A major shift in the computing paradigm is taking shape that could render all current technologies obsolete: quantum computing. However, to understand the challenges posed by the development of quantum computing, we need to look back at the very paradigm of computing as it works today.
The computing paradigm
Information Technology (IT) in the broadest sense, has undeniably opened up a new page in industrial history. All current developments in computing (from neural networks to video games and graphics) are based on the representation of information in a binary system. Any calculation, information, image, sound or signal can be represented in a binary configuration, a logical sequence of bits. The bit represents the smallest, most detailed level of granularity at which information can be represented.
In today’s computing paradigm, a bit can only take on two values: 0 and 1. This is why we speak of a “binary” system. Although this formulation is now well known to the general public, few people actually know how to explain what “0” or “1” means for a bit. For there is an underlying, very tangible physical phenomenon that enables us to qualify a bit by giving it a value of “0” or “1”. Indeed, almost all printed circuit boards rely on electricity to determine/assign/read the value of a bit. So, in most cases, electrical potential (i.e. voltage) is used to characterize a bit. If this exceeds a certain threshold value, then the bit is considered to be worth 1; otherwise, it’s worth 0. There is no intermediate state. It is therefore a binary system, because it is discrete (there is only a finite number of possible values: 0 or 1) and deterministic (a bit is either 0 or 1).
Where quantum computing breaks with so-called “classical” computing is precisely in the way it represents information. The underlying physical phenomenon is not electricity (the presence or absence of an electric current or the value of an electric potential) but quantum physics (i.e. the presence or absence of particles). Quantum physics is dominated by an uncertainty principle, and is non-deterministic by nature. What appears to be a limitation is in fact an extremely powerful feature.
Information in the quantum sense: the qubit
In “classical” computing, a bit has two values: 0 and 1. This represents only two possible states (equivalent, for example, to the absence or presence of electric potential). For a quantum particle, these two states 0 and 1 also exist. But there is also a third possibility: an indeterminate state, a linear combination of the two states 0 and 1. In this third state, this means that the quantum particle can be observed in state “0” with a certain probability and state “1” with a complementary probability.
On the other hand, if we want to measure the state of the quantum particle at a given moment, we’ll observe either the “0” state or the “1” state. By analogy with the bit in “classical” computing, we use the term “qubit” to represent information in the quantum sense, i.e. the linear combination of “0” or “1” states. If we measure a qubit, we’ll observe one of the two values “0” or “1”.
Even trying to measure the qubit’s value can change its state. Nevertheless, if we don’t measure the qubit, its state still exists as a linear combination of the “0” and “1” states, although we can’t know it precisely. Another quantum phenomenon, which does not exist in the classical world, makes qubits very interesting: quantum entanglement. Quantum entanglement enables two particles (and hence qubits) to have correlated states. By using quantum entanglement, it is therefore possible to link the value of several qubits together and represent a much more complex set of possibilities. This is precisely the strength of quantum computing.
The most complex problems within the reach of qubits
Problems are generally considered complex because of the number of possibilities that need to be explored to solve them. One labyrinth will be more complex than another due to its many detours and crossings. It is therefore necessary to explore each possibility sequentially to determine whether it is a possible solution. For a conventional computer, this requires a considerable amount of resources and time. For the most powerful supercomputers, some problems are even out of reach, as they would take years to solve.
For a quantum computer, the entanglement of qubits enables a greater number of possible solutions to be covered and explored simultaneously, providing considerable power and time savings. The pharmaceutical and banking industries are just some of the possible applications that classical computing is struggling to solve. Quantum computing would open up the possibility of exploring complex combinations of proteins with potential medical applications. Similarly, quantum computing would make it possible to find the prime factors of large numbers, which is a very demanding mathematical problem today, to the extent that the robustness of the RSA cryptography used to protect bank data relies on it.
The current state of quantum computers
Quantum computers already exist. However, they are still in the experimental stage, giving companies time to adapt before they can be applied in industrial and commercial contexts. The realization of quantum processes requires extreme experimental conditions, not because one approach requires a temperature close to absolute 0 (which is -273.15°C). But also because of the presence of errors due to the modification of qubit states, which are highly sensitive to quantum decoherence and noise. Nevertheless, demonstrations by experimental quantum computers leave little doubt that a revolution is underway in the computing paradigm.
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