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One of the top applications of quantum computing is its utility in research in the field of particle physics or high energy physics. Particle physics models are highly complex. Quantum computers enable physicists to deal with vast experimental data with accuracy and speed. They also allow one to simulate nuclear experiments and fundamental interactions, including scattering the nuclei and quarks.
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Quantum computing applications include the crucial task of training artificial intelligence. The intelligence demonstrated by machines requires training; quantum computing can simplify the task of analyzing millions or even billions of data points with accuracy and speed. In 2020, Google, in collaboration with Volkswagen and the University of Waterloo, launched TensorFlow Quantum to accelerate development in quantum computing.
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One of the top applications of quantum computing includes its use in financial modeling. Based on expected returns and associated risks, finding the right mix for profitable investments is significant for financial investors to survive in the market. Since quantum computers are mainly designed for such probabilistic calculations, by using them, investment banks can enhance the quality of their solutions and significantly decrease the time required to develop them.
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The development of drugs is on the list of top applications of quantum computing. It can take over ten years and billions of dollars for pharmaceutical companies to discover or develop a new drug, for which scientists run hundreds of millions of comparisons on conventional computers. However, the processing capabilities of traditional computers are limited as they can analyze molecules only up to a specific size. This issue can be rectified with the use of quantum computing.
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Applications of quantum computing in advertising and marketing are revolutionary. Quantum algorithms can help create and deliver better advertisements by interpreting associations influencing purchasing patterns. Instead of just using browser history for ad delivery, quantum algorithms focus on factors like how users feel after looking at an advertisement and what types of ads could help make long-term relations with the customers.
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Applications of quantum computing include the discovery of new materials. Quantum computing is based on quantum-mechanical phenomena; hence, it can represent other quantum systems more efficiently than conventional computers. For instance, consider Schrödinger’s equation. A quantum machine can solve Schrödinger’s equation for a molecule to accurately calculate its allowed energy states.
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The development of clean fertilizers is one of the quantum computing applications. Quantum computers are gearing up to model the primary cofactor of nitrogenase, i.e., the FeMo cofactor. This advancement can enable chemists to develop energy-efficient industrial processes for synthesizing nitrogen or clean fertilizers.
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Quantum computers can also help tackle the problem of traffic control, which is a result of the increasing population. Technology using quantum computing can be used to mitigate traffic jams and thus shorten waiting periods. Recently, Volkswagen demonstrated the use of quantum computing to optimize traffic in a live setting.
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Enhancement of cybersecurity is one of the most crucial applications of quantum computing. Quantum computers can crack encryption algorithms that protect the infrastructure and sensitive data of the internet. Estimates predict that a quantum computer with 20 million qubits is capable of breaking such encryptions in less than 8 hours.
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One of many applications of quantum computing is mapping complicated weather patterns. Unlike traditional weather forecast systems, quantum computers can provide forecasts for much smaller and more specific areas. This can assist farmers in preparing for weather changes efficiently and allow airlines to minimize fight disruption.
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Researchers at IBM and Daimler AG are testing how quantum computers can simulate the behavior of chemical compounds in Lithium-ion batteries. They were able to simulate dipole moments of four industrially relevant molecules, viz. lithium sulfide, hydrogen sulfide, lithium hydride, and lithium hydrogen sulfide, using a 21-qubit quantum computer.