Published on December 31, 2018
"Let's leave the question of whether the origin of life is genetically quantum mechanic," says the team behind a new and exciting research that provides an advance that may eventually help answer the question of if the origin of life can be explained by quantum mechanics: a new approach announced in October 2018 to one of the most lasting unresolved mysteries of science: how life arises of the inert matter.
For the first time, with a quantum computer, individual living organisms represented at the microscopic level with superconducting qubits became "mates", interact with their surroundings and "die" to model some of the main factors that influence the evolution .
"The objective of the proposed model is to reproduce the characteristic processes of Darwinian evolution, adapted to quantum algorithms and quantum computing," informs Scientific Alerts. To do this, the researchers used an IBM QX4 quantum quad-qubit computer developed by IBM that is accessible through the cloud. Quantum computers use qubits, the value of the information can be a combination of zero and zero. This property, known as a superposition, means that large-scale quantum computers will have much more information processing power than classic computers.
The researchers, led by Enrique Solano of the University of the Basque Country in Spain, codified units of quantum life composed of two qubits (those basic elements of quantum physics): one to represent the genotype (genetic code passed between generations) and one to represent the phenotype (the outer manifestation of this code or the "body"). These units were programmed to reproduce, mutate, evolve and die, partly using quantum swing, just like any real being.
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The new research, published in Scientific Reports, is an advance that may possibly help answer the question of whether the origin of life can be explained by quantum mechanics, a physics theory that describes the # 39; Universe in terms of the interactions between subatomic particles.
This quantum algorithm simulated large biological processes such as autoreplication, mutation, interaction between individuals and death at the qubits level. The final result was a precise simulation of the evolutionary process that is played at a microscopic level, with life, a complex macroscopic characteristic that emerges from inanimate matter. The individuals were represented in the model with two qubits. A qubit represented the genotype of the individual, the genetic code behind a certain trait, and another its phenotype, or the physical expression of this trait.
To model autoreplication, the algorithm copied the expectation value (the average probabilities of all possible measures) from the genotype to a new qubit through the interlacing, one a process that unites qubits to instantly exchange information between them. To take into account the mutations, the researchers codified random qubit rotations in the algorithm applied to the genotype qubits.
The algorithm modeled the interaction between the individual and his environment, which represented aging and, eventually, death, taking the new genotype of the self-replicating action in the Previous step and transferred to another qubit through a plot. The new qubit represented the phenotype of the individual. The life of the individual depends on the information coded 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 some criteria coded in their genotype qubits. The interaction produced a new individual and the process started again. In total, the researchers repeated this process more than 24,000 times.
"Our quantum individuals are driven by an effort of adaptation along the lines of a Darwin quantum evolution, which effectively transfers quantum information through generations of angry states with multiple qubit" , the researchers wrote.
Although the computing technology needed to achieve the so-called "quantum supremacy" is still not good, Solano's work and colleagues could eventually lead to quantum computers that can model the evolution of form autonomous without having been fed an algorithm designed for the home.
"What we show here is that microscopic quantum systems can efficiently encode quantum features and biological behaviors, usually associated with living systems and natural selection," the team concluded.
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The Daily Galaxy for the University of the Basque Country, Motherboard and ScienceAlerts