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True random numbers are required in fields as diverse as slot machines and data encryption. These numbers must be truly random, so that they cannot even be predicted by people with detailed knowledge of the method used to generate them.
As a rule, they are generated using physical methods. For example, thanks to the smallest movements of high-frequency electrons, the electrical resistance of a wire is not constant but fluctuates slightly unpredictably. This means that measurements of this background noise can be used to generate real random numbers.
Now, for the first time, a research team led by Robert Grass, a professor at the Institute of Chemistry and Bioengineering, has described a non-physical method of generating such numbers: one that uses biochemical signals and actually works in practice. In the past, the ideas advanced by other scientists for the generation of random numbers by chemical means tended to be largely theoretical.
DNA synthesis with random building blocks
For this new approach, researchers at ETH Zurich apply the synthesis of DNA molecules, an established chemical research method often used for many years. It is traditionally used to produce a precisely defined DNA sequence. In this case, however, the research team constructed DNA molecules with 64 building block positions, where one of the four DNA bases A, C, G and T was randomly placed in each position. Scientists achieved this by using a mixture of the four building blocks, rather than just one, at each step of the synthesis.
As a result, a relatively simple synthesis produced a combination of about three quadrillion single molecules. The scientists subsequently used an effective method to determine the DNA sequence of five million of these molecules. This produced 12 megabytes of data, which the researchers stored as zeros and ones on a computer.
Huge amounts of randomness in a small space
However, an analysis showed that the distribution of the four building blocks A, C, G and T was not completely uniform. Either the complexities of nature or the synthesis method implemented led to the G and T bases being integrated more frequently into the molecules of A and C. However, the scientists were able to correct this bias with a simple algorithm, thus generating numbers perfect random.
The main goal of ETH Professor Grass and his team was to demonstrate that random events in the chemical reaction can be exploited to generate perfect random numbers. Translating the discovery into direct application wasn’t a major concern at first. “Compared to other methods, however, ours has the advantage of being able to generate huge amounts of randomness that can be stored in an extremely small space, a single tube,” says Grass. “We can read the information and reinterpret it digitally at a later time. This is impossible with previous methods.”
Source of the story:
Materials provided by ETH Zurich. Original written by Fabio Bergamin. Note: The content can be changed by style and length.
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