Posted on Dec 31, 2018
“We leave open the question whether the origin of life is genuinely quantum mechanical,” says the team behind exciting new research that provides a breakthrough that may eventually help answer the question of whether the origin of life can be explained by quantum mechanics — a new approach announced October 2018 to one of the most enduring unsolved mysteries in science: how does life emerge from inert matter.
For the first time, with a quantum computer, individual living organisms represented at a microscopic level with superconducting qubits were made to “mate,” interact with their environment, and “die” to model some of the major factors that influence evolution.
“The goal of the proposed model is to reproduce the characteristic processes of Darwinian evolution, adapted to quantum algorithms and quantum computing,” reports Science Alerts. To do this the researchers used a five qubit IBM QX4 quantum computer developed by IBM that is accessible through the cloud. Quantum computers make use of qubits, whose information value can be a combination of both one and zero. This property, known as superposition, means that large-scale quantum computers will have vastly more information-processing power than classical computers.
The researchers, led by Enrique Solano from the University of the Basque Country in Spain, coded units of quantum life made up of two qubits (those basic building blocks of quantum physics): one to represent the genotype (the genetic code passed between generations) and one to represent the phenotype (the outward manifestation of that code or the “body”). These units were programmed to reproduce, mutate, evolve and die, in part using quantum entanglement – just as any real living being would.
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The new research, published in Scientific Reports, is a breakthrough that may eventually help answer the question of whether the origin of life can be explained by quantum mechanics, a theory of physics that describes the universe in terms of the interactions between subatomic particles.
This quantum algorithm simulated major biological processes such as self-replication, mutation, interaction between individuals, and death at the level of qubits. The end result was an accurate simulation of the evolutionary process that play out at the microscopic level, with life, a complex macroscopic feature emerging from inanimate matter. Individuals were represented in the model using two qubits. One qubit represented the individual’s genotype, the genetic code behind a certain trait, and the other its phenotype, or the physical expression of that trait.
To model self-replication, the algorithm copied the expectation value (the average of the probabilities of all possible measurements) of the genotype to a new qubit through entanglement, a process that links qubits so that information is instantaneously exchanged between them. To account for mutations, the researchers encoded random qubit rotations into the algorithm that were applied to the genotype qubits.
The algorithm then modeled the interaction between the individual and its environment, which represented aging and eventually death by taking the new genotype from the self-replicating action in the previous step and transferring it to another qubit via entanglement. The new qubit represented the individual’s phenotype. The lifetime of the individual depends on the information coded in this phenotype.
Finally, these individuals interacted with one another, requiring four qubits (two genotypes and two phenotypes), but the phenotypes only interacted and exchanged information if they met certain criteria as coded in their genotype qubits. The interaction produced a new individual and the process began again. In total, the researchers repeated this process more than 24,000 times.
“Our quantum individuals are driven by an adaptation effort along the lines of a quantum Darwinian evolution, which effectively transfer the quantum information through generations of larger multi-qubit entangled states,” the researchers wrote.
While the computing technology needed to achieve so-called “quantum supremacy” isn’t quite there yet, the work of Solano and his colleagues could eventually lead to quantum computers that can autonomously model evolution without first being fed a human-designed algorithm.
“What we prove here is that microscopic quantum systems can efficiently encode quantum features and biological behaviors, usually associated with living systems and natural selection,” concluded the team.
Image top of page with thanks to Fiverr.com -Cosmic design creations and Greenrose Organization
The Daily Galaxy via University of the Basque Country, Motherboard and ScienceAlerts