Methuselahs: Long-Lived Patterns That Eventually Stabilize

Explore methuselahs in Conway's Game of Life—long-lived patterns that evolve for thousands of generations before stabilizing into simple forms.

angen.ai
June 13, 2024
2 min read
cellular automata
patterns
complexity
evolution
still lifes
oscillators

Methuselahs: Long-Lived Patterns That Eventually Stabilize

Methuselahs are patterns that evolve for many generations before eventually stabilizing into a combination of still lifes, oscillators, and sometimes spaceships. Named after the biblical figure who lived 969 years, these patterns demonstrate the unpredictable complexity of Life evolution.

The Classic Methuselahs

R-pentomino: The R-pentomino is the most famous methuselah, starting with just 5 cells and evolving for 1,103 generations before stabilizing.

Acorn: The Acorn begins with 7 cells and runs for 5,206 generations, making it one of the longest-lived small patterns.

Diehard: Uniquely, Diehard completely vanishes after 130 generations, making it a "mortal" pattern.

B-heptomino: The B-heptomino stabilizes after 148 generations and is commonly seen in random configurations.

Record-Breaking Methuselahs

Rabbits: The Rabbits pattern evolves for 17,331 generations, one of the longest known lifespans.

Lidka: Lidka runs for 29,055 generations from a 13-cell starting configuration.

Fred: Fred holds the record for longest-lived pattern fitting in a 20×20 box at 35,426 generations.

What Makes a Good Methuselah?

Small starting size: The most interesting methuselahs begin with fewer than 20 cells

Long lifespan: Hundreds or thousands of generations of evolution

Clean debris: Eventually settling into recognizable still lifes and oscillators

Glider production: Many methuselahs emit gliders during their evolution

Methuselah Families

Pentomino family: All 12 pentominoes exhibit interesting evolution patterns

Switch engine derivatives: Patterns that create and destroy switch engines

Pi-heptomino family: Various arrangements of the Pi-heptomino

Discovery Methods

Soup searching: Random pattern generation and automated analysis

Systematic exploration: Testing all patterns of a given size

Theoretical construction: Engineering methuselahs with specific properties

Applications

Random number generation: Methuselah evolution can appear pseudo-random

Benchmarking: Testing Life simulation software performance

Art and visualization: Creating complex, evolving displays