{"id":11108,"date":"2021-09-15T17:31:50","date_gmt":"2021-09-15T17:31:50","guid":{"rendered":"http:\/\/ctqywot.cluster028.hosting.ovh.net\/use-cases-for-quantum-computing\/"},"modified":"2022-02-07T15:17:08","modified_gmt":"2022-02-07T15:17:08","slug":"use-cases-for-quantum-computing","status":"publish","type":"post","link":"https:\/\/www.qureca.com\/es\/use-cases-for-quantum-computing\/","title":{"rendered":"Use cases for quantum computing"},"content":{"rendered":"\n

QURECA would like to acknowledge Quantum Business Europe,<\/a> and more specifically Bruno Fedrici, Arthur Wolgust, and Adeline Velnon, for their research which forms the basis of this article.<\/em> <\/p>\n\n

The New York Times heralds that, \u201cQuantum Computing Is Coming, Bit by Qubit<\/strong>\u201d [1]; the Guardian touts, \u201cthe new space race<\/strong>\u201d [2]; and Le Monde speaks of, \u201cLe futur au rythme du Quantum Computing<\/strong> (the future at the pace of Quantum Computing)<\/em>\u201d [3]. Yet in spite of all this chatter about the merits of quantum computers few in the media have actually stopped to ask how this technology might manifest? With this in mind, Quantum Business Europe\u2019s – Quantum Computing Use Cases Reports offer us some insight. <\/p>\n\n

Transportation and energy sectors<\/strong><\/p>\n\n

The mobility sector faces a considerable refashioning, not least because of an increase in road traffic expected in growing markets. Quantum computers are likely to improve the accuracy and resolution of traffic flow analysis. They might help individuals find the optimal route in constrained environments; predict congestion, and aid in the adjustment of driving parameters, such as traffic signals, to ease said holdups; as well as provide real time insight to road operators about driving patterns, enabled in theory by the \u2018big data\u2019 generated by connected cars. <\/p>\n\n

Take Volkswagen who used D-Wave\u2019s quantum annealer to help Lisbon taxi and transport companies make informed decisions about where and when they should be in situ, and with how many vehicles. The transport business may also task quantum computers to help develop cutting-edge solid-state batteries. <\/em>IMB and Daimler began to explore this possibility following research that showed it was possible to calculate the dipole moment of lithium-containing molecules using a quantum computer of less than fifty qubits. By modeling new chemical arrangements, newer batteries that are more powerful, longer lasting, and more affordable, might emerge. <\/p>\n\n

This new approach to material science also applies to the aerospace industry. There, quantum computers help to manage the burden of fluid dynamic simulations<\/em> and assist engineers in improving the accuracy of flight models.<\/em> Typically resource heavy computing environments are streamlined by the data chomping benefits of quantum computers. In this instance optimisation is key; something that is much the same in the creation and distribution of energy resources. Here quantum computers might increase overall grid efficiency: \u201cglobal energy usage has risen in recent years, fueled by a near doubling of energy consumption in China since 2004, the global proliferation of energy-hungry connected devices, and increasing reliance on massive data centers that store and transmit digital information. This is placing tremendous pressure on power companies to meet growing usage demand while cost-effectively managing a rapidly evolving energy grid comprising multiple types and sources of energy.\u201d [4]\n\n

Chemistry and Pharmaceuticals<\/strong><\/p>\n\n

The realm of chemistry and pharmaceuticals is also not immune from the reach of the quantum computing revolution. The chemicals and drugs life cycle will be significantly enhanced by computational abilities of quantum computers. It will enable scientists to design molecules and solid materials with required properties, as well as help to define the shape of proteins to make better active ingredients<\/em>. Where chemists struggle to model complex molecules they can rely on approximation methods to solve chemical equations and in future should be able to use quantum computing to derive accurate simulations. <\/p>\n\n

Quantum computing could help in discovering more effective formulations by modeling how ingredients affect processes or how complex mixtures behave. <\/em>Pharmaceutical companies could for instance use quantum computing simulation to predict how a potential drug molecule will bind to a specific target protein. <\/p>\n\n

\u201cEventually, quantum computing could permit end-to-end in silico drug discovery, reducing the need for costly and time-consuming in-vitro testing.\u201d [5] <\/p>\n\n

In the production of medicines quantum computers also come into play, improving yields and suppressing byproduct generation through a better understanding of reactions and new catalysts<\/em>, as well as optimising problems in heat and mass transport.<\/em> Improvements to supply and production, though less glamorous, present cost and efficiency savings. <\/p>\n\n

Finance and Insurance<\/strong><\/p>\n\n

The financial sector, already heavily involved in quantum research, will likely gain greatly from the implementation of quantum computing technologies. <\/p>\n\n

Quantum optimisation algorithms will make portfolio optimisation faster and easier to tackle.<\/em> The mathematical framework for assembling a portfolio of assets is essentially a hard computational problem where, the larger data set, the harder it is for classical computers to arrange assets in a way where the expected return is maximised for a given level of risk. Quantum computers make this task easier and can provide asset managers with stronger portfolios – quicker. <\/p>\n\n

Monte Carlo methods are used in risk analysis. Though effective, the computing power needed to provide high accuracy remains out of reach for most in the financial industry. Quantum computing provides a quadratic speed-up of Monte Carlo methods.<\/em> Risk analysis represents a very good example of where quantum computers can be applied to real world problems.<\/p>\n\n

\u201cThe acceleration provided by quantum computing may in the long term reduce calculation time from overnight to near-real time or from days to hours, respectively.\u201d [6] <\/p>\n\n

Quantum driven algorithmic trading will use quantum machine learning to gain an advantage in high-frequency trading. <\/em>Machine learning has shown its usefulness handling the large volumes of historical financial data. When combined with quantum information processing, quantum machine learning unlocks the tasks which previously took thousands of man hours to complete. The acceleration in computing helps not just speed up transactions but equally enhances tasks like fraud detection, credit scoring, and loan \/ insurance underwriting. <\/p>\n\n

When your business wants to think quantum – think QURECA<\/strong><\/p>\n\n

Quantum computing represents a significant leap forward in processing ability. Its impact is far reaching and will likely benefit sectors far beyond those outlined in this blog. When your business is ready to consider what quantum technologies mean for them, turn to QURECA and our experience at the helm of this industry.<\/p>\n\n

Contact us: http:\/\/www.qureca.com\/contact-us-qureca-quantum\/ <\/a> <\/p>\n\n

References:<\/strong><\/p>\n\n[1] Dennis Overbye – The New York Times, Quantum Computing is Coming, Bit by Qubit, 2019 – https:\/\/www.nytimes.com\/2019\/10\/21\/science\/quantum-computer-physics-qubits.html<\/a> <\/p>\n\n[2] The Guardian Editorial, The Guardian view on Quantum Computing – the new space race, 2017 – https:\/\/www.theguardian.com\/commentisfree\/2017\/dec\/29\/the-guardian-view-on-quantum-computing-the-new-space-race<\/a> <\/p>\n\n[3] Le Monde Editorial, Le Futur Au Rythme du Quantum Computing, 2017 – https:\/\/www.lemonde.fr\/trajectoires-digitales\/article\/2017\/09\/22\/le-futur-au-rythme-du-quantum-computing_5189629_4887831.html<\/a> <\/p>\n\n[4] Bruno Fedrici, Arthur Wolgust, Adeline Velnon, Quantum Business Europe, Quantum Computing Use Cases: Applications in transportation and energy – https:\/\/www.quantumbusinesseurope.com\/download-our-guides\/<\/a> <\/p>\n\n[5] Bruno Fedrici, Arthur Wolgust, Adeline Velnon, Quantum Business Europe, Quantum Computing Use Cases: Applications in chemistry and pharma – https:\/\/www.quantumbusinesseurope.com\/download-our-guides\/<\/a> <\/p>\n\n[6] Bruno Fedrici, Arthur Wolgust, Adeline Velnon, Quantum Business Europe, Quantum Computing Use Cases: Applications in finance and insurance – https:\/\/www.quantumbusinesseurope.com\/download-our-guides\/<\/a> <\/p>\n","protected":false},"excerpt":{"rendered":"

QURECA would like to acknowledge Quantum Business Europe, and more specifically Bruno Fedrici, Arthur Wolgust, and Adeline Velnon, for their research which forms the basis of this article. 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