10 −8 · (2d − 1) n<br />
Imag. threshold : 1 × 10 −8 · (2d − 1) n Imag. threshold : 1 × 10 −8 · (2d − 1) n<br />
Max # iterations : 1000 Max # iterations : 1000<br />
Min dimension : 0.5 · (2d − 1) n Min dimension : 0.5 · (2d − 1) n<br />
Max dimension : 0.7 · (2d − 1) n Max dimension : 0.7 · (2d − 1) n<br />
Start vec<strong>to</strong>r : Random Start vec<strong>to</strong>r : Random<br />
Preconditioning : None Preconditioning : None<br />
Extraction : Refined Schur Decomposition<br />
: No<br />
Expansion : JD Conjugate pairs : No<br />
Linear Solver : GMRES Linear solver : GMRES<br />
Fix target : 0.01 Test space : 3<br />
Krylov space : Yes Lin solv <strong>to</strong>l : 0.7, 0.49<br />
Max # LS it. : 10 Max # LS it. : 15<br />
Thick restart : 1 vec<strong>to</strong>r Track : 1.0 × 10 −4<br />
The mean results of the 20 global minima computations of all the polynomials in<br />
the test set are given in Table 7.6. This table shows for JD and JDQZ the mean time<br />
and its standard deviation needed <strong>to</strong> compute the smallest real eigenvalue (denoted<br />
by mean ± standard deviation), the mean required number of matrix-vec<strong>to</strong>r product<br />
and its standard deviation, and the error. This error is defined as the mean of the