k | |||||
5 | -0.99999 | 68 | 86 | 144 | |
6 | -0.999999 | 96 | 114 | 188 | |
7 | -0.9999999 | 128 | 146 | 236 | |
8 | -0.99999999 | 164 | 182 | 288 |
Hénon map is a well-studied classical example of area-contracting maps, modelling dissipative dynamics. The rich phenomena of coexistence of stable islands and their separatrices is typical of area-preserving maps, modelling conservative dynamics. In this paper we use the Hénon map to ascertain that coexistence of sinks is greater and greater approaching the conservative case, and that part of it can be organized following a renormalization argument. Using a numerical continuation that we devised, and called "dribbling method" [
Citation: |
Figure 1.
"Dribbling" a possible singularity at
Figure 3.
Adjustments in renormalization scheme of the saddle node bifurcation value. If Newton's method initialized using linear prediction seems not to converge, adjust initial guess only in one variable
Figure 4.
Blow-up of same error function of Fig. 3 but with
Figure 7.
Stability ranges in the
Figure 9.
Rate of convergence in
Figure 11.
Coexistence of periodic attractors (isolated points), all other points are orbits of a discretized segment: on the unstable manifold (and inside a
Figure 12.
Stability range in
Table 1.
Values of
k | |||||
5 | -0.99999 | 68 | 86 | 144 | |
6 | -0.999999 | 96 | 114 | 188 | |
7 | -0.9999999 | 128 | 146 | 236 | |
8 | -0.99999999 | 164 | 182 | 288 |
Table 2.
Values of
k | |||||
5 | 0.99999 | 20 | 25 | 38 | |
6 | 0.999999 | 25 | 30 | 46 | |
7 | 0.9999999 | 31 | 36 | 55 | |
8 | 0.99999999 | 38 | 43 | 65 |
Table 3.
Coexistence of attractors for
-0.999 | 4 | 0.151600 | 20 - 30 | |
-0.9999 | 9 | 0.098750 | 28 - 46 | |
-0.99999 | 16 | 0.076900 | 30 - 74 | |
-0.999999 | 27 | 0.054900 | 42 - 98 | |
-0.9999999 | 39 | 0.045000 | 46 - 134 | |
-0.99999999 | 54 | 0.035794 | 54 - 166 |
Table 4.
Coexistence of attractors for
0.99999 | 10 | -0.93294 | 11 - 20 | |
0.999999 | 14 | -0.95400 | 12 - 25 | |
0.9999999 | 18 | -0.96490 | 12 - 29 | |
0.99999999 | 23 | -0.97420 | 13 - 35 |
Table 5.
first eigenvalue | accuracy | |||
42 | -0.02471212033 | -0.004353351966 | 0.999666+0.025007 i | 980 |
44 | 0.003893968151 | 0.01400370243 | 0.998106+0.061164 i | 981 |
46 | 0.03287883220 | 0.03630238615 | 0.996571+0.082467 i | 981 |
48 | 0.06028145342 | 0.05973990689 | 0.994655+0.103021 i | 980 |
50 | 0.08552343060 | 0.08300646446 | 0.992221+0.124292 i | 980 |
52 | 0.1082722485 | 0.1051821971 | 0.989124+0.146904 i | 979 |
54 | 0.1283734421 | 0.1256447760 | 0.985195+0.171279 i | 979 |
56 | 0.1458237800 | 0.1440274072 | 0.980218+0.197778 i | 979 |
58 | 0.1607392037 | 0.1601751773 | 0.973924+0.226748 i | 979 |
60 | 0.1733182271 | 0.1740957680 | 0.965971+0.258534 i | 979 |
62 | 0.1838069083 | 0.1859098749 | 0.955930+0.293489 i | 979 |
64 | 0.1924697936 | 0.1958070451 | 0.943258+0.331965 i | 978 |
66 | 0.1995685673 | 0.2040103236 | 0.927268+0.374309 i | 978 |
68 | 0.2053481559 | 0.2107505750 | 0.907097+0.420841 i | 978 |
70 | 0.2100289888 | 0.2162495981 | 0.881651+0.471827 i | 978 |
72 | 0.2138038071 | 0.2207103044 | 0.849555+0.527432 i | 978 |
74 | 0.2168375173 | 0.2243120570 | 0.809070+0.587650 i | 979 |
76 | 0.2192688855 | 0.2272094757 | 0.758004+0.652192 i | 979 |
78 | 0.2212131915 | 0.2295333706 | 0.693593+0.720313 i | 979 |
80 | 0.2227652522 | 0.2313928385 | 0.612348+0.790538 i | 979 |
82 | 0.2240024479 | 0.2328778729 | 0.509870+0.860204 i | 978 |
84 | 0.2249875438 | 0.2340620792 | 0.380610+0.924690 i | 977 |
86 | 0.2257712060 | 0.2350052607 | 0.217565+0.976002 i | 977 |
88 | 0.2263941791 | 0.2357557547 | 0.011907+0.999885 i | 976 |
90 | 0.2268891314 | 0.2363524720 | -0.247504+0.968841 i | 975 |
92 | 0.2272821942 | 0.2368266348 | -0.574717+0.818296 i | 975 |
94 | 0.2275942304 | 0.2372032327 | -0.987457+0.157593 i | 974 |
96 | 0.2278418727 | 0.2375022270 | -0.379187 | 974 |
98 | 0.2280383657 | 0.2377395373 | -0.244788 | 973 |
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