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Probabilistic computing is one of the excellent ways to deal with the uncertainties in the data

Over the years, the world of technology has been waiting desperately for quantum computing. The fact that still remains is that quantum computers sound great as far as theory is concerned. But building practical machines is concerned with a truck load of hurdles and challenges. On the brighter side, if the engineers are able to successfully step into the world of practical quantum computers, the kind of computations performed would be taken to a different level altogether. Considering these challenges, one of the most remarkable ways that we could employ here is Probabilistic computing. It is one of the excellent ways to deal with the uncertainties in the data.

Experts believe that the technical challenges faced in case of quantum computers are so immense that it is very unlikely that general-purpose quantum computers would become available anytime in the future. Additionally, it might take anywhere between 5 to 10 years or may be even more to bring the first practical general-purpose quantum computers on line. Evidently, it is a huge investment of time. It is because of all the complications and challenges that people are inspired to delve deeper into understanding the importance and role of probability in computing systems. Late physicist Richard Feynman was confident about people accepting this and proceeding with the same about 30 years back. He believed that a probabilistic computer holds the potential to stand as a competition to quantum computers.

The base, needless to say, is a probabilistic bit. Long back, computers used a magnet with two possible directions of magnetization to store a bit. These magnets can be used to implement p-bits. A team had used the similar technique to build a probabilistic computer in 2019 with eight p-bits.

The best part about using unstable magnets as the fundamental building block is that the p-bit can be implemented using a few transistors rather than thousands of them. This feature makes it possible to build larger probabilistic computers.

Talking about the working principle of probabilistic computers, a system of p-bits evolves from an initial to a final state. Obviously, there are could be a considerable number of intermediate states. Each path has a different probability. The surprise element here is that which path is taken by the computer totally depends on the chance. To get the overall probability, you need to add together all the probabilities of all possible paths. In case of a quantum computer, it uses qubits instead of p-bits. Here, the probability is determined by adding the complex amplitudes for all the possible paths between the initial state and the final state.

Simply put, the difference between a probabilistic computer and a quantum computer is that the former adds up the probabilities whereas the latter adds complex probability amplitudes. There is yet another point to note, probabilities are positive numbers less than one whereas the probability amplitudes are complex numbers. Hence, when you add an additional path in case of quantum computing, it can cancel out an existing path. On the other hand, adding an extra path in probabilistic computers can only increase the final probability.

Another point worth noting is that the qubits carry complex amplitudes. These have to be carefully protected from the environment. A lot of attention has to be paid to the temperature thats maintained. All this hassle is eliminated in case of a probabilistic computer as it can be built with simpler technology operating at room temperature.

On the downside, you cannot deal with negative probabilities here. Thisfurther makes it suitable only for those algorithms that do not require path cancellation.

In a nutshell, probabilistic computing is one of the most effective ways to replace quantum computing.

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