Endless Forms Are the Most Beautiful; Why Does Evolution Favor Symmetry?

A worldwide team of researchers thinks endless forms are indeed beautiful, and they've integrated principles from biology, computer science, and mathematics to explain why.

As they describe in PNAS, symmetric and other basic forms occur so frequently because evolution has a strong bias for simple "algorithms," that is, simple instruction sets or recipes for constructing a certain structure.

Symmetry in biology

(Photo : ASTRID VELLGUTH/AFP via Getty Images)

Nature is full of symmetry, often in the most beautiful ways.

A beautiful snowflake, a budding young sunflower, and a luminous complex from a bacteria all have stunning symmetry as if created by some higher purpose.

But how did that particular design come to be? Why were so many biological sources materialized in such ordered patterns, especially while thermodynamic equations state that the cosmos is trending toward increased entropy and ever-increasing randomness?

According to Fast Company, scientists incorporated parts of biology, computer science, and mathematics in a paper published in the Proceedings of the National Academy of Sciences to support the hypothesis that evolution has an overwhelming preference for algorithms, which dictate how our planet's natural structures emerge.

Imagine having to explain how to tile a floor to a buddy in a few words, says Iain Johnston, a professor at the University of Bergen and the study's author said.

Researchers employed computer modeling to investigate how this predilection develops in biology.

They demonstrated that there are far more potential genomes that explain basic algorithms than complicated ones.

According to ScienceDaily, simple methods are more likely to be discovered when evolution searches for potential genomes, as are the more symmetric structures that they generate.

The researchers then linked this evolutionary picture to a profound discovery from the theoretical discipline of algorithmic information theory.

According to Ard Louis, professor at the University of Oxford and author of the paper, these intuitions may be codified in the discipline of algorithmic information theory, which yields mathematical predictions for the bias toward descriptive simplicity.

Also Read: EXPLAINED: Strange Symmetrical Zigzag Patterns Appear in Iceland

The 'infinite monkey theorem'

In a final framework, the authors relate their findings to the "famous trope of monkeys typing at irregular intervals on typewriters."

Known as the "infinite monkey theorem," this thought experiment proposes that a monkey trying to punch random keys on a typewriter for an unlimited period will ultimately create any given text including the complete works of William Shakespeare, among basically any other conceivable literature.

That premise is based on the assumption that, given unlimited time, random input should yield every potential output.

The Infinite Monkey Theorem states that every problem can be solved if adequate resources and time are applied, as per Whatis.com.

That concept has been applied in a variety of contexts, including developing the proposed system, primary commodities computing, project management, and the SETI (Search for Extraterrestrial Intelligence) project, to support a greater allocation of resources, particularly low-end resources, to solve a given problem.

The theorem is sometimes used to demonstrate fundamental probability principles.

Consider those writings to be algorithms, and the monkey to be nature's programmer, encapsulating the whirling forces of physics as well as the entire condition of existence.

Simply by chance, the monkeys would develop simpler algorithms more frequently than sophisticated ones.

The researchers demonstrate that a wide range of biological systems and structures, ranging from proteins to RNA and communication systems, adopt algorithmically simple forms with probability, as anticipated by this theory.

They intend to study the projections that their theory provides for biases in bigger developmental stages in the future.