Our computers, even the fastest ones, seem today unable to withstand the needs of the enormous quantity of data in our technological society. That’s why scientists are working on computers using quantum physics, so much faster and powerful than conventional ones
An ordinary computer works with bits, where a bit has a single binary value, either 0 or 1. A quantum bit, or qubit, instead can store a zero, a one, both zero and one, or an infinite number of values in between. That increases enormously the capacities of calculations.
We are still at the beginning of this new era of computing, hence there are for sure many ways to use this new technology that have yet to be discovered. For example, the factorisation of very big prime numbers, a task which is closely related to cryptography and security of passwords, could be one of the many possible uses of quantum computers.
Many future applications of quantum computers are showing up on the horizon. And many more will follow
According to Professor Sabrina Maniscalco, who heads the Turku Quantum Technology group in Finland, “The most famous quantum algorithm is Shor’s algorithm. This algorithm, if running on a quantum computer, factorises integer numbers into prime factors faster than any known classical algorithm. This is remarkable as the slowness of prime factorisation is the basis of currently used methods to decipher messages.”
But there are many other possible uses of this new technology. According to recent research reported in the peer-reviewed journal Science Advances, “The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device.” Computing giants Google and Microsoft are investing a lot of money in this research field.
By using quantum physics in computers, scientists could also in the future simulate chemical reactions, in order to facilitate drug design and improve machine learning.