Google achieved a huge milestone in 2019 as it announced its much-anticipated breakthrough of “quantum supremacy.” As the news broke, there was a buzz about the enthralling power of quantum computing applications. The tech giant’s achievement signifies the rapid advancement of technology for commercial viability. It proclaimed that quantum computing had achieved what a traditional computer would have fulfilled in a thousand years. Though that may seem quite like an exaggeration to many, research centers in Japan and Australia also announced breakthroughs about quantum computers becoming more potential than ever.
As the breakthroughs continue, millions of dollars pour in, and the horizon of quantum computing uses & applications widens. This comes as no surprise with major tech giants companies such as Amazon, Alibaba, Google, IBM, and Microsoft accelerating their development of quantum capabilities by launching commercial quantum-computing cloud services. As a result, most of the uses of quantum computers may become normal in 2030 as These companies envision launching their quantum computing applications by that time. Though more advanced uses of quantum computing are still far, such facts make it intriguing to learn about today’s most prominent applications of quantum computing. So, in this article, we will learn about the top eleven quantum computing uses & applications that everyone should know.
From Artificial intelligence and machine learning to weather forecasting, here are some of the astonishing quantum computing uses that have already taken the tech world by storm.
Let’s have a look at each of them one by one.
Almost every aspect of human life has been touched by developing technologies. Emerging technologies like artificial intelligence vs machine learning are examples of this. Applications for speech, image, and handwriting recognition are common. As the number of applications increased, it became more challenging for conventional computers to match the precision and speed. This is where quantum computing comes into play, processing complex problems within a few minutes, unlike traditional computers, which would take much longer to do so. Therefore, quantum computing for machine learning and artificial intelligence can bring new and easier applications for people.
Some cancers are curable if found in their early stages. Numerous techniques, including chemotherapy, radiation therapy, and surgery, are used in this course of treatment. Beam optimization is a key component of radiation therapy for cancer treatment. The cells in the area that radiation impacts are killed when administered to a patient. A portion of the healthy cells’ surrounding tissue is frequently eliminated as the cancer cells are removed. Over the last ten years, multiple radiation-related techniques have been created using conventional computers. But, in 2015, a popular study suggested a fresh approach to radiation beam optimization using quantum annealing computers. They are said to possibly enhance the predictions of whether malignant cancers will develop in tissue at a later stage or not.
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It is vital to find the right blend of lucrative investment opportunities according to expected returns, associated risks, and other factors to survive in the finance industry. Just as fleet management software development helps you tackle the issues of your enterprise’s human resources, financial modeling can help you with financing.
To remain competitive, “Monte Carlo” simulation algorithms are continuously run on traditional computers. This requires a significant amount of computer time. However, by employing quantum computing, businesses may increase the quality of the solutions and shorten the development time to carry out these enormous and complex calculations.
Financial leaders manage billions of dollars, so even a small boost in the expected return can be quite valuable to them. Another potential application of quantum computing here is algorithmic trading, which automatically triggers share dealings by evaluating market conditions and is particularly useful for high-volume transactions.
Molecule simulation is a classic example of quantum computing applications for computational chemistry. Although traditional computers can simulate molecules, the complexity of a simulation that they can perform is constrained. Quantum computers, however, can effectively get around this limitation. For instance, at the moment, quantum computers can simulate tiny molecules like beryllium hydride (BeH2). Even though this molecule currently appears little, the point that its simulation was held on a 7-qubit machine is noteworthy since the simulation of larger molecules would be possible if more qubits were available. As the number of qubits in a quantum system rises, so do its processing powers.
Drugs are typically produced through the trial-and-error process, which is expensive and a dangerous and difficult endeavor to complete. Drug corporations may save a tonne of money and time by using quantum computing, according to researchers, to understand better medications and how they affect people by enabling businesses to conduct more drug discoveries and find novel medical treatments.
A 2017 study suggested that quantum computers could predict the weather more precisely than traditional computers. Quantum computers are anticipated to accelerate data management to provide more precise weather forecasts using the Dynamic Quantum Clustering (DQC) methodology. This can help aircraft run more smoothly and help farmers prepare for weather fluctuations effectively. In addition, by analyzing vast amounts of meteorological data, quantum computing systems can foresee minute meteorological occurrences like the development of individual clouds or wind eddies.
A wide range of companies will be able to optimize their logistics and scheduling workflows related to their supply-chain management thanks to improved data analysis and strong modeling. The operational models may severely impact applications by repeatedly calculating and recalculating the best routes for traffic management, air traffic control, freight, fleet operations, and distribution. Normally, conventional computing is employed to complete these jobs; however, some might become more difficult for an ideal computer solution, whereas a quantum technique might be able to. Quantum annealing and universal quantum computers are two popular solutions to overcome such issues.
By understanding associations among factors impacting purchasing behaviors, quantum algorithms aid in the creation and delivery of better advertisements. Quantum algorithms concentrate on elements like how people feel after viewing an advertisement and what kinds of ads could help build long-term relationships with the customers rather than only using browser history for ad distribution. Businesses are exploring quantum computing uses for advertising to analyze complex data more quickly & effectively and offer adverts to their target clients.
As our reliance on digitization grows, the risks of cyber attacks expand. Quantum computing with machine learning can aid in developing numerous strategies to counter these cybersecurity companies‘ risks. Additionally, quantum computing, also known as quantum cryptography, can assist in developing robust encryption techniques.
Volkswagen attempted to solve the traffic problem in 2017 by solving the traffic. In addition to considering all alternative routes, they employed the quantum annealing computers and the QUBO-Quadratic Unconstraint Binary Optimization technique to identify the best route for a specific number of cars. To date, they have tested around 10,000 taxis in Beijing to demonstrate how this technology can optimize traffic more quickly than traditional computers. Hence, quantum computing can become an effective solution to curb traffic congestion.
The behavior of chemical compounds in lithium-ion batteries is being modeled by IBM researchers using quantum computers. Using a 21-qubit quantum computer, they could model the dipole moments of four industrially important molecules: lithium sulfide, lithium hydride, hydrogen sulfide, and lithium hydrogen sulfide. Improving the qubit states will enable scientists to conduct more complex compounds and develop robust yet inexpensive next-gen batteries.
Presently, many quantum computing applications still require extensive research. Though the technology is in its nascent stage, its potential is still unmatched. GlobeNewswire statistics evaluated the global market value of quantum computing at $507.1 Mn in 2019. This is predicted to reach $4531.04 Bn by 2030. Thus, there is a lot to be seen beside the above-mentioned quantum computing uses; all we have to do is wait and watch.
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