Researchers first created a life simulator on a quantum computer

Original author: Daniel Oberhaus
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“Our research transferred these amazing and complex events, called life, into the microscopic world of atoms - and it worked.”

For the first time, an international team of researchers used a quantum computer to create artificial life - a simulation of living organisms that scientists can use to understand life at the level of populations and below, up to intercellular interactions.

On a quantum computer, individual living organisms, represented at the microscopic level using superconducting qubits , were forced to “mate”, interact with the environment and “die”, simulating the most important factors affecting evolution.

New studypublished in the journal Scientific Reports, was a breakthrough that, perhaps, will eventually help answer the question of whether the origin of life can be explained by quantum mechanics - a physical theory that describes the Universe in terms of interactions between subatomic particles.

Modeling quantum artificial life is a new approach to one of the most troubling scientists' questions: how does life come from inert matter , from the “ primary broth ” of organic molecules that once existed on Earth?

For the first time, the idea that the answer may be in the quantum field was proposed in 1944 by Erwin Schrödingerin his influential book What Is Life? But progress in this area was slowed down due to difficulties in creating powerful quantum computers, which were required for simulations that could answer this question.

Ordinary, “classic” computers, one of which you use to read this article, process information in the form of binary bits - units of information whose value can take the value 0 or 1. In contrast, quantum computers use qubits, the value of which can represent a combination of 0 and 1. Such their property, superposition, means that the power of large-scale quantum computers will seriously exceed the power of classical ones.

The goal of a team of researchers from the Basque Science Foundation, led by Enrique Solano, was to create a computer model that reproduces the processes of Darwin evolution on a quantum computer. To do this, the researchers used a five-qubit quantum processor developed by IBM , access to which is possible via cloud technology.

This quantum algorithm simulated basic biological processes, such as self-reproduction, mutations, interaction between individuals and death, at the level of qubits. The result was an accurate simulation of the evolutionary process taking place at the microscopic level.

“Life is a complex macroscopic feature arising from inanimate matter, and quantum information is a feature of qubits, microscopic isolated objects, occurring in a very small universe,” Solano told me by mail. “Our research transferred these amazing and complex events, called life, into the microscopic world of atoms - and it worked.”

Individuals were represented in the model using two qubits. One qubit was a separate genotype, the genetic code behind a particular feature, and the other was a phenotype, the physical expression of this feature.

To simulate self-reproduction, the algorithm copied the mathematical expectation (the average value of the probability of the results of all possible measurements) of the genotype into a new qubit usingentanglement , the process of linking qubits together so that they instantly exchange information. To account for mutations, the researchers introduced random turns of qubits into the algorithm code and used it for qubits of the genotype.

The algorithm then modeled the interaction between individuals and their environment, representing aging and death. This was done by transferring a new genotype from the step of self-reproduction to another qubit using entanglement. The new qubit represented the phenotype of the individual. An individual’s lifespan — how long it takes for information to degrade or dissipate in the process of interacting with the environment — depends on the information encoded in the genotype.

Finally, these individuals interacted with each other. This required four qubits (two genotypes and two phenotypes), but phenotypes interacted and exchanged information only if they met certain criteria encoded in their genotypic qubits.

The interaction produced a new individual, and the process was repeated again. In total, the researchers repeated this process more than 24,000 times.

“Our quantum individuals acted under the influence of adaptation attempts within the framework of Darwin's quantum evolution, which, in fact, transmitted quantum information through generations of larger multi-qubit entangled states,” the researchers wrote.

Now that the work of the quantum artificial life algorithm has been demonstrated, the next step will be to scale it to work with a large number of individuals and expand their abilities. For example, Solano told me that he and his colleagues are working on the possibility of adding “sexual characteristics” to qubits, in order to better study social and sexual interactions at a quantum level.

“We can find that it is better to have two sexes, or perhaps not one, for the good of the species, its survival and development,” said Solano.

In addition, Solano said that he and his colleagues want to increase the number of interactions that occur between individuals in the simulation. But it depends on the capabilities of the computer equipment itself.

Although quantum computing has made great strides in recent codes, they still have a very long way to go - mainly due to the capricious nature of qubits. They are incredibly sensitive to noise; they can only be implemented within complex and expensive systems that can shield them from external influences, and this usually means the presence of many lasers, exotic materials and extremely low temperatures.

But even after all these tricks, making several tens of qubits work together is a difficult task. This year, Google has already set a record with a 72-qubit processor , but it is still very far from true quantum superiority, the theoretical point at which quantum computers can get ahead of the most powerful of the classic computers on Earth.

Although the computer technologies necessary to achieve quantum superiority have not yet appeared, the work of Solano and his colleagues can, in principle, lead to the emergence of quantum computers that can autonomously simulate evolution without first asking them to write an algorithm written by people.

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