The National Student Research Center

E-Journal of Student Research: Math

Volume 6, Number 1, September, 1999


The National Student Research Center is dedicated to promoting student research and the use of the scientific method in all subject areas across the curriculum, especially science and math.

For more information contact:

John I. Swang, Ph.D.
Founder/Director
National Student Research Center
2024 Livingston Street
Mandeville, Louisiana 70448
U.S.A.
E-Mail: nsrcmms@communique.net
http://youth.net/nsrc/nsrc.html



TABLE OF CONTENTS

  1. Fractals - The Effects of Changes in the Complex Number C In Julia Set Fractals.

 

TITLE:  Fractals - The Effects of Changes in the Complex
        Number C In Julia Set Fractals.

STUDENT RESEARCHER:  Iain Hunt
SCHOOL ADDRESS:  Del Norte High School 
                 Del Norte, Colorado, 81132
GRADE:  11
TEACHER:  Laura Stuemky


I.  STATEMENT OF PURPOSE AND HYPOTHESIS:

In my experiment, I explored the effects of changing the real 
part of c in Julia Set fractals representing the equation 
f(z)=z^2+c.  I predicted that fractals with close values for the 
real part of the complex number c would have similar shapes and 
color patterns.

II.  METHODOLOGY:

In my experiment, I originally intended to test a longer series 
of values that would have ranged from -1 to 1.  I planned on 
using numbers that were exact only to one decimal place.  In 
conducting this experiment I found that the numbers were too far 
apart to produce any recognizable pattern.  I then chose two 
imaginary values for c and two sets of real number values.  The 
values I chose were suggested on the website.  I tested two 
different sets as a way of repeating my experiment, in order to 
reduce error in the interpretation of the images.

Other than the value for c, everything in experiment remained 
constant.  All the fractals were generated by the same means: 
the program on the Internet, at the site 
library.advanced.org/3288/myojulia.html.  I tested only Julia 
Set fractals representing the equation f(z)=z^2+c.  The starting 
value for z was always 0+0i.  I always used the red/green/blue 
color palette, and the magnification factor always remained at 
1.

Procedure

1. Get on the Internet and go to 
library.advanced.org/3288/myojulia.html.
2. Enter .097i as the value for the imaginary part of c.
3. Enter -.750 as the value for the real part of c.  Click the 
finish button.
4. Save the picture of the fractal for future analysis.
5. Repeat steps 3 and 4 with the same value for the imaginary 
part of c and -.749, -.748, -.747, -.746, -.745, -.744, -.743, -
.742, and -.741.
6. Repeat the experiment with .043i as the imaginary part of c 
and .320, .321, .322, .323, .324, .325, .326, .327, .328, and 
.329 as the values for the real part of c.
7. Analyze the fractals.  Look for patterns in the shapes and 
colors of the fractals.

III.  ANALYSIS OF DATA:

The only data in my experiment is included on a separate page.  
These are the resultant fractal images from my investigation.

IV.  SUMMARY AND CONCLUSION:

In my experimentation I found that all the fractals with close c 
values had similar shapes.  The basic shapes of these fractals 
were nearly identical.  This supports the first part of my 
hypothesis, where I predicted that fractals with close c values 
would have similar shapes.  I also found that the color patterns 
weren't near as similar.  With a difference of .001 in the real 
part of the c value, the color patterns were similar.  However, 
with a difference of .009, the color patterns seemed to have no 
similarity whatsoever.  From this I conclude that there is 
greater and more rapid change in the color patterns of fractals 
than in the shapes of fractals.  The second part of my 
hypothesis, where I predicted that fractals with close c values 
would have similar color patterns, was somewhat correct, 
although not correct to the extent of the first one.

V.  APPLICATION:

The science of fractals is still a young one, so at this point 
applications for fractals haven't been fully developed, although 
there is potential in fields such as fluid dynamics.  Fractals 
can be used to model complex systems, such as the stock market, 
population trends, or weather patterns.  These models could 
possibly lead to a greater understanding of the stock market and 
more accurate weather forecasting.  There is potential for 
fractals in most, if not all non-linear systems.