Generalized Game of Life uses qubits to boost species survival models

Conway’s Game of Life has enjoyed popularity in modeling the rise and ultimate fates of theoretical species since its introduction in the 1960s. The zero-player game is an automaton in which cells in a grid are either “dead” or “alive” based on rules involving their immediate neighbors. In its classic form, it assigns ones and zeroes to describe whether each cell is “alive” or not.

David Faux and Peter Bassom developed a generalized variant of Conway’s Game of Life that incorporates qubits to more accurately represent the cycle of life, death, and extinction that species encounter in the fight for survival.

“The paper proposes problems that undergraduate physics students could tackle and are interesting from an environmental perspective. Students can develop a wide range of skills and knowledge outside those normally associated with a physics degree (coding, species ecology, the environment) and provide insight into struggles for survival faced by many species.”

The game describes two new species parameters: the tendency to herd that controls the preferred number of neighbor cells and resilience to environmental changes.

The group tested the game to model the decline of the dodo and the predator-prey interactions between rabbits and foxes, among others. It also predicted that global whale populations would return to their pre-hunting level by the year 2140.

“The most remarkable feature was that it predicted that species can be resilient, that is they can survive in very small numbers and can eventually recover if environmental conditions improve,” Faux said. “The paper provides grounds for optimism.”

They next look to use the game to pit humans and viruses together in a virtual pandemic.

Source: “The game of life as a species model,” by David A Faux and Peter Bassom, American Journal of Physics (2023). The article can be accessed at https://doi.org/10.1119/5.0150858 .