Published December 31, 2018
"We leave open the question of the origin of life is truly quantum mechanic," said the team of exciting new research that provides a breakthrough that can ultimately help answer the question of whether or not life's origin can be explained by quantum mechanics ̵
For the first time, with a quantum computer, individual living organisms were represented on a microscopic level of superconducting qubits designed to "feed", interact with their environment and "die" to model some of the major factors affecting evolution.
"The aim of the proposed model is to reproduce the characteristic processes of Darwinian evolution, adapted to quantum algorithms and quantum calculations, "reports Science Alerts. n five-quarter IBM QX4 quantum computer developed by IBM available through the cloud. Quantity computers use qubits, whose information value can be a combination of both one and zero. This feature, known as the superposition, means that large quantum computers will have much more information process than classic computers.
The researchers, led by Enrique Solano of the Basque University in Spain, coded quantum units of life consisting of two qubits (the basic building blocks of quantum physics): one to represent the genotype (the genetic code that runs between generations) and one to represent the phenotype (the outward manifestation of that code or "body"). These devices were programmed to reproduce, mutate, evolve, and die, partly by quantum conflict – just as any true living creature would.
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The new research, published in Scientific Reports, is a breakthrough that can help answer the question of whether the origin of life can be explained by quantum mechanics, a theory of physics describing the universe with account for the interaction between subatomic particles.
This quantum algorithm simulated large biological processes such as self-replication, mutation, interaction between individuals and death in the level of qubits. The end result was an accurate simulation of the evolutionary process that plays out at microscopic level, with life, a complex macroscopic function that comes from lifeless matter. Individuals were represented in the model using two qubits. A qubit represented the individual's genotype, the genetic code behind a particular trait, and the other is the phenotype or physical expression of that trait.
To model self-replication, the algorithm copied the expectation value (average of the probabilities of all possible measurements) of the genotype of a new qubit through entanglement, a process that connects qubits so information is exchanged instantly between them. To account for mutations, the researchers encoded coding qubit rotations in the algorithm used on genotype qubits.
The algorithm then modeled the interaction between the individual and its environment, which represented aging and ultimately 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 person depends on the information encoded in this phenotype.
Finally, these individuals interacted with each other, requiring four qubits (two genotypes and two phenotypes), but the phenotypes only interacted and exchanged information if they met certain criteria encoded in their genotype qubits. The interaction gave a new individual, and the process began again. Overall, the researchers repeated this process more than 24,000 times.
"Our quantum individuals are driven by an adaptation effort in line with a quantum Darwinian evolution that effectively transmits quantum information through generations of larger multi-qubit entangled states," The researchers wrote.
Although the data technology needed to achieve so-called "quantum supremacy" is not quite there yet, Solano and his colleagues can eventually lead to quantum computers that can autonomously develop evolution without first feeding a human-designed algorithm.
"What we are showing here is that microscopic quantum systems can effectively encode quantum functions and biological behaviors, usually associated with living systems and natural selection," the team concluded.
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Daily Galaxy via University of the Basque Coun try, Motherboard and ScienceAlerts