Cantorian Fractal Patterns, Quantum-Like Chaos and Prime Numbers in Atmospheric Flows
Transcript of Cantorian Fractal Patterns, Quantum-Like Chaos and Prime Numbers in Atmospheric Flows
2/13/2015 CANTORIAN FRACTAL PATTERNS, QUANTUMLIKE CHAOS AND PRIME NUMBERS IN ATMOSPHERIC FLOWS.
http://arxiv.org/html/chaodyn/9810011v1 1/15
arXiv:chaodyn/9810011v1 9 Oct 1998
Cantorian Fractal Patterns, QuantumLike Chaos and Prime Numbers in AtmosphericFlows
A.M. Selvam and Suvarna Fadnavis
Indian Institute of Tropical Meteorology,
Dr. Homi Bhabha Road, Pashan, Pune, 411 008, India
Email: [email protected]
Website: http://www.geocities.com/CapeCanaveral/Lab/5833
Telephone: 0910212330846
Fax: : 0910212347825
ABSTRACT
Atmospheric flows exhibit cantorian fractal spacetime fluctuations signifying longrangespatiotemporal correlations. A recently developed cell dynamical system model shows thatsuch nonlocal connections are intrinsic to quantumlike chaos governing flow dynamics. Thedynamical evolution of fractal structures can be quantified in terms of ordered energy flowdescribed by mathematical functions which occur in the field of number theory. Thequantumlike chaos in atmospheric flows can be quantified in terms of the followingmathematical functions / concepts: (1) The fractal structure of the flow pattern is resolvedinto an overall logarithmic spiral trajectory with the quasiperiodic Penrose tiling pattern forthe internal structure and is equivalent to a hierarchy of vortices. The incorporation ofFibonacci mathematical series, representative of ramified bifurcations, indicates orderedgrowth of fractal patterns. (2) The steady state emergence of progressively larger fractal
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structures incorporates unique primary perturbation domains of progressively increasingnumber equal to z/lnz where z, the length step growth stage is equal to the length scale ratioof large eddy to turbulent eddy. In number theory z/lnz gives the number of primes less thanz. The model also predicts that z/lnz represents the normalised cumulative variancespectrum of the eddies and which follows statistical normal distribution. The important resultof the study is that the prime number spectrum is the same as the eddy energy spectrum forquantumlike chaos in atmospheric flows.
1. INTRODUCTION
Recent studies indicate a close association between number theory in mathematics, inparticular, the distribution of prime numbers and the chaotic orbits of excited quantumsystems such as the hydrogen atom [1]. Mathematical studies indicate that cantorian fractalspacetime characterises quantum systems[2 to 4]. A recently developed cell dynamicalsystem model shows that cantorian fractal spacetime is associated with quantumlike chaosin atmospheric flows.
The dynamical evolution of fractal structures can be quantified in terms of ordered energyflow described by mathematical functions which occur in the field of number theory. Thequantumlike chaos in atmospheric flows can be quantified in terms of the followingmathematical functions / concepts: (a) The fractal structure of the flow pattern is resolvedinto an overall logarithmic spiral trajectory with the quasiperiodic Penrose tiling pattern forthe internal structure and is equivalent to a hierarchy of vortices. The incorporation ofFibonacci mathematical series, representative of ramified bifurcations, indicates orderedgrowth of fractal patterns. (b) The steady state emergence of progressively larger fractalstructures incorporates unique primary perturbation domains of progressively increasingnumber equal to z/lnz where z, the length step growth stage is equal to the length scale ratioof large eddy to turbulent eddy. In number theory [5] z/lnz gives the number of primes lessthan z. The model also predicts that z/lnz represents the normalised cumulative variancespectrum of the eddies and which follows statistical normal distribution. The important resultof the study is that the prime number spectrum is the same as the eddy energy spectrum forquantumlike chaos in atmospheric flows.
2. MODEL CONCEPTS
Based on Townsend�s [6] concept that large eddies are envelopes of enclosed turbulenteddy circulations, the relationship between root mean square (r.m.s.) circulation speeds Wand w* respectively of large and turbulent eddies of respective radii R and r is given as
(1)
In number field domain, the above equation can be visualized as follows. The r.m.s.
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circulation speeds W and w* are equivalent to units of computations of respective yardsticklengths R and r. Spatial integration of w* units of yardstick length r, i.e. a computationaldomain w*r, results in a larger computational domain WR [7]. The computed domain WR islarger than the primary domain w*r because of uncertainty in the length measurement usinga finite yardstick length r, which should be infinitely small in an ideal measurement. Theabove visualization will help apply concepts developed for atmospheric flow dynamics toevolution of structures in number field such as the distribution of prime numbers, asexplained in the following.
Fractal structures emerge in atmospheric flows because of mixing of environmental air intothe large eddy volume by inherent turbulent eddy fluctuations. The steady state emergenceof fractal structures A is equal to [8,9]
The spatial integration of enclosed turbulent eddy circulations as given in Equation.(1)represents an overall logarithmic spiral flow trajectory with the quasiperiodic Penrose tilingpattern for the internal structure [8,9] and is equivalent to a hierarchy of vortices. Theincorporation of Fibonacci mathematical series, representative of ramified bifurcationsindicates ordered growth of fractal patterns and signifies nonlocal connectionscharacteristics of quantumlike chaos. Further, the means of ensembles of successivelylarger number field domains follow a logarithmic spiral trajectory with the quasiperiodicPenrose tiling pattern for the internal structure.
The logarithmic flow structure is given by the relation.
(2)
where z is equal to the length scale ratio R/r and k is equal to the steady state fractionalvolume dilution of large eddy by turbulent eddy fluctuations and is given as
(3)
The steady state emergence of fractal structure A is
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(4)
The outward and upward growing large eddy carries only a fraction f of the primaryperturbation equal to
since the fractional outward mass flux of primary perturbation equal to W/w* occurs in thefractional turbulent eddy cross section r/R.
from equation (2)
from equation (3)
from equation (1)
Therefore
from equation (4)
In atmospheric flows the fraction equal to f of surface air is transported upward to level z andrepresents the upward transport of moisture which condenses as liquid water content inclouds, and also aerosols of surface origin. The observed vertical profile of liquid watercontent inside clouds is found to follow the f distribution [10]. The vertical profile of aerosolconcentration in the atmosphere also follows the f distribution [11]. The fraction f carries theunique signature of surface air (primary perturbation) at the level z.
Therefore the ratio P equal to A/f gives the number of units of the unique domain of surfaceair at level z.
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(6)
In number theory, z/lnz represents the number of primes less than z. Prime numbers areunique numbers, i.e. which cannot be factorized [5].
In the quantumlike chaos in atmospheric flows z/lnz represents the variance spectrum ofthe fractal structures as shown below.
The length scale ratio z equal to R/r represents the relative variance (1). The relative upwardmass flux of primary perturbation equal to W/w* is proportional to lnz (2). Therefore z/lnzrepresents the cumulative variance normalized to upward flow of primary perturbation. Thecumulative variance or energy spectrum of the eddies is therefore represented by z/lnzdistribution.
By concept (1) large eddies are but the integrated mean of inherent turbulent eddies andtherefore the eddy energy spectrum follows statistical normal distribution according to theCentral Limit Theorem. The prime number spectrum which is equivalent to the variance(energy) spectrum of eddies follows normal distribution. Earlier studies using variousmeteorological data sets have shown that atmospheric eddy energy spectrum followstatistical normal distribution [12]. The values of z/lnz which give the number of primes lessthan z. also follow statistical normal distribution as described in the following. The number ofprimes P less than z are calculated for a range of n values from x1=z1 to xn=zn . Thecumulative percentage number of primes PC is calculated as equal to (Pm / Pn )*100 wherem=1,2,...n for each class interval X=(xm+xm+1)/2. The number of primes Pt = Pm+1 Pm ineach class interval X is also calculated. The normalized standard deviate t is then equal to(Xbar X)/ where Xbar is the mean of the prime number distribution. The correspondingstandard deviation of the X versus Pt distribution is then calculated as equal to .
A representative computation is shown in Table 1.
Figs. 1 to 3 show representative samples of the z spectrum for three different ranges of zvalues. The statistical normal distribution is also plotted in the Fig.s 1 to 3. It is seen that thez spectrum closely follows normal distribution.
3. CONCLUSION
In mathematics cantorian fractal spacetime is now associated with reference to quantumsystems [2 to 4,13]. Recent studies indicate a close association between number theory inmathematics, in particular, the distribution of prime numbers and the chaotic orbits of excitedquantum systems such as the hydrogen atom [1]. The cell dynamical system modelpresented in this paper shows that quantumlike chaos incorporates prime numberdistribution function in the description of atmospheric flow dynamics.
Acknowledgements
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The authors are grateful to Dr. A. S. R. Murty for his keen interest and encouragementduring the course of the study. The authors are indebted to Professor M. S. El Naschie forinspiration and guidance in this field of study
Thanks are due to Mr .R. D. Nair for typing the manuscript.
REFERENCES
1. Cipra , B., Prime formula weds number theory and quantum physics. Science,1996,274, 20141015.
2. Nottale, L., Fractals and the quantum theory of spacetime. Int'l J. Mod. Phys. A,1989, 4(19) , 50475117.
3. Ord, G. N., Fractal spacetime : a geometric analogue of relativistic quantummechanics .J. Phys .A: Math. Gen. ,1983, 16 , 18691884.
4. El Naschie, M. S., Penrose tiling, semiconduction and cantorian 1/f spectra in fourand five dimensions. Chaos, Solitons and Fractals , 1993, 3(4) , 489491.
5. Stewart, I., From here to infinity. Oxford university press, Oxford, 1996, pp. 299.
6. Townsend, A. A., The Structure of Turbulent Shear Flow. Cambridge UniversityPress, London, U.K. ,1956.
7. Mary Selvam,A., Universal quantification for deterministic chaos in dynamicalsystems. Applied Math. Modelling 1993, 17, 642649.
8. Selvam A. M. and Suvarna Fadnavis, Superstrings, Cantorianfractal Spacetimeand Quantumlike Chaos in Atmosperic flows. Chaos, Solitons and Fractals, 1998 (inPress)
9. Selvam A. M. and Suvarna Fadnavis, Cantorian fractal spacetime, quantumlikechaos and scale relativity in atmospheric flows. Chaos, Solitons and Fractals, 1998. (inPress)
10. Mary Selvam, A. Deterministic chaos, fractals and quantumlike mechanics inatmospheric flows. Can. J. Phys. 1990, 68, 831841.
11. Sikka, P., Mary selvam, A., and Ramachandran Murty, A. S., Possible solarinfluence on atmospheric electric field. Adv. Atmos. Sci., 1988, 2, 218118 .(http://arXiv.org/abs/chaodyn/9806014)
12. Selvam A. M. and Suvarna Fadnavis, Signatures of a universal spectrum foratmospheric interannual variability in some disparate climatic regimes. Meteorologyand Atmospheric Physics , 1998, 66, 87112. (http://arXiv.org/abs/chaodyn/9805028)
13. El Naschie, M. S., Penrose universe and cantorian spacetime as a model fornoncommutative quantum geometry. Chaos, Solitons and Fractals , 1998, 931934.
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Table 1
S.No.
Classintervalmean
Freq.of
primes
Cum.freq. ofprimes
Cum. %freq. ofprimes
t vales Cum.normal
distrib(%)
1 3.5 0.155 0.155 0.815 1.603 5.443
2 4.5 0.221 0.376 1.980 1.568 5.846
3 5.5 0.242 0.618 3.255 1.532 6.273
4 6.5 0.249 0.867 4.565 1.497 6.722
5 7.5 0.250 1.116 5.881 1.461 7.194
6 8.5 0.249 1.365 7.192 1.426 7.701
7 9.5 0.247 1.612 8.493 1.390 8.228
8 10.5 0.244 1.857 9.780 1.355 8.777
9 11.5 0.242 2.098 11.054 1.319 9.356
10 12.5 0.239 2.338 12.314 1.283 9.967
11 13.5 0.237 2.574 13.560 1.248 10.607
12 14.5 0.234 2.808 14.793 1.212 11.264
13 15.5 0.232 3.040 16.014 1.177 11.963
14 16.5 0.229 3.270 17.223 1.141 12.683
15 17.5 0.227 3.497 18.420 1.106 13.443
16 18.5 0.225 3.722 19.607 1.070 14.225
17 19.5 0.223 3.945 20.783 1.035 15.042
18 20.5 0.221 4.167 21.950 0.999 15.890
19 21.5 0.220 4.387 23.107 0.964 16.760
20 22.5 0.218 4.605 24.255 0.928 17.670
21 23.5 0.216 4.821 25.395 0.893 18.604
22 24.5 0.215 5.036 26.527 0.857 19.574
23 25.5 0.213 5.249 27.652 0.821 20.569
24 26.5 0.212 5.461 28.769 0.786 21.599
25 27.5 0.211 5.672 29.878 0.750 22.649
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26 28.5 0.209 5.882 30.982 0.715 23.735
27 29.5 0.208 6.090 32.078 0.679 24.843
28 30.5 0.207 6.297 33.168 0.644 25.986
29 31.5 0.206 6.503 34.253 0.608 27.149
30 32.5 0.205 6.707 35.331 0.573 28.342
31 33.5 0.204 6.911 36.404 0.537 29.561
32 34.5 0.203 7.114 37.472 0.502 30.795
33 35.5 0.202 7.315 38.534 0.466 32.063
34 36.5 0.201 7.516 39.591 0.430 33.342
35 37.5 0.200 7.716 40.644 0.395 34.647
36 38.5 0.199 7.915 41.691 0.359 35.962
37 39.5 0.198 8.113 42.734 0.324 37.303
38 40.5 0.197 8.310 43.773 0.288 38.654
39 41.5 0.196 8.506 44.807 0.253 40.021
40 42.5 0.196 8.702 45.838 0.217 41.397
41 43.5 0.195 8.897 46.864 0.182 42.792
42 44.5 0.194 9.091 47.886 0.146 44.190
43 45.5 0.193 9.284 48.904 0.111 45.595
44 46.5 0.193 9.477 49.919 0.075 47.007
45 47.5 0.192 9.669 50.930 0.040 48.419
46 48.5 0.191 9.860 51.937 0.004 49.840
47 49.5 0.191 10.050 52.941 0.032 51.262
48 50.5 0.190 10.240 53.942 0.067 52.674
49 51.5 0.189 10.430 54.939 0.103 54.085
Table 1 (continued)
50 52.5 0.189 10.618 55.934 0.138 55.497
51 53.5 0.188 10.807 56.925 0.174 56.895
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52 54.5 0.188 10.994 57.913 0.209 58.291
53 55.5 0.187 11.181 58.898 0.245 59.667
54 56.5 0.186 11.368 59.880 0.280 61.043
55 57.5 0.186 11.553 60.859 0.316 62.394
56 58.5 0.185 11.739 61.835 0.351 63.734
57 59.5 0.185 11.924 62.809 0.387 65.058
58 60.5 0.184 12.108 63.780 0.423 66.370
59 61.5 0.184 12.292 64.748 0.458 67.650
60 62.5 0.183 12.475 65.714 0.494 68.919
61 63.5 0.183 12.658 66.677 0.529 70.160
62 64.5 0.182 12.840 67.638 0.565 71.389
63 65.5 0.182 13.022 68.597 0.600 72.587
64 66.5 0.181 13.204 69.553 0.636 73.754
65 67.5 0.181 13.385 70.506 0.671 74.902
66 68.5 0.181 13.566 71.458 0.707 76.019
67 69.5 0.180 13.746 72.407 0.742 77.111
68 70.5 0.180 13.925 73.354 0.778 78.170
69 71.5 0.179 14.105 74.298 0.813 79.201
70 72.5 0.179 14.284 75.241 0.849 80.203
71 73.5 0.179 14.462 76.182 0.885 81.183
72 74.5 0.178 14.640 77.120 0.920 82.122
73 75.5 0.178 14.818 78.057 0.956 83.036
74 76.5 0.177 14.996 78.991 0.991 83.918
75 77.5 0.177 15.173 79.924 1.027 84.771
76 78.5 0.177 15.349 80.854 1.062 85.592
77 79.5 0.176 15.526 81.783 1.098 86.382
78 80.5 0.176 15.702 82.710 1.133 87.150
79 81.5 0.176 15.877 83.635 1.169 87.878
80 82.5 0.175 16.052 84.558 1.204 88.578
81 83.5 0.175 16.227 85.479 1.240 89.249
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82 84.5 0.175 16.402 86.399 1.276 89.894
83 85.5 0.174 16.576 87.317 1.311 90.508
84 86.5 0.174 16.750 88.233 1.347 91.095
85 87.5 0.174 16.924 89.148 1.382 91.652
86 88.5 0.173 17.097 90.061 1.418 92.185
87 89.5 0.173 17.270 90.972 1.453 92.695
88 90.5 0.173 17.443 91.882 1.489 93.174
89 91.5 0.172 17.615 92.790 1.524 93.626
90 92.5 0.172 17.787 93.696 1.560 94.058
91 93.5 0.172 17.959 94.601 1.595 94.469
92 94.5 0.172 18.131 95.505 1.631 94.850
93 95.5 0.171 18.302 96.407 1.666 95.215
94 96.5 0.171 18.473 97.307 1.702 95.560
95 97.5 0.171 18.643 98.206 1.738 95.888
96 98.5 0.170 18.814 99.104 1.773 96.188
97 99.5 0.170 18.984 100.000 1.809 96.479
Mean of prime number distribution = 48.612
Standard deviation = 28.136
Legend
Fig. 1. Association between prime number distribution and statistical normaldistribution for primes up to 3 to 100.
Fig. 2. Same as Fig. 1. for primes up to 3 to 1000.
Fig. 3. Same as Fig. 1. for primes up to 1500 to 2000.
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Fig.1
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Fig.2
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