You might have heard of something called a quantum computer and how it could be the future of computing, as it can potentially solve the problems that were previously intractable on classical computers, that is, the computers we use today.

But how are quantum computers able to solve problems that are practically impossible on classical computers?

The answer to this lies in the basic unit of quantum information — the quantum bit or the qubit, which is the quantum analog to the binary bit of classical information. Unlike the binary bit which consists of only two possible states (0 and 1), the qubit states consist of 0, 1 and a multitude of superposition (or linear combinations) of the 0 and 1 states. In quantum computation, we are interested in this purely quantum mechanical behaviour and the state of superposition.

To be clear, measurement of the qubit will yield only 0 or 1, but when it is in a state of superposition, we can only talk about the probabilities of measurement, that is, how probable is the state of 0 or 1 upon measurement. To visualize the possible states of a qubit, consider a sphere in 3 dimensions. The surface of this sphere can be used to represent all the states of the qubit, including the 0 and 1 states. The “North pole” of this sphere represents the 0 state, while the “South pole” represents the 1 state. These are the two points accessible to a classical binary bit. However, all the other points on the surface of this sphere are also possible states for the qubit. Thus, we can see that the “state space” accessible to a qubit is much larger than that of the binary bit!

Why is this significant?

The state space of the qubit (or a system of qubits) is what allows it to perform a large number of calculations at once, and gives it tremendous potential to solve previously intractable problems. This is done using the principle of superposition. But there’s a catch. Among these large number of different answers which are in a superposition, we might want only one (the right answer!), but measurement could yield any one of these answers at random. In order to get the right answer, we need to get all the wrong answers to destructively interfere with each other (where the property of superposition is once again used) so that only the state corresponding to the right answer remains. This is one of the key features of quantum computation and quantum algorithms are all about taking advantage of them.

Few problems like finding the prime factors of any given composite odd integer (which is crucial to modern-day cryptographic systems) are almost exponentially faster on quantum computers (on paper at least) than classical computers. To highlight this, it’s practically impossible for even the world’s largest supercomputers to break a sufficiently strong encryption as no efficient non-quantum algorithm for doing so has been discovered so far. Therefore, the brute-force method of guessing random keys and checking if they work is the only approach. This would indeed take an extremely long time and consume a lot of energy for the size of encryption keys that we use today. With quantum computers, however, this becomes virtually trivial. Some other areas where quantum computers can tremendously help are in drug research, molecular modelling, better financial models and a whole class of optimization problems that are employed in several disciplines.

How far are we in realizing true quantum computers?

Tech giants like Google, Intel, Microsoft, IBM (along with publicly funded institutions) have already successfully made quantum computing processors that consist of a few dozen qubits. But these are not nearly enough to solve problems of practical relevance. These qubits also require a high degree of maintenance, requiring them to be kept at extremely low temperatures (colder than even the vacuum of deep space!) so as to protect them from thermal excitation and other environmental noise. This is important because the qubit’s pure state of superposition, which is an entirely quantum mechanical phenomenon, can easily be destroyed by external noise (which can be anything from tiny vibrations to stray electromagnetic fields). This destruction of the pure state of the qubits is known as decoherence and it can happen all too easily, thus rendering the qubits useless. Aside from the technological and engineering challenge of fabricating and maintaining qubits, there are other auxiliary questions that need to be answered and are currently being explored. How do you input signals into a qubit? How do you control the qubits so that they behave in the manner that you want them to? How do you extract information out of a qubit? How do you do all this without destroying the pure state of the qubits, and protect them from environmental noise? How do you store quantum information? And in the event of decoherence, how do you protect your information from possible errors? These are just some of the many questions that scientists, engineers and mathematicians working in this field are thinking about. There is much progress to be made, but we have already come a long way in the past two decades. So there’s hope that one day we may create a useful, fault-tolerant quantum computer, perhaps in the not so distant future.