According to a study undertaken by the Stanford University, a pattern was recognized between the digital currency network and natural process. The study released on April 23, 2018, revealed that the laws of nature share a distinct similarity with bitcoin transactions.
Being the most popular digital financial instrument in the world; bitcoin has become a case study for many scientists. Amidst several research studies being conducted on bitcoin William Gilpin, a doctoral student and head of The Stanford National Academy of Sciences has come up with a strange hypothesis. He claims that his studies can help in streamlining and validating procedure in the production of drugs. He added that the study had the capability of discovering a new theory of the universe.
To be precise, his findings explain the homogenous principles shared by digital currency transactions and swirling liquids. A complex mathematical sequence called the cryptographic hash encrypts the transactions on the blockchain. Gilpin informs that hash functions mathematically change the digital information contained in a unique cryptographic output key that protects the input.
He claims that the prominent governing laws of swirling liquids operate in the same manner. The study states, “An essential component of digital communication is hashing, in which a complex piece of information (a document, video, etc.) is mathematically transformed into a unique signature that can later be used to identify the original piece of data. Here, we show that this process bears a strong similarity to the chaotic behavior of certain types of flows observed when ordinary fluids mix, such as the stirring of dye into the water. We use this analogy between rearranging information and stirring a fluid to construct a fluid-based hash function with comparable properties to traditional algorithms.”
Gilpin was able to find the connection between cryptographic hash functions and the equations involved in mixing a fluid through a principle called chaotic mixing. He said, “I wasn’t expecting it to perform that well. When it looked like it satisfied every property of a hash function I started getting really excited. It suggests that there’s something more fundamental going on with how chaotic math is acting.”
Gilpin’s finding has gained attraction due to its capability of creating better ways of protecting information. Moreover, the theory can be applied in the development of drugs that involve mixing numerous fluids at specific points in time. As both the operations have the same dynamics, it becomes easy to minimize the margin of error.
He adds, “If you don’t form the correct arrangement when you’re done, then you know that one of your processes didn’t go right. The chaotic property ensures that you’re not going to accidentally get a final product that looks correct.”
As far as Gilpin’s credentials are concerned, he is not a drug developer or computer scientist himself. He has interest in learning more about the behavior of fluids in nature apart from connecting the digital and physical fields. For him, “the idea that we can start to use some of these ideas from computer science is pretty exciting.”…