Dataset: The Chaotic Butterfly

About this Dataset

The Chaotic Butterfly

Chaos Theory, the Butterfly Effect and the Mandelbrot Set.

Chaos Theory.

This is the study of systems that are sensitive to initial conditions. It suggests that small changes in the initial state of a system can lead to drastically different outcomes. This is commonly referred to as the butterfly effect.
It's about systems that appear random or disorderly but are governed by underlying patterns and deterministic (predictable) laws. The catch is that these systems are so sensitive, that tiny changes in initial conditions can lead to drastically different outcomes.

The double pendulum is a classic example of chaos theory. Chaos theory is a branch of mathematics and physics that studies the behaviour of dynamical systems that are highly sensitive to initial conditions. These systems are often unpredictable over long time periods, even when the initial conditions are known exactly.
The double pendulum is a chaotic system because its motion is strongly influenced by the initial conditions. For example, if you release two double pendulums from slightly different initial conditions, their trajectories will quickly diverge, even though they are both governed by the same laws of physics.

This sensitivity to initial conditions is known as the butterfly effect. It is a key characteristic of chaotic systems.
One of the most famous examples of a simple system that exhibits chaotic behaviour is the Logistic Map. It's a mathematical model often used to describe population dynamics, but its behaviour can be quite chaotic under certain conditions.

The Logistic Map.

The Logistic Map is defined by the recurrence relation:

Where:

xn is a number between 0 and 1, representing the ratio of the existing population to the maximum possible population.
r is a positive number representing the growth rate.

Let's explore this equation:

When r = 2,
with x0 = 0.5 (i.e., half the maximum population), the sequence will settle into a steady value.
When r = 3.1,
with x0 = 0.5, the sequence does not settle but oscillates between two values.
When r = 3.5,
with x0 = 0.5, the sequence oscillates among four values.
When r = 3.57,
with x0 = 0.5, the sequence oscillates among eight values.
When r > 3.57 and r < 4 the sequence behaves chaotically.

The Logistic Map sequence generator: A Markdown Document with a code chunk. - link

A spreadsheet with charts showing the Logistic map sequences (from the above csv file generator). - link

Charts from the above spreadsheet:

For r values between 3.57 and 4, the system behaves chaotically, and small changes in the initial value of x0 can also result in vastly different sequences. This sensitivity to initial conditions is a hallmark of chaotic systems.

Explaining the butterfly effect using butterflies and probable scenarios.

Theoretical Framework: The Butterfly Effect and the Butterfly Mating System.

1. Background: Definitions and Context.

Butterfly Effect: Originating from chaos theory, the butterfly effect posits that tiny changes in initial conditions can produce vast differences in outcomes. It's often illustrated with the idea that the flap of a butterfly's wings in one part of the world could initiate a chain of events leading to a tornado in another part.
Butterfly Mating System: In various butterfly species, mating can be influenced by a range of factors, from visual cues to pheromones. While overt aggression isn't common, competition can be subtle, like aerial displays or territorial behaviours. Different species have their unique nuances in mating.

2. Core Assumption: Small Initial Variability in Mating Can Produce Significant Long-term Genetic Outcomes.

Drawing from the essence of the butterfly effect, we assume that seemingly minor variations or events in butterfly mating behaviour can lead to significant genetic changes over multiple generations.

For example:

A single instance of a unique mating choice (like a butterfly choosing a mate outside its usual territory) could introduce a new set of genes into a population.
Over generations, if this new genetic material confers an advantage, it could spread throughout the population, leading to a noticeable shift in genetic composition.

3. Randomisation and Unpredictability.

One of the hallmarks of the butterfly effect is unpredictability. If we consider the butterfly mating system as somewhat randomised or subject to many unpredictable factors, it mirrors the unpredictability in chaos theory.

For example:

Changing environmental factors, such as temperature fluctuations or altered availability of food sources, can impact which butterflies get to mate. These seemingly small changes could alter the genetic trajectory of a butterfly population over time, similar to the butterfly effect's ripple consequences.

4. Broader Implications: Impact on Ecosystems.

If these small changes in mating dynamics lead to broader genetic shifts in butterfly populations, they could also impact the ecosystems they inhabit:

Butterflies play roles as pollinators and prey for other animals. Changes in their population dynamics could influence plant reproduction or predator populations, setting off a cascade of ecological effects.

5. Comparing the Framework with Existing Phenomena.

As seen with the butterfly effect, the Logistic Map is highly sensitive to initial conditions. Similarly, in the butterfly mating context, the initial conditions (mating choices) can set off a chain of genetic and ecological events with far-reaching consequences.

While this framework establishes a parallel between the butterfly mating system and the butterfly effect, it's essential to note that this is a blend of factual information, logical extrapolation, and hypothetical thinking.

The Butterfly Effect and the Mandelbrot Set.

Originating from chaos theory, the Butterfly effect posits that tiny changes in initial conditions can produce vast differences in outcomes.The idea is often illustrated by suggesting that the flap of a butterfly's wings in Brazil can set off a tornado in Texas. The Mandelbrot set is a mathematical set of points in the complex plane, known for its fractal nature and intricate patterns. Both these concepts are related to chaos and complexity.

Mandelbrot Set & Chaos Theory:

Mandelbrot Set: It is a set of complex numbers that, when subjected to repeated iterations of a certain mathematical operation, do not escape to infinity. When visualised, it creates a fascinating and infinitely intricate fractal pattern. link
Chaos Theory: This is the study of systems that are sensitive to initial conditions. It suggests that small changes in the initial state of a system can lead to drastically different outcomes. This is commonly referred to as the Butterfly effect.
Connection: The Mandelbrot Set is a manifestation of chaos in the complex plane. Even slight changes in the initial complex number can determine whether it belongs to the Mandelbrot Set or not, which means it's a great visual representation of sensitive dependence on initial conditions. Both the Mandelbrot set and chaos theory deal with how simple rules can lead to complex behaviours.

A brief bio of Benoit Mandelbrot: A Markdown document - link

The Mandelbrot set: A Markdown Document with a code chunk for a plot in R. - link

The Mandelbrot set, plot output from the above Markdown document.

The Mandelbrot set is determined by iterating the function:

Given a complex number C, initialise Z to 0. For each iteration, update Z to be the result of Z squared plus C.

Infinity is deeply intertwined with the nature and definition of the Mandelbrot set. It's the potential for sequences to grow without bound (to infinity) that determines whether a point is inside or outside the set, and the fractal nature of the set itself implies infinite complexity as one zooms in.

link - To my project about Infinity on Kaggle.

Conclusion:
Our exploration of chaos theory, the butterfly effect, and the Mandelbrot set has shown us that there is order in the midst of chaos. Even though the world may seem unpredictable at times, there are underlying paradigms and rules that govern its behaviour and that mathematics is a powerful tool for understanding the world around us.
Chaos theory teaches us that small changes in the initial conditions of a system can lead to big changes in the long run. This is known as the butterfly effect. The Mandelbrot set is a fractal, which means that it has infinitely complex patterns that repeat themselves at different scales. It is a striking example of how something simple can give rise to something complex.
By studying chaos theory and the Mandelbrot set, we can learn more about the inherent unpredictability and order of dynamic systems. This knowledge can be used to make better predictions and develop new technologies in a variety of fields.

Patrick Ford 🦋

Tables

Logistic Map R 3–1

@kaggle.patricklford_logistic_map.logistic_map_r_3_1

3.06 KB
100 rows
3 columns


CREATE TABLE logistic_map_r_3_1 (
  "r" DOUBLE,
  "n" VARCHAR,
  "n_3_1" VARCHAR
);

Logistic Map R 3–5

@kaggle.patricklford_logistic_map.logistic_map_r_3_5

2.56 KB
100 rows
3 columns


CREATE TABLE logistic_map_r_3_5 (
  "r" DOUBLE,
  "n" VARCHAR,
  "n_3_5" VARCHAR
);

Logistic Map R 3–57

@kaggle.patricklford_logistic_map.logistic_map_r_3_57

3.29 KB
100 rows
3 columns


CREATE TABLE logistic_map_r_3_57 (
  "r" DOUBLE,
  "n" VARCHAR,
  "n_3_57" VARCHAR
);

Logistic Map R 2

@kaggle.patricklford_logistic_map.logistic_map_r_2

2.38 KB
100 rows
3 columns


CREATE TABLE logistic_map_r_2 (
  "r" DOUBLE,
  "n" VARCHAR,
  "n_2" VARCHAR
);

Logistic Map R 3–99

@kaggle.patricklford_logistic_map.logistic_map_r_3_99

3.29 KB
100 rows
3 columns


CREATE TABLE logistic_map_r_3_99 (
  "r" DOUBLE,
  "n" VARCHAR,
  "n_3_99" VARCHAR
);