What Generates the Complexity of the Universe and Life?

The complexity of the universe and life arises from three behaviors of complex systems: the dynamic tension that generates temporary stabilities; coupled, assembled, and synchronous coemergences; and sequential and escalating asymmetrical fluctuations. 

Stabilizing functions ensure the functional organization of a system by synchronizing energy flows and optimizing its structure in the present. Simultaneously, synchronous convergences organize components and functions in simultaneous interaction, achieving cohesive and stable morphological configurations. On the other hand, sequential asymmetrical fluctuations introduce progressive imbalances, reorganizing structural morphologies and reconfiguring temporal connectivities, leading to innovations and evolutionary adaptations. It is through this dynamic interplay—where energy flows are efficiently managed, structures are constantly reorganized, and temporalities intertwine—that functional stability and adaptive change are balanced, ensuring the system's evolution and survival.

These interactive behaviors, which might sometimes seem oppositional—stability and emergence, compression and expansion, synchronicity and sequentiality—not only coexist but are the driving forces behind the evolution, transformation, and continuity of complex systems. Through a stochastic and evolutionary process, phenomena emerge that explain, on a large scale, the complexity of the universe and life. When organizing these behaviors by their role in complex systems, three broad groups can be identified: producers of provisional stability, drivers of synchronous coemergences, and generators of asymmetrical fluctuations leading to sequential emergencies and progressive innovations.

Processes that generate provisional stability are fundamental for establishing structures and temporary equilibria in complex systems. Examples include crystallization, where atoms organize into three-dimensional lattice networks; the stable configuration of planetary orbits through gravitational interactions; ocean currents, which regulate climate and transport nutrients; and tree growth rings, which reveal cyclical adaptations to environmental conditions. In biology, this is seen in the self-organized stability of the DNA double helix, cellular membranes that maintain functional integrity, and bone structures, where a combination of compactness and porosity ensures strength and adaptability.

Behaviors that drive synchronous coemergences promote self-organization and systemic efficiency, enabling constant interactions. Examples include geometric patterns in floral formations, which follow the Fibonacci sequence to optimize reproductive efficiency; bird flocks, whose coordinated flight reduces energy consumption and improves aerodynamics; and transport networks in leaves, which optimize the distribution of nutrients and water. In ecosystems, trophic networks enable stable interaction among producers, consumers, and decomposers, while coral reef structures and root systems with mycorrhizae foster adaptability and cooperation, optimizing the creation of complex habitats. At the neuronal level, the plasticity of networks allows the functional reorganization of the nervous system, facilitating learning and memory in response to environmental stimuli.

Generators of asymmetrical fluctuations and sequential emergencies introduce fundamental transformations that drive evolutionary innovations. From a cosmic perspective, key examples include pre-Big Bang quantum fluctuations and those during the Big Bang, which gave rise to the universe's first structures. Phase transitions during the early cooling of the cosmos allowed for the emergence of finely tuned particles and structures, while primordial nucleosynthesis produced the first light elements that served as the basis for the formation of initial stars. In later stages, the asymmetry between matter and antimatter, quantum tunneling effects, and nuclear fusion enabled the emergence of heavy elements and the release of energy.

In biology, autocatalysis and genetic mutations play crucial roles in the emergence of new life forms, while speciation and adaptation facilitate diversification and optimization of organisms. At the cognitive and cultural levels, coevolutionary processes generated complex interdependence networks, where consciousness, cognition, and learning enabled the emergence of new social structures and technologies. In the realm of artificial intelligence, phenomena such as convolutional neural networks, generative adversarial networks, and deep learning represent contemporary examples of progressive innovations in complex systems, revolutionizing processing capacity and knowledge generation.

Thus, complex systems develop through a dynamic balance between provisional stability, synchronous coemergences, and asymmetrical fluctuations, resulting in the continuous generation of new structures and behaviors. These processes demonstrate that the complexity of the universe cannot be reduced to linear or simplified patterns, as it arises from the dynamic interaction among energy flows, structural morphologies, and temporal connectivities, both within systems and in their multiscalar interactions. From this perspective, the universe is conceived as an interconnected fabric of energy, interactions, and evolution, where the causes of complexity intertwine to generate the rich diversity that characterizes our reality.

The Supercomplex Knowledge approach captures these deep interactions, showing that the evolution, transformation, and continuity of complex systems depend on the dynamics among stability, synchronization, and progressive imbalance. From the SK perspective, this interconnected fabric of energy, structures, and temporalities not only explains how the universe, life, and the human brain function but also inspires us to explore new forms of understanding and self-understanding.