Links, Repetition, and Conditional Branching: Components of Complex Systems
Science has enabled us to rigorously understand a wide range of phenomena by breaking them down into elements and expressing laws through mathematical formulas. Technological advancements based on scientific understanding have enriched society.
However, even today, there are many challenges in science that are difficult to comprehend. One such challenge is the origin of life.
Life is a complex system, and its emergence on Earth has been studied for decades.
As someone with experience as a systems architect, I conduct personal research on the origin of life from a systems architecture perspective. Through this research, I have realized that while current scientific approaches excel at decomposing subjects into material elements and expressing laws through equations and formulas, they struggle with addressing complex systems.
Complex systems are studied in fields like complexity science and systems theory. However, I believe these theories often fail to address the essential components of complex systems accurately.
The key components of complex systems must go beyond material elements and the laws represented by formulas. They should also include links, repetition, and conditional branching.
When we assume that only material elements and laws are the components to analyze, we may overlook or forget to include these additional factors. Consequently, even if all analyzed elements are combined, the whole system cannot be properly understood. However, if we can decompose and analyze these additional components and integrate them, we can achieve a comprehensive understanding of the entire system.
The Origin of Life
To illustrate this, let us outline the origin of life.
The origin of life is explained as a phenomenon known as chemical evolution, where chemical reactions on Earth produced new compounds, which then repeated and diversified. This process eventually led to the integration of these compounds into living organisms.
However, considering the complexity of the chemicals and reactions involved in life, it seems improbable that life emerged purely by chance. Thus, the question becomes: how could chemical evolution have given rise to the extraordinarily complex system of living organisms?
Repetition in the Origin of Life
Repetition is the first crucial element. The key biomolecules that define the mechanisms of life — DNA, RNA, and proteins — are polymers composed of chain-like structures of smaller molecules called monomers. Polymers can be synthesized by repetitively bonding monomers. Since the bonding mechanism remains consistent regardless of the polymer’s length, it is theoretically possible to synthesize extremely long polymers through repeated bonding.
However, the bonds within polymers are susceptible to degradation from ultraviolet rays and heat. The longer a polymer grows, the more bonds it has, and the shorter its viable lifespan becomes. As a result, under natural conditions, it is unlikely for very long polymers, like those found in living organisms, to remain stable.
Conditional Branching in the Origin of Life
Conditional branching becomes significant here. Depending on the arrangement of monomers within a polymer, proteins and RNA exhibit various catalytic abilities. Catalysts enhance the likelihood of specific chemical reactions. Even polymers of the same length can exhibit different catalytic properties based on the sequence of their monomers.
These catalytic properties determine which chemical reactions are facilitated, introducing conditional branching. Depending on the polymer’s sequence, outcomes can vary significantly.
If the chemical substances generated by these catalytic properties enhance polymer synthesis, prevent degradation, or support their stability, feedback loops may arise. The proliferation of such feedback loops increases the length and number of polymers that can be synthesized and sustained.
Links in the Origin of Life
Furthermore, chemical evolution is thought to have progressed within containers filled with water on Earth. If chemical evolution relied on a single container, it would face a high risk of stalling or being reset by unexpected disturbances. Thus, the probability of success increases with a larger number of containers. Moreover, greater diversity in the chemical environments of these containers further enhances the likelihood of success.
Nevertheless, if each container operates independently, the risk of chemical evolution stalling or being repeatedly reset remains high.
This is where links become essential. When containers are connected, allowing chemical substances to move between them, new combinations of chemicals can interact, increasing the likelihood of novel reactions.
By linking containers, chemical evolution can progress without stagnation, and the outcomes of chemical evolution can be shared across containers, enhancing resistance to disruptions. Moreover, if the links form a cyclical structure, the distributed chemicals can form feedback loops, creating redundancy across multiple containers.
This linking mechanism provides significant advantages for chemical evolution, greatly improving its likelihood of continuous progress and reducing the risk of resets due to localized disruptions. Consequently, chemical evolution can advance step by step, steadily progressing over time.
Comparison with Existing Hypotheses
The mechanism of life’s origin outlined here is, without doubt, a hypothesis. However, it holds a distinct advantage over existing hypotheses on the origin of life: it can fundamentally encompass them.
For example, the hypothesis that life originated in a specific environment aligns with a model where only one container existed. Similarly, the hypothesis that specific chemicals played a central role corresponds to a scenario where the chemical substances discussed here were of a particular type.
Thus, even if existing hypotheses are proven accurate, the model described here remains valid, merely adjusting to specify that certain locations or chemicals played a primary role within this broader framework.
Existing hypotheses have yet to succeed in reproducing the emergence of life, nor are they close to replicating life’s complexity. Additionally, each limited hypothesis has its strengths and weaknesses, leaving gaps that cannot be explained.
The model presented here can encompass these hypotheses concurrently, allowing for easier explanations of phenomena that individual hypotheses struggle to address.
Furthermore, comparing the plausibility of these hypotheses highlights the differences: the probability of successful chemical evolution in a single location or involving specific chemicals is dwarfed by the likelihood of success when involving all waters, lakes, and pools on Earth, utilizing all chemical substances and their combinations.
Taking into account differences in container numbers, chemical diversity, and the stepwise progression of chemical evolution without resets, the probability of success is not merely several times higher — it is orders of magnitude greater. A rough estimate using ChatGPT-4 indicated a difference ranging from 10¹³ to 10²⁰ times.
This makes it clear that the comprehensive model described here has a far higher probability of success in chemical evolution.
Conclusion: Analyzing Complex Systems
The study of the origin of life involves analyzing extremely complex systems. However, the simple model of chemical evolution outlined here has not been proposed in existing research.
This model is based on the elements I identified as necessary for analyzing complex systems: links, repetition, and conditional branching.
In considering the origin of life, if we accurately identify and integrate not just the physical elements and formulas but also links, repetition, and conditional branching, we can conceive and understand such a comprehensive model.
Successfully analyzing the complex system of life’s origin in this way supports my claim that the essential components of complex systems extend beyond physical elements and formulas to include links, repetition, and conditional branching. It also validates my assertion that integrating these components enables us to understand the whole system as the sum of its parts.
This approach addresses the weaknesses of traditional reductionism while compensating for the shortcomings of complexity science and systems theory.
The fact that such a model has not been devised in the longstanding scientific study of life’s origins further supports my claim that science struggles to address complex systems.
