DNA molecules yield biochemical random number
Scientists at the European Institute of Technology (ETH) have used DNA synthesis to generate a giant true random number. This is the first time such a huge number has been created through biochemical means.
True random numbers are needed in fields as diverse as slot machines and data encryption. These numbers need to be truly random, so much so that they cannot even be predicted by people with detailed knowledge of the methods used to generate them.
Usually, they are generated physically. For example, the resistance of a wire is not constant, but fluctuates slightly in an unpredictable way, due to the slightest high-frequency electron movement. This means that measurements of this background noise can be used to generate truly random numbers.
Now, a research team led by Robert Glass, a professor at the Institute of Chemical and Biological Engineering, has described for the first time a non-physical way to generate such numbers: a method that uses biochemical signals and actually works in practice. In the past, ideas proposed by other scientists to generate random numbers using chemical methods have tended to be largely theoretical.
Synthesizing DNA with random building blocks
For this new approach, ETH researchers applied the synthesis of DNA molecules, a well-established chemical research method that has been used regularly for many years. Traditionally, it has been used to produce a precisely defined DNA sequence. In this case, however, the team constructed a DNA molecule with 64 building block positions, with one of the four DNA bases A, C, G, and T randomly located at each position. The scientists did this by using a mixture of the four building blocks at each step of the synthesis, rather than just one.
As a result, a relatively simple synthesis yielded a combination of about four trillion individual molecules. Scientists then determined the DNA sequences of 5 million of these molecules using an efficient method. This yielded 12 terabytes of data, which the researchers stored in the form of 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 perfectly uniform. Nonetheless, the scientists corrected for this discrepancy with a simple algorithm to produce perfect random numbers.
The main goal of ETH Professor Grass and his team was to demonstrate that random occurrences in chemical reactions can be exploited to generate perfect random numbers. Translating this discovery into direct application was not initially a primary concern." However, our method has an advantage over other methods in that it can generate a large number of randomnesses that can be stored in a very small space, a test tube," Grass said." We can read the information and reinterpret it later in digital form. That wasn't possible in previous methods."
Translated with www.DeepL.com/Translator (free version)
