NATURE IS A CONNECTION OF COMPLEX SYSTEMS, AS IS LIFE.
ALL THINGS ARE DRIVEN BY THEIR CODING PATTERNS.
Connections are the conduits for energy flows. Interdependent connectivity makes each system work in nature and the body. These self-replicating hierarchies drive the ongoing results. Humans need to be mindful not to destroy some of these systems. Remember that nature’s organizing systems are both orderly and chaotic. Complex systems tend to change their states dynamically. As Aristotle said: ” The whole is more than the sum of its parts.”
Complex systems are collective behaviors of their parts. They emerge with properties that can’t be inferred from their parts. The properties of complex systems are very different from the properties of their components. Non-chaotic systems are predictable. Emergence changes things.
Interactions between members of a complex system can produce global behavior patterns on a self-organized basis, without a central or external controller. Distribution happens across components and is integrated by these interactions. These self-organizing systems can create physical/functional structures with dynamic/informational behaviors.
As a system becomes more organized by this process, new interaction patterns emerge that produce greater complexity. These complex systems can self-organize into a new critical state that only exists in a subtle balance between randomness and regularity.
Complex systems are constantly adapting to what is next on the complexity scale. They react to the environment at hand.
Patterns in nature are composed of complicated and connected structures with highly ordered dynamic properties. This complexity results in an emergent behavior or structure that manifests as a mega-form or superorganism. We know the equations in complex systems like turbulence flows, but we will never have the computational power to solve them accurately enough for engineering applications. We can only use shortcuts and approximate solutions.
Forests are an ecological complex system. They have gap-size distribution and dynamic succession results from memory-based, cross-scale planning abilities. Randomness didn’t write the code for this to happen.
All chemistry results from the behavior of electrons that are bound to atomic nuclei. Quantum mechanics determine how electrons are bound to the atomic nuclei. A molecule (a system of two or more atoms bound together) is formed by sharing electrons between the atoms that make up that molecule. Chemistry is the science of predicting which pairs of atoms are capable of forming molecules and what energies and relative positions are needed to create the chemical bond. Also, what does it take to destroy a bond and break the molecule apart? Quantum mechanics rules the sub-chemistry atomic world. Quantum mechanics produces stable inter-atomic bonds that result in molecules. Math shortcuts and approximations are needed to get answers for the complex systems of different atoms interacting together. The complexity of complex systems is beyond our maths and geometry abilities. The properties of the whole often cannot be understood or predicted. As complexity rises, the data complexity goes off the chart.
COMPLEX SYSTEMS IN NATURE ARE TOO COMPLEX FOR US TO FULLY UNDERSTAND (WHEN THERE ARE TOO MANY VARIABLES, HIDDEN OR NOT.)
Mathematical and computational methods are powerful tools to study complex systems until they run out of talent.
Most models are wrong, but some are useful, anyway. Too many variables get in the way.
Math shortcuts and approximations will never crack the creation code. It is embedded in the fundamental level of physics. You can’t trick it up to get there. Hidden pattern system complexity grows to be beyond our ken.
The universe is a deterministic model. Its systems are so complex and chaotic that they seem to be driven by randomness. Chaos happens when the present determines the future. The approximated present, however, does not specify an accurate result. Also, hidden variables and hidden patterns abound as system complicity rises.
Only non-random physical laws can produce order with the appearance of design. Randomness can’t make a deterministic law of nature. Only a Determinator can create a deterministic law of nature.
Deterministic laws of nature with one system variable can be perceptually and mathematically understood. As variables are added, predictability goes away. How many? It depends on the system’s function. This is what chaos is all about. Methods dependent on initial conditions become impossible to predict ahead of time. They might as well be random.
A universe with billions upon trillions upon quadrillions of moving parts and complexities only appears to be random. Add to that, the quantum indeterminacy state of an elementary particle isn’t determined until it interacts with a classical system and its wave function collapses. Randomness can’t begin to handle that.
A deterministic system predicts future sequential behavior. Minor differences in initial conditions result in widely diverging outcomes in dynamical systems. They render long-term predictions of their behavior that are impossible to predict. When emergence happens, the properties of the whole often cannot be understood or anticipated. Diverse mechanisms cause the interaction between system components to generate new information with collective structures and behaviors at larger scales. Chaotic dynamics systems are not the presence of singular points or limit cycles but a large number of various cycles on a complexly folded surface called an attractor.
The deterministic nature of these systems does not make them predictable. They are determined by their initial conditions, with no random elements involved. This behavior is known as deterministic chaos or simply chaos.
Complex systems are constantly adapting to what is next on the complexity scale. They react to the environment at hand. Random behavior is non-deterministic. Chaotic behavior is fully deterministic if the initial state is known. Any initial impression initially grows exponentially.
