Fractals/Mathematics/Numerical

'''It will give you a clear visual perception of the gap between mathematics ... (and) your computer calculations. Lynn Wienck'''

= attractive and repelling=

In the terminology of numerical analysis, computation near an attractive fixed point is stable while computation near a repelling fixed point is unstable. Generally speaking, stable computation is trustworthy while unstable computation is not. Mark McClure

= perturbation and aproximation =
 * how solution of the problem is altered for non-zero but small perturbation ( usually denoted as an espilon)
 * problem can not be solved explicitely ( using symbolic methods), only numericla aproximation can be found

=Convergence= " ... methods of acceleration of convergence. Suppose you have a slowly convergent series, and want to know its sum (numerically). Just by summing x_1 + x_2 + ... + x_{1000} + ... x_{1000000} + ... + x_{1000000000} + ... you will get the required accuracy after 100 years. If you fit your x_n to c_2/n^2 + c_3/n^3 + (a few more terms), you will get the same accuracy of the sum in 1 second." Andrey (theoretical high energy physicist)

Above problem you can find in parabolic Julia sets.

" your sequence was generated as ... the output of a fixed point iteration $$x_{i+1} =f(x_i)$$. ... The Levin transformation ... uses forward differences successively to remove error terms of an alternating series."

Examples:
 * GSL library
 * "checking for when the series approximation starts to deviate from the result of running it through the Levin u-transform available in the gnu scientific library. so far in my tests this is taking me right up to the event horizon of what will end up being the lowest iteration, even in locations that used to cause the other methods to bail on the series approximation way sooner, but it also does not seem to be going too far so as to cause glitchy artifacts.  it seems to be just right, across the board, which i find to be rather exciting! " ( quaz0r about Mandelbrot )
 * series calculator

=limitation of native double numbers format=
 * when 2 pixels separated by less than :$$2^{-53}$$
 * when the size of a pixel drops below approx $$10^{-308}$$

=Precision=

Precision in numerical compuiting
 * Floating-point arithmetic Accuracy_problems in wikipedia

How to deal with lack of floating point precision:
 * implement higher precision arithmetic than your hardware natively supports
 * software emulation ( emulating a double with two floats, fixed points numbers, ...)
 * use algorithms that are more numerically stable
 * use representable numbers

how-many-floating-point-numbers-are-in-the-interval [0,1] ?

Libraries :
 * Arb by Fredrik Johansson

See how arb library can be used for checking and adjusting precision :

How many decimal digits are there in n bits ?
One digit of binary number needs one bit : there are 2 binary digits ( 0 and 1) and bits have 2 states. One digit of decimal number needs approximately 3.4 bits. There are 10 decimal numbers, 3 bits have 8 states which is not enough, 4 bits have 16 states which is too much.

See also: decimal-precision-of-binary-floating-point-numbers by RIck Regan

Rounding

 * "compute with two more significant figures than your ultimate answer
 * Round only after the last step in calculation. Never do further calculations with rounded numbers.
 * for multiplying and dividing find the number of significant digits in each factor. The result will have the smaller number of significant digits.
 * For powers and roots, the answer should have the same number of significant digits as the original"
 * "When you add (or subtract), you keep as many decimal places as there are in the least accurate number.
 * When you multiply (or divide), you keep as many significant digits as there are in the least accurate number."

See
 * gcc -frounding-math option

=Examples of numerical computings=
 * Finding roots of equation

Seed value

 * fractalforums.org: julia-sets-true-shape-and-escape-time

standard images ( without zoom)

 * Roundoff Error
 * Shadowing lemma : that every pseudo-orbit (which one can think of as a numerically computed trajectory with rounding errors on every step) stays uniformly close to some true trajectory

Parameter rays
The Wolf Jung test : The external parameter rays for angles (in turns) Angles differ by about $$10^{-15}$$, but the landing points of the corresponding parameter rays are about 0.035 apart.
 * 1/7 (period 3)
 * 321685687669320/2251799813685247 (period 51)
 * 321685687669322/2251799813685247 ( period 51 )

angle precision
For rotational number ( internal angle) 1/34 ray for external angle :

$$t_a =\frac{2^{33}}{2^{34}-1} =\frac{8589934592}{17179869183} = 0.5000000000291038 $$

lands on the alfa fixed point :

$$z_a = 0.491486549841951 +0.091874758908285i $$

It is not a ray for angle :

$$t_b =\frac{1}{2} = 0.5 $$

which land on the point :

$$z_b = -0.508513450158049 +0.091874758908285i$$

Difference between external angles of the rays is :

$$dt = t_b - t_a =-0.0000000000291038 $$

and between landing points of the rays points is : /* Maxima CAS code */ (%i1) za:0.491486549841951 +0.091874758908285*%i; (%o1)             0.091874758908285 %i + 0.491486549841951 (%i2) zb:-0.508513450158049 +0.091874758908285*%i; (%o2)             0.091874758908285 %i - 0.508513450158049 (%i3) abs(za-zb); (%o3)                                1.0

Storing the angle as an exact rational (e.g. mpq_t using libgmp), allows it to be accurate for more than 53 iterations (the number of bits of accuracy of double precision floating point). Convert to double only when needing to do sin and cos for finding the target point. Double is plenty accurate for target point. ( 	Claude Heiland-Allen	)

Escaping test
This test was introduced by by John Milnor. See also analysis by Mark Braverman and roundoff error by Robert P. Munafo Comment by Mark McClure : " an escape time algorithm would take forever to generate that type of image, since the dynamics are so slow there. If you want resolution of 1/100, it would take roughly 2*10^8 iterates to move the point z0=0.01 to z=2 by iterating f(z)=z+z5 "

Here's an orbit computed with 1000 decimal digits, escaping after about 300000 iterations by gerrit

Nonparabolic case
Lets take simple hyperbolic case where parameter c is :

$$c= 0$$

Here repelling fixed point z_f is : $$z_f = 1 $$

Parabolic case
Lets take simple parabolic case where parameter c is :

$$c= \frac{1}{4}$$

Here parabolic fixed point z_f is : $$z_f = \frac{1}{2} $$

Test
Lets take point z of exterior of Julia set but lying near fixed point :

$$distance = 2^{-n}$$ $$z = z_f + distance$$

where n is a positive integer

Check how many iterates i needs point z to reach target set ( = escape) :

$$|z_i| > ER$$

where ER is Escape Radius

Show relationship between :
 * n
 * Last Iteration
 * type of numbers used for computations ( float, double, long double, extended, arbitrary precision )

Programs
See FractalForum for evaldraw script

Results
The results for standard C types ( float, double, long double) and MPFR precision are the same for the same precision

Relation between number of iterations and time of computation in hyperbolic case :

Using MPFR-3.0.0-p8 with GMP-4.3.2 with precision = 128 bits and Escape Radius = 2.000000 n =  1 distance = 5.0000000000e-01 LI =          1 log2(LI) =   0; time =  0 seconds n =  2 distance = 2.5000000000e-01 LI =          2 log2(LI) =   1; time =  0 seconds n =  3 distance = 1.2500000000e-01 LI =          3 log2(LI) =   2; time =  0 seconds n =  4 distance = 6.2500000000e-02 LI =          4 log2(LI) =   2; time =  0 seconds n =  5 distance = 3.1250000000e-02 LI =          5 log2(LI) =   2; time =  0 seconds n =  6 distance = 1.5625000000e-02 LI =          6 log2(LI) =   3; time =  0 seconds n =  7 distance = 7.8125000000e-03 LI =          7 log2(LI) =   3; time =  0 seconds n =  8 distance = 3.9062500000e-03 LI =          8 log2(LI) =   3; time =  0 seconds n =  9 distance = 1.9531250000e-03 LI =          9 log2(LI) =   3; time =  0 seconds n = 10 distance = 9.7656250000e-04 LI =         10 log2(LI) =   3; time =  0 seconds n = 11 distance = 4.8828125000e-04 LI =         11 log2(LI) =   3; time =  0 seconds n = 12 distance = 2.4414062500e-04 LI =         12 log2(LI) =   4; time =  0 seconds n = 13 distance = 1.2207031250e-04 LI =         13 log2(LI) =   4; time =  0 seconds n = 14 distance = 6.1035156250e-05 LI =         14 log2(LI) =   4; time =  0 seconds n = 15 distance = 3.0517578125e-05 LI =         15 log2(LI) =   4; time =  0 seconds n = 16 distance = 1.5258789062e-05 LI =         16 log2(LI) =   4; time =  0 seconds n = 17 distance = 7.6293945312e-06 LI =         17 log2(LI) =   4; time =  0 seconds n = 18 distance = 3.8146972656e-06 LI =         18 log2(LI) =   4; time =  0 seconds n = 19 distance = 1.9073486328e-06 LI =         19 log2(LI) =   4; time =  0 seconds n = 20 distance = 9.5367431641e-07 LI =         20 log2(LI) =   4; time =  0 seconds n = 21 distance = 4.7683715820e-07 LI =         21 log2(LI) =   4; time =  0 seconds n = 22 distance = 2.3841857910e-07 LI =         22 log2(LI) =   4; time =  0 seconds n = 23 distance = 1.1920928955e-07 LI =         23 log2(LI) =   5; time =  0 seconds n = 24 distance = 5.9604644775e-08 LI =         24 log2(LI) =   5; time =  0 seconds n = 25 distance = 2.9802322388e-08 LI =         25 log2(LI) =   5; time =  0 seconds n = 26 distance = 1.4901161194e-08 LI =         26 log2(LI) =   5; time =  0 seconds n = 27 distance = 7.4505805969e-09 LI =         27 log2(LI) =   5; time =  0 seconds n = 28 distance = 3.7252902985e-09 LI =         28 log2(LI) =   5; time =  0 seconds n = 29 distance = 1.8626451492e-09 LI =         29 log2(LI) =   5; time =  0 seconds n = 30 distance = 9.3132257462e-10 LI =         30 log2(LI) =   5; time =  0 seconds n = 31 distance = 4.6566128731e-10 LI =         31 log2(LI) =   5; time =  0 seconds n = 32 distance = 2.3283064365e-10 LI =         32 log2(LI) =   5; time =  0 seconds n = 33 distance = 1.1641532183e-10 LI =         33 log2(LI) =   5; time =  0 seconds n = 34 distance = 5.8207660913e-11 LI =         34 log2(LI) =   5; time =  0 seconds n = 35 distance = 2.9103830457e-11 LI =         35 log2(LI) =   5; time =  0 seconds n = 36 distance = 1.4551915228e-11 LI =         36 log2(LI) =   5; time =  0 seconds n = 37 distance = 7.2759576142e-12 LI =         37 log2(LI) =   5; time =  0 seconds n = 38 distance = 3.6379788071e-12 LI =         38 log2(LI) =   5; time =  0 seconds n = 39 distance = 1.8189894035e-12 LI =         39 log2(LI) =   5; time =  0 seconds n = 40 distance = 9.0949470177e-13 LI =         40 log2(LI) =   5; time =  0 seconds n = 41 distance = 4.5474735089e-13 LI =         41 log2(LI) =   5; time =  0 seconds n = 42 distance = 2.2737367544e-13 LI =         42 log2(LI) =   5; time =  0 seconds n = 43 distance = 1.1368683772e-13 LI =         43 log2(LI) =   5; time =  0 seconds n = 44 distance = 5.6843418861e-14 LI =         44 log2(LI) =   5; time =  0 seconds n = 45 distance = 2.8421709430e-14 LI =         45 log2(LI) =   5; time =  0 seconds n = 46 distance = 1.4210854715e-14 LI =         46 log2(LI) =   6; time =  0 seconds n = 47 distance = 7.1054273576e-15 LI =         47 log2(LI) =   6; time =  0 seconds n = 48 distance = 3.5527136788e-15 LI =         48 log2(LI) =   6; time =  0 seconds n = 49 distance = 1.7763568394e-15 LI =         49 log2(LI) =   6; time =  0 seconds n = 50 distance = 8.8817841970e-16 LI =         50 log2(LI) =   6; time =  0 seconds n = 51 distance = 4.4408920985e-16 LI =         51 log2(LI) =   6; time =  0 seconds n = 52 distance = 2.2204460493e-16 LI =         52 log2(LI) =   6; time =  0 seconds n = 53 distance = 1.1102230246e-16 LI =         53 log2(LI) =   6; time =  0 seconds n = 54 distance = 5.5511151231e-17 LI =         54 log2(LI) =   6; time =  0 seconds n = 55 distance = 2.7755575616e-17 LI =         55 log2(LI) =   6; time =  0 seconds n = 56 distance = 1.3877787808e-17 LI =         56 log2(LI) =   6; time =  0 seconds n = 57 distance = 6.9388939039e-18 LI =         57 log2(LI) =   6; time =  0 seconds n = 58 distance = 3.4694469520e-18 LI =         58 log2(LI) =   6; time =  0 seconds n = 59 distance = 1.7347234760e-18 LI =         59 log2(LI) =   6; time =  0 seconds n = 60 distance = 8.6736173799e-19 LI =         60 log2(LI) =   6; time =  0 seconds n = 61 distance = 4.3368086899e-19 LI =         61 log2(LI) =   6; time =  0 seconds n = 62 distance = 2.1684043450e-19 LI =         62 log2(LI) =   6; time =  0 seconds n = 63 distance = 1.0842021725e-19 LI =         63 log2(LI) =   6; time =  0 seconds n = 64 distance = 5.4210108624e-20 LI =         64 log2(LI) =   6; time =  0 seconds n = 65 distance = 2.7105054312e-20 LI =         65 log2(LI) =   6; time =  0 seconds n = 66 distance = 1.3552527156e-20 LI =         66 log2(LI) =   6; time =  0 seconds n = 67 distance = 6.7762635780e-21 LI =         67 log2(LI) =   6; time =  0 seconds n = 68 distance = 3.3881317890e-21 LI =         68 log2(LI) =   6; time =  0 seconds n = 69 distance = 1.6940658945e-21 LI =         69 log2(LI) =   6; time =  0 seconds n = 70 distance = 8.4703294725e-22 LI =         70 log2(LI) =   6; time =  0 seconds n = 71 distance = 4.2351647363e-22 LI =         71 log2(LI) =   6; time =  0 seconds n = 72 distance = 2.1175823681e-22 LI =         72 log2(LI) =   6; time =  0 seconds n = 73 distance = 1.0587911841e-22 LI =         73 log2(LI) =   6; time =  0 seconds n = 74 distance = 5.2939559203e-23 LI =         74 log2(LI) =   6; time =  0 seconds n = 75 distance = 2.6469779602e-23 LI =         75 log2(LI) =   6; time =  0 seconds n = 76 distance = 1.3234889801e-23 LI =         76 log2(LI) =   6; time =  0 seconds n = 77 distance = 6.6174449004e-24 LI =         77 log2(LI) =   6; time =  0 seconds n = 78 distance = 3.3087224502e-24 LI =         78 log2(LI) =   6; time =  0 seconds n = 79 distance = 1.6543612251e-24 LI =         79 log2(LI) =   6; time =  0 seconds n = 80 distance = 8.2718061255e-25 LI =         80 log2(LI) =   6; time =  0 seconds n = 81 distance = 4.1359030628e-25 LI =         81 log2(LI) =   6; time =  0 seconds n = 82 distance = 2.0679515314e-25 LI =         82 log2(LI) =   6; time =  0 seconds n = 83 distance = 1.0339757657e-25 LI =         83 log2(LI) =   6; time =  0 seconds n = 84 distance = 5.1698788285e-26 LI =         84 log2(LI) =   6; time =  0 seconds n = 85 distance = 2.5849394142e-26 LI =         85 log2(LI) =   6; time =  0 seconds n = 86 distance = 1.2924697071e-26 LI =         86 log2(LI) =   6; time =  0 seconds n = 87 distance = 6.4623485356e-27 LI =         87 log2(LI) =   6; time =  0 seconds n = 88 distance = 3.2311742678e-27 LI =         88 log2(LI) =   6; time =  0 seconds n = 89 distance = 1.6155871339e-27 LI =         89 log2(LI) =   6; time =  0 seconds n = 90 distance = 8.0779356695e-28 LI =         90 log2(LI) =   6; time =  0 seconds n = 91 distance = 4.0389678347e-28 LI =         91 log2(LI) =   7; time =  0 seconds n = 92 distance = 2.0194839174e-28 LI =         92 log2(LI) =   7; time =  0 seconds n = 93 distance = 1.0097419587e-28 LI =         93 log2(LI) =   7; time =  0 seconds n = 94 distance = 5.0487097934e-29 LI =         94 log2(LI) =   7; time =  0 seconds n = 95 distance = 2.5243548967e-29 LI =         95 log2(LI) =   7; time =  0 seconds n = 96 distance = 1.2621774484e-29 LI =         96 log2(LI) =   7; time =  0 seconds n = 97 distance = 6.3108872418e-30 LI =         97 log2(LI) =   7; time =  0 seconds n = 98 distance = 3.1554436209e-30 LI =         98 log2(LI) =   7; time =  0 seconds n = 99 distance = 1.5777218104e-30 LI =         99 log2(LI) =   7; time =  0 seconds n = 100 distance = 7.8886090522e-31 LI =       100 log2(LI) =   7; time =  0 seconds n = 101 distance = 3.9443045261e-31 LI =       101 log2(LI) =   7; time =  0 seconds n = 102 distance = 1.9721522631e-31 LI =       102 log2(LI) =   7; time =  0 seconds n = 103 distance = 9.8607613153e-32 LI =       103 log2(LI) =   7; time =  0 seconds n = 104 distance = 4.9303806576e-32 LI =       104 log2(LI) =   7; time =  0 seconds n = 105 distance = 2.4651903288e-32 LI =       105 log2(LI) =   7; time =  0 seconds n = 106 distance = 1.2325951644e-32 LI =       106 log2(LI) =   7; time =  0 seconds n = 107 distance = 6.1629758220e-33 LI =       107 log2(LI) =   7; time =  0 seconds n = 108 distance = 3.0814879110e-33 LI =       108 log2(LI) =   7; time =  0 seconds n = 109 distance = 1.5407439555e-33 LI =       109 log2(LI) =   7; time =  0 seconds n = 110 distance = 7.7037197775e-34 LI =       110 log2(LI) =   7; time =  0 seconds n = 111 distance = 3.8518598888e-34 LI =       111 log2(LI) =   7; time =  0 seconds n = 112 distance = 1.9259299444e-34 LI =       112 log2(LI) =   7; time =  0 seconds n = 113 distance = 9.6296497219e-35 LI =       113 log2(LI) =   7; time =  0 seconds n = 114 distance = 4.8148248610e-35 LI =       114 log2(LI) =   7; time =  0 seconds n = 115 distance = 2.4074124305e-35 LI =       115 log2(LI) =   7; time =  0 seconds n = 116 distance = 1.2037062152e-35 LI =       116 log2(LI) =   7; time =  0 seconds n = 117 distance = 6.0185310762e-36 LI =       117 log2(LI) =   7; time =  0 seconds n = 118 distance = 3.0092655381e-36 LI =       118 log2(LI) =   7; time =  0 seconds n = 119 distance = 1.5046327691e-36 LI =       119 log2(LI) =   7; time =  0 seconds n = 120 distance = 7.5231638453e-37 LI =       120 log2(LI) =   7; time =  0 seconds n = 121 distance = 3.7615819226e-37 LI =       121 log2(LI) =   7; time =  0 seconds n = 122 distance = 1.8807909613e-37 LI =       122 log2(LI) =   7; time =  0 seconds n = 123 distance = 9.4039548066e-38 LI =       123 log2(LI) =   7; time =  0 seconds n = 124 distance = 4.7019774033e-38 LI =       124 log2(LI) =   7; time =  0 seconds n = 125 distance = 2.3509887016e-38 LI =       125 log2(LI) =   7; time =  0 seconds n = 126 distance = 1.1754943508e-38 LI =       126 log2(LI) =   7; time =  0 seconds n = 127 distance = 5.8774717541e-39 LI =       127 log2(LI) =   7; time =  0 seconds

Parabolic case : Using MPFR-3.0.0-p8 with GMP-4.3.2 with precision = 100 bits and Escape Radius = 2.000000 n =  1 distance = 5.0000000000e-01 LI =           3 log2(LI) =   2; time =     0 seconds n =  2 distance = 2.5000000000e-01 LI =           5 log2(LI) =   2; time =     0 seconds n =  3 distance = 1.2500000000e-01 LI =          10 log2(LI) =   3; time =     0 seconds n =  4 distance = 6.2500000000e-02 LI =          19 log2(LI) =   4; time =     0 seconds n =  5 distance = 3.1250000000e-02 LI =          35 log2(LI) =   5; time =     0 seconds n =  6 distance = 1.5625000000e-02 LI =          68 log2(LI) =   6; time =     0 seconds n =  7 distance = 7.8125000000e-03 LI =         133 log2(LI) =   7; time =     0 seconds n =  8 distance = 3.9062500000e-03 LI =         261 log2(LI) =   8; time =     0 seconds n =  9 distance = 1.9531250000e-03 LI =         518 log2(LI) =   9; time =     0 seconds n = 10 distance = 9.7656250000e-04 LI =        1031 log2(LI) =  10; time =     0 seconds n = 11 distance = 4.8828125000e-04 LI =        2055 log2(LI) =  11; time =     0 seconds n = 12 distance = 2.4414062500e-04 LI =        4104 log2(LI) =  12; time =     0 seconds n = 13 distance = 1.2207031250e-04 LI =        8201 log2(LI) =  13; time =     0 seconds n = 14 distance = 6.1035156250e-05 LI =       16394 log2(LI) =  14; time =     0 seconds n = 15 distance = 3.0517578125e-05 LI =       32778 log2(LI) =  15; time =     0 seconds n = 16 distance = 1.5258789062e-05 LI =       65547 log2(LI) =  16; time =     0 seconds n = 17 distance = 7.6293945312e-06 LI =      131084 log2(LI) =  17; time =     0 seconds n = 18 distance = 3.8146972656e-06 LI =      262156 log2(LI) =  18; time =     0 seconds n = 19 distance = 1.9073486328e-06 LI =      524301 log2(LI) =  19; time =     0 seconds n = 20 distance = 9.5367431641e-07 LI =     1048590 log2(LI) =  20; time =     1 seconds n = 21 distance = 4.7683715820e-07 LI =     2097166 log2(LI) =  21; time =     0 seconds n = 22 distance = 2.3841857910e-07 LI =     4194319 log2(LI) =  22; time =     2 seconds n = 23 distance = 1.1920928955e-07 LI =     8388624 log2(LI) =  23; time =     2 seconds n = 24 distance = 5.9604644775e-08 LI =    16777232 log2(LI) =  24; time =     6 seconds n = 25 distance = 2.9802322388e-08 LI =    33554449 log2(LI) =  25; time =    11 seconds n = 26 distance = 1.4901161194e-08 LI =    67108882 log2(LI) =  26; time =    21 seconds n = 27 distance = 7.4505805969e-09 LI =   134217747 log2(LI) =  27; time =    42 seconds n = 28 distance = 3.7252902985e-09 LI =   268435475 log2(LI) =  28; time =    87 seconds n = 29 distance = 1.8626451492e-09 LI =   536870932 log2(LI) =  29; time =   175 seconds n = 30 distance = 9.3132257462e-10 LI =  1073741845 log2(LI) =  30; time =   351 seconds n = 31 distance = 4.6566128731e-10 LI =  2147483669 log2(LI) =  31; time =   698 seconds n = 32 distance = 2.3283064365e-10 LI =  4294967318 log2(LI) =  32; time =  1386 seconds n = 33 distance = 1.1641532183e-10 LI =  8589934615 log2(LI) =  33; time =  2714 seconds n = 34 distance = 5.8207660913e-11 LI = 17179869207 log2(LI) =  34; time =  5595 seconds n = 35 distance = 2.9103830457e-11 LI = 34359738392 log2(LI) =  35; time = 11175 seconds n = 36 distance = 1.4551915228e-11 LI = 68719476762 log2(LI) =  36; time = 22081 seconds

Analysis
Maximal n in hyperbolic case $$n = n_h $$ is almost the same as the precision of the significand

$$ n_h = precision - 1 $$

In parabolic case maximal $$n =  n_p $$ is

$$ n_p = \frac{precision}{2} $$

Last Iteration ( escape time = iteration fro which abs(zn) > ER ) is : in hyperbolic case equal to n : $$ LI_h = n $$

in parabolic case equal to 2^n :

$$ LI _p = 2^n $$

Time of computations is proportional to number of iterations. In hyperbolic case is is short. In parabolic case grows quickly as number of iterations.

$$ time [seconds] = 6 * 2^{n-24} $$

Checking one point if escapes in parabolic case :
 * for n = 34 take about one hour ( 5 595 seconds )
 * for n = 40 take about one day
 * for n = 45 take about one month
 * for n = 50 take about one year

Why programs fails ?
Cancellation of significant digits and loss of significance (LOS).

The program fails because of limited precision of used number types. Addition of big (zp) and small number (distance) gives number which has more decimal digits then can be saved ( floating point type has only 7 decimal digits). Some of the most right digits are cancelled and iteration goes into an infinite loop.

For example : when using floating point in parabolic case lets take

so

It is greater then machine epsilon:

so this addition still works :

After multiplication it gives :

next step is addition. Because floating point format saves only 7 decimal digits it is truncated to :

Here relative error is to big and is smaller then FLT_EPSILON/2.0 = 0.0000000596;

Solution : increase precision !

Explanation in polish

Why parabolic dynamics is so weak ?
Parabolic dynamics
 * numerical problems

Distance estimation
Example

Zoom

 * manipulating numbers below $$10^{-308}$$ in double format shall be avoided.

What precision do I need for zoom ?
 * Pixel density
 * Pixel spacing is a distance between the centers of each two-dimensional pixel

One can check it using such program ( automatic math precision ) :

Tent map
Numerical error in computing orbit of the tent map with parameter m = 2. Aftere 50 iterations of double numbers all orbits fall into zero.

Result: i =  0 	 x = 0.1720333817284710 i =  1 	 x = 0.3440667634569419 i =  2 	 x = 0.6881335269138839 i =  3 	 x = 0.6237329461722323 i =  4 	 x = 0.7525341076555354 i =  5 	 x = 0.4949317846889292 i =  6 	 x = 0.9898635693778584 i =  7 	 x = 0.0202728612442833 i =  8 	 x = 0.0405457224885666 i =  9 	 x = 0.0810914449771332 i = 10 	 x = 0.1621828899542663 i = 11 	 x = 0.3243657799085327 i = 12 	 x = 0.6487315598170653 i = 13 	 x = 0.7025368803658694 i = 14 	 x = 0.5949262392682613 i = 15 	 x = 0.8101475214634775 i = 16 	 x = 0.3797049570730451 i = 17 	 x = 0.7594099141460902 i = 18 	 x = 0.4811801717078197 i = 19 	 x = 0.9623603434156394 i = 20 	 x = 0.0752793131687213 i = 21 	 x = 0.1505586263374425 i = 22 	 x = 0.3011172526748851 i = 23 	 x = 0.6022345053497702 i = 24 	 x = 0.7955309893004596 i = 25 	 x = 0.4089380213990808 i = 26 	 x = 0.8178760427981615 i = 27 	 x = 0.3642479144036770 i = 28 	 x = 0.7284958288073540 i = 29 	 x = 0.5430083423852921 i = 30 	 x = 0.9139833152294159 i = 31 	 x = 0.1720333695411682 i = 32 	 x = 0.3440667390823364 i = 33 	 x = 0.6881334781646729 i = 34 	 x = 0.6237330436706543 i = 35 	 x = 0.7525339126586914 i = 36 	 x = 0.4949321746826172 i = 37 	 x = 0.9898643493652344 i = 38 	 x = 0.0202713012695312 i = 39 	 x = 0.0405426025390625 i = 40 	 x = 0.0810852050781250 i = 41 	 x = 0.1621704101562500 i = 42 	 x = 0.3243408203125000 i = 43 	 x = 0.6486816406250000 i = 44 	 x = 0.7026367187500000 i = 45 	 x = 0.5947265625000000 i = 46 	 x = 0.8105468750000000 i = 47 	 x = 0.3789062500000000 i = 48 	 x = 0.7578125000000000 i = 49 	 x = 0.4843750000000000 i = 50 	 x = 0.9687500000000000 i = 51 	 x = 0.0625000000000000 i = 52 	 x = 0.1250000000000000 i = 53 	 x = 0.2500000000000000 i = 54 	 x = 0.5000000000000000 i = 55 	 x = 1.0000000000000000 i = 56 	 x = 0.0000000000000000 i = 57 	 x = 0.0000000000000000 i = 58 	 x = 0.0000000000000000 i = 59 	 x = 0.0000000000000000 i = 60 	 x = 0.0000000000000000 i = 61 	 x = 0.0000000000000000 i = 62 	 x = 0.0000000000000000 i = 63 	 x = 0.0000000000000000 i = 64 	 x = 0.0000000000000000 i = 65 	 x = 0.0000000000000000 i = 66 	 x = 0.0000000000000000 i = 67 	 x = 0.0000000000000000 i = 68 	 x = 0.0000000000000000 i = 69 	 x = 0.0000000000000000 i = 70 	 x = 0.0000000000000000 i = 71 	 x = 0.0000000000000000 i = 72 	 x = 0.0000000000000000 i = 73 	 x = 0.0000000000000000 i = 74 	 x = 0.0000000000000000 i = 75 	 x = 0.0000000000000000 i = 76 	 x = 0.0000000000000000 i = 77 	 x = 0.0000000000000000 i = 78 	 x = 0.0000000000000000 i = 79 	 x = 0.0000000000000000 i = 80 	 x = 0.0000000000000000 i = 81 	 x = 0.0000000000000000 i = 82 	 x = 0.0000000000000000 i = 83 	 x = 0.0000000000000000 i = 84 	 x = 0.0000000000000000 i = 85 	 x = 0.0000000000000000 i = 86 	 x = 0.0000000000000000 i = 87 	 x = 0.0000000000000000 i = 88 	 x = 0.0000000000000000 i = 89 	 x = 0.0000000000000000 i = 90 	 x = 0.0000000000000000 i = 91 	 x = 0.0000000000000000 i = 92 	 x = 0.0000000000000000 i = 93 	 x = 0.0000000000000000 i = 94 	 x = 0.0000000000000000 i = 95 	 x = 0.0000000000000000 i = 96 	 x = 0.0000000000000000 i = 97 	 x = 0.0000000000000000 i = 98 	 x = 0.0000000000000000 i = 99 	 x = 0.0000000000000000

=See also=
 * A few notes on computation by Mark McClure
 * The Numerical Tours of Data Sciences, by Gabriel Peyré, gather Matlab, Python, Julia and R experiments to explore modern mathematical data sciences
 * Numerical Errors in Logistic Map Calculation
 * Keisan Online Calculator
 * Finite arithmetic and error analysis in python by Gonzalo Galiano Casas and Esperanza García Gonzalo
 * math.stackexchange question: is-there-an-equation-for-the-number-of-iterations-required-to-escape-the-mandelb ?

=References=
 * Do Numerical Orbits of Chaotic Dynamical Processes Represent True Orbits?