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True random numbers are required in fields as diverse as slot machines and data encryption. These numbers need to be truly random, such that they cannot even be predicted by people with detailed knowledge of the method used to generate them.
從投幣機到數據加密，各個領域都需要真正的隨機數。這些數字必須是真正隨機的，如此即使是那些了解這些數字生成規則的人也無法預測它們。
As a rule, they are generated using physical methods. For instance, thanks to the tiniest high-frequency electron movements, the electrical resistance of a wire is not constant but instead fluctuates slightly in an unpredictable way. That means measurements of this background noise can be used to generate true random numbers.
這些數字通常是使用物理方法生成的，例如，由於最微小的高頻電子運動，導線的電阻不是恆定的，而是以一種不可預測的方式輕微波動，這意味著對這種波動背景噪音的測量可以用來生成真正的隨機數。
Now, for the first time, a research team led by Robert Grass, Professor at the Institute of Chemical 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 put forward by other scientists for generating random numbers by chemical means tended to be largely theoretical.
如今，（蘇黎世聯邦理工學院）化學和生物工程研究所的羅伯特·格拉斯教授領導的一個研究小組，首次描述了一種生成這些數字的非物理方法:一種使用生物化學信號並能夠實際操作的方法。在此之前，其他科學家提出的用化學方法生成隨機數的想法大多是理論層面的。
DNA synthesis with random building blocks
具有隨機結構的DNA合成
For this new approach, the ETH Zurich researchers apply the synthesis of DNA molecules, an established chemical research method frequently employed over many years. It is traditionally used to produce a precisely defined DNA sequence. In this case, however, the research team built DNA molecules with 64 building block positions, in which one of the four DNA bases A, C, G and T was randomly located at each position. The scientists achieved this by using a mixture of the four building blocks, rather than just one, at every step of the synthesis.
對於這種新方法，蘇黎世聯邦理工學院的研究人員應用了DNA分子的合成方法，這是一種多年來經常使用的成熟的化學研究方法，一般用來產生精確定義的DNA序列。然而，在這種情況下，研究小組構建了具有64個基塊位置的DNA分子，其中A、C、G和T四個DNA鹼基的其中一個被隨機放置在每個位置上。科學家通過在合成的每個步驟中混合使用四個構建模塊而不是僅使用一個構建模塊來實現這一目標。
As a result, a relatively simple synthesis produced a combination of approximately three quadrillion individual molecules. The scientists subsequently used an effective method to determine the DNA sequence of five million of these molecules. This resulted in 12 megabytes of data, which the researchers stored as zeros and ones on a computer.
結果，一個相對簡單的合成產生了大約3千萬億單個分子的組合。隨後，科學家們使用了一種有效的方法確定了其中500萬個這樣的分子的DNA序列。這就產生了12兆字節的數據，研究人員將這些數據以0和1的形式存儲在計算機上。
Huge quantities of randomness in a small space
一個小空間中存在大量的隨機性
However, an analysis showed that the distribution of the four building blocks A, C, G and T was not completely even. Either the intricacies of nature or the synthesis method deployed led to the bases G and T being integrated more frequently in the molecules than A and C. Nonetheless, the scientists were able to correct this bias with a simple algorithm, thereby generating perfect random numbers.
然而，一項分析顯示，A、C、G、T四種構建塊的分布並不完全均勻。無論是自然的複雜性還是採用的合成方法，都導致G和T鹼基比A和C鹼基更頻繁地融入分子中。儘管如此，科學家們還是能夠用一個簡單的算法糾正這種偏差，從而產生完美的隨機數。
The main aim of ETH Professor Grass and his team was to show that random occurrences in chemical reaction can be exploited to generate perfect random numbers. Translating the finding into a direct application was not a prime concern at first. "Compared with other methods, however, ours has the advantage of being able to generate huge quantities of randomness that can be stored in an extremely small space, a single test tube," Grass says. "We can read out the information and reinterpret it in digital form at a later date. This is impossible with the previous methods."
聯邦理工學院的格拉斯教授和他的團隊的主要研究目的是證明化學反應中的隨機事件可以用來產生完美的隨機數。一開始，把這一發現轉化為直接應用並不是首要考慮的問題。「然而，與其他方法相比，我們的優勢在於能夠產生大量的隨機性，這些隨機性可以儲存在一個極小的空間裡，一個試管中，」格拉斯說。「我們可以讀出信息，並在以後以數字形式重新解釋它。用以前的方法是不可能的。」
Story Source:
Materials provided by ETH Zurich. Original written by Fabio Bergamin. Note: Content may be edited for style and length.
encryption 加密
random 隨機的
electrical resistance 電阻
synthesis 合成
DNA sequence DNA序列
bases 鹼基
algorithm 算法