Quantum computing is potentially useful for many fields, such as cryptography, molecular modeling, machine learning, and computational biology, etc. Before going into detail of what quantum computing is useful for, let’s know what quantum computing is.
What Is Quantum Computing?
Quantum computing is a type of computation that uses the laws of quantum mechanics to solve problems and store data. It is a new-generation technology and the problems it solves are too complex for ordinary computers and even supercomputers. A quantum computer is about 158 million times faster than the classical computers we currently have.
Potential Applications Of Quantum Computing
The following are some of the potential applications of quantum computing:q1
Attacking the cryptographic systems that are in use today could be a remarkable application of quantum computing. And of-course, it would be a big concern for cyber security. However, scientists are actively researching under the field of post-quantum cryptography to identify such cryptographic systems that may not be attacked by quantum algorithms.
Artificial Intelligence (AI)
Artificial intelligence is another main application of quantum computing. The basis of artificial intelligence is “learning from experience”, and it becomes more accurate when proper feedback is given. While the basis of the ‘feedback’ is calculating the probabilities for many possible options. So it is predicted that in the future, artificial intelligence (AI) can benefit from the advancements in quantum computing.
Simulation Of Quantum Systems
It is believed that quantum simulation will be one of the major applications of quantum computing. Because, nanotechnology and chemistry depend on understanding quantum systems and it is not possible to efficiently simulate such systems in a classical way. It is predicted that quantum simulation could be used for the simulation of atomic and other particles’ behavior at uncommon conditions, like the reactions occurring inside a collider.
Quantum computing played a major role in solving problems in the field of computational biology. Computational genomics is a well-known example of this. Quantum computing has also extremely minimized the time required to sequence the human genome. Quantum computing algorithms have also been used to investigate the function of micro-RNA.
Generative Chemistry and Computer-Aided Drug Design
The models of deep generative chemistry are emerging as a powerful method to boost drug discovery. In future, quantum computers could overcome the hurdles of the huge size and complex structural space of all the drug-like molecules.
To forecast weather, an immense amount of data and so many different variables are required. Quantum computation could help to overcome the complexity level with which weather is forecasted.
It is also expected that better climate models could be built with the help of quantum computers that could provide a deep insight of environmental influence on humans. These models would help to predict future warming and determine the ways to prevent disasters.