However, these applications are envisioned only on a theoretical level and multiple industries are currently experimenting with the technology and trying to find use-cases. Chad Rigetti mentions that “Quantum machines today are able to run basic programs, but they’re not yet at the level of performance or scale for commercially relevant problems.”50
Check out the database: “Companies in various industries currently implementing quantum technologies”
Cryptography and data security
Cryptography and data security
Perhaps one of quantum computing’s most widely discussed and commended applications is the development of Quantum Cryptography or the Quantum Key Distribution (QKD). Cryptography (the ability to exchange information between two users in a way that cannot be understood by other parties) significantly impacts all communication, be it between customers and companies, business partners, or governments. All industries, from finance, aerospace and defense, and healthcare to telecom and distribution, encrypt their communications using the AES (Advanced Encryption Standard) with a minimum key length of 128 bits (usually 256 bits) or the RSA cryptosystem. However, government agencies and some private companies already use stronger encryption keys.51
Based on the principles of quantum physics, quantum cryptography aims to protect and secure the distribution of encrypted messages.
According to quantum laws, any attempt to measure or observe quantum information leads to transmission perturbations and errors, a feature that alerts the communication partners to the presence of a potential eavesdropper. By creating a quantum channel that can be used in conjunction with conventional channels and exploiting certain principles of quantum mechanics,52 QKD allows for securing the communication channel between users.
However, since the main function of the QKD is to withstand potential quantum attacks, it cannot currently be tested accurately, given that quantum computers can’t be used to generate the attack yet. Therefore, all tests are done on simulators, and modeling processes run on conventional computers.
Infineon, a German company based in Munich, successfully implemented post-quantum cryptography on a contactless security chip in 2017; Mitsubishi is also performing research in the field of quantum cryptography and quantum technologies to protect the confidentiality of phone conversations.
CraftProspect, a company based in the UK, conducted the Responsive Operations Key Services In Orbit Demonstration (or ROKS IOD) mission in order to test and develop the necessary technologies for the use of QKD in space.
Finance
Finance
The financial sector deals with complex problems, uncertainty, and volatility. On one side, customers are demanding more personalized financial services and solutions, while traditional computation systems face difficulties integrating the sheer amount of behavioral data and environmental impact factors in order to provide customized alternatives in a timely manner. The complexity of trading activities is constantly increasing, further compounded by regulatory demands and validation processes53.
Risk assessments have to take into consideration an increasing number of factors, while methods for risk impact analysis such as The Monte Carlo Simulation might soon exceed the computational capabilities of conventional devices. For successful portfolio optimization, a high number of variables should be taken into consideration, from economic fluctuation, power distribution between competitors, company history, and performance indicators to social and political events. Therefore, quantum computers are considered to be a suitable option for dealing with these types of data and problems and for rapid analysis of multiple scenarios.
IBM believes that quantum computing could help in terms of targeting and prediction, trading optimization, and risk profiling. Therefore, this technology has the potential to increase gains from investments while simultaneously reducing the infusion of capital required.54 In this regard, IBM has already developed an option-pricing simulator and an algorithm to improve AI classification accuracy. Jerome Sandrini, VP and Head of Big Data for Atos North America, has stated that quantum computing’s predictive capabilities, combined with artificial intelligence, will also accelerate and enhance high-frequency trading and diminish the effects of stock market volatility.
Nomura Securities, a Japanese brokerage firm, explores quantum applications for financial portfolio optimization. Dutch bank ABN AMRO, in collaboration with QuTech, works on testing various ways to make online and mobile banking operations more secure. The Future Lab for Applied Research and Engineering (FLARE), a program within JPMorgan Chase, has already published several papers presenting approaches to using Honeywell’s quantum computer for complex mathematical calculations and financial trading applications.
However, Christa Zoufal, a member of the IBM Research Team in Zurich, estimates that in order to run such applications and solve these types of problems, quantum computers would need around 1,000 qubits and a low error rate.55 Current capabilities are nowhere near that stage yet.
Chemistry and material development
Chemistry and material development
Advancements in the area of chemistry have been limited by the computational power of conventional systems. Molecular simulations are very important here because they allow researchers across various fields to understand complex processes and interactions that take place at an atomic level and that aren’t always accessible via experiments.
Simulating chemical interactions between molecules is already being done on traditional devices, on supercomputers, and with the help of Artificial Intelligence, but scientists believe that quantum computers will be capable of tackling problems with a much higher degree of complexity. If quantum computers achieve their envisioned potential, it is expected that these devices will be capable of modeling interactions involving 50 to 150 atoms, opening up a huge array of possibilities in terms of applications.
One of the most eagerly anticipated applications would be the solving of the FeMoco problem (understanding and replicating the process through which tiny organisms carrying the FeMoco molecule fix nitrogen in the soil). This would help reduce the volume of natural gas currently needed to produce artificial fertilizers,56 which would have a huge environmental impact. Other expected applications would be in the field of new material development (e.g., more efficient materials for solar cells) and battery cell research.
Although they are not very robust yet and somewhat prone to errors, current quantum devices can already model molecular configurations. After accurately simulating a molecule for the first time in 2016,57 Google managed to simulate a chemical reaction in 2020.58
Manufacturing and logistics
Manufacturing and logistics
In the manufacturing sector, “advanced manufacturing” refers to the use of innovative and cutting-age technology to develop products and processes. Quantum technology is useful in this context because manufacturing often involves vast amounts of complex data and a huge array of variables. Quantum computers can help solve typical manufacturing problems such as finding the fastest route between multiple points while taking into consideration various limitations, creating efficient transportation networks that minimize congestion, and efficient use of existing resources. Benefits include better product quality, higher production speeds, and the ability to scale up more rapidly to a higher production volume.60
In terms of logistics, quantum computers are seen as having a substantial impact on supply chain management, where they can help with finding the optimal distribution path, routing warehouse robots for maximum efficiency and resource utilization, and providing real-time solutions for unexpected changes in the environment.
Applications in this area could go beyond factories and supply chains and help with problems caused by natural disasters or other major unexpected events. Tohoku University in Japan is already modeling a tsunami evacuation plan, while other Asian companies are using this technology to develop plans for efficient mobilization in case of earthquakes.
Tina Sebastian, Supertrends expert and CEO of Quacoon, works with companies in the manufacturing sector to help them harness the power of quantum computers in order to optimize supply chains and improve traceability. Adjusting to sudden and unexpected changes in the environment currently requires human intervention as well as intensive pen-and-paper labor to recalculate schedules, minimize downtime, and re-establish the previous level of productivity. Sebastian is convinced that quantum technology can be invaluable in these types of situations by recalculating the major parameters in real time and minimizing losses.
Pharma and medicine
Pharma and medicine
Cynthia Pussinen, Vice President of Honeywell and General Manager of Life Sciences and Specialty Chemicals, states that “it takes 10 to 13 years and more than $2.5 billion to bring a new medical therapy from the discovery bench to the patient […] and the odds of success are overwhelmingly weighted in favor of failure.”61
Because the structure of the molecules can also predict the effects of a drug, companies are trying to implement a process called “molecular matching” in order to speed up the drug screening process. This involves finding a binding energy for molecules, determining the most efficient chemical transition, and predicting which compounds will be active for a series of chosen receptors. While very time-consuming for regular computers, these calculations could be done much faster on a quantum computer, which would also allow for simultaneous processing of vast quantities of data while taking into consideration even more factors and interactions than classical computers can currently handle.
In July 2020, Stefan Bekiranov, a researcher at the University of Virginia, developed an algorithm aimed at studying genetic diseases by harnessing quantum properties. This algorithm was tested on IBM’s quantum computers, but still higher computing power and advanced quantum computers will be required to return meaningful results. “The new algorithm essentially classifies genomic data. It can determine if a test sample comes from a disease or control sample exponentially faster than a conventional computer. For example, if they used all four building blocks of DNA (A, G, C or T) for the classification, a conventional computer would execute 3 billion operations to classify the sample. The new quantum algorithm would need only 32.”62
Similar applications geared towards precision quantum medicine have also been proposed by David Sahner in collaboration with the producer of quantum devices D-Wave.64 The potential process and outcomes may be represented as follows:
Automotive and transportation
Automotive and transportation
Transportation is one of the most suitable areas for quantum computing capabilities because it involves many optimization problems. While employing quantum computers to reduce congestion and optimize processes inside airports and factories is a welcome improvement, quantum computers could even speed up the development of autonomous cars.
This type of vehicle will need to use artificial intelligence in order to operate independently, and this artificial intelligence has to be trained through complex processes, which require structuring and making sense of a vast array of data. This training process is another area where quantum computing could make a significant contribution.
Volkswagen is collaborating with D-Wave on finding solutions to optimize traffic flow and simulate battery behavior. Denso, a Japanese company, employs D-Wave machines for optimizing traffic flow and manufacturing processes. The German Aerospace Center, a German research institute that operates as an incorporated society, uses quantum computers in the aviation industry for air traffic management, satellite telemetry verification, gate flow management, and scheduling. In addition to the operational side, it uses quantum simulators for battery development and research.
Machine learning and artificial intelligence
Machine learning and artificial intelligence
Machine learning and the training of artificial intelligence systems are seen some of the major future applications of quantum computing. While machine-learning algorithms are already employed to deal with large quantities of data, quantum computing could increase these capabilities by allowing more complex problems to be processed, and at a higher speed.
Tony Uttley, President of Honeywell Quantum Solutions, explains that conventional devices and artificial intelligence could help with searching and extracting information from huge libraries of data (e.g., scans, MRIs, and X-rays), but the results will only rely on past information and events that were recorded by the system.
By introducing a quantum input, and due to its probabilistic nature, the new result might anticipate issues that could come up in the future.
Arbitration and politics
Arbitration and politics
By speeding up the training of various deep neuronal networks, quantum computing could help forecast election results, the potential outcomes of court disputes, the results of conflicts between world powers or political adversaries, etc. It is envisioned that this might help optimize the resolution of legal disputes and arbitration processes by providing insight into the potential outcome.
Amir Vahid, Supertrends expert and CEO and co-founder of Eonum, one of the few companies aiming to apply quantum principles in the legal field, mentions a few problems companies currently face when entering into a legal dispute, including extremely high trial costs for corporates and insurance companies, the fact that the information is static and soon outdated, and the difficulty of interpreting the massive amount of documents. By employing quantum principles, companies would be able to predict the court verdicts, trial costs, liability, and premiums, and decide their strategy based on live data, thus saving up to 40 percent of the costs.
Defense
Defense
The applications of quantum technology in the defense sector range from secure communication, precise navigation, and precise timing, to classic optimization problems. Because quantum computers can deal best with high uncertainty and multiple variables, they are considered suitable for logistics problems. They are expected to support more efficient decision making in rapidly changing situations in war zones or conflict situations.
Los Alamos National Security used a D-Wave quantum computer to explore the formation of global terrorist networks. Lockheed Martin – one of the largest US defense contractors with programs in aeronautics, information systems, missile and fire control, and space systems – also acquired a D-Wave quantum computer in 2010 aiming to reduce the costs of systems validation and verification.67
When it comes to using quantum technologies in the military and defense field, the world is dominated by the race between US and China, each country trying to surpass the other in terms of research investments, patents, and breakthroughs. China’s advancements in terms of long-distance communication, the development of a quantum radar, and a quantum submarine detector are seen by the US as a threat to its defensive and offensive strategies.
Other industries
Other industries
The telecommunication sector frequently faces problems related to resource allocation and planning. It is expected that quantum computing could help with network layout issues, job scheduling, configuration of overlapping cells, routing and wavelength assignment, malicious traffic flow propagation, etc.68 British Telecom is one of the leaders in this field, employing quantum computers for cell network optimization.
The ability of a quantum computer to deal with vast amounts of data in a short period of time, and most importantly, to take new variables into consideration in real time, might provide a very good solution for weather forecasting. Fast prediction of weather changes and the enhancement of weather modeling systems might prove valuable for many industries and for society in general, especially given the ongoing challenge of climate change.
However, contemporary quantum computers lack the capability and sophistication to carry out such complex operations. All these projections and aspirations reflect the “Holy Grails” that the respective industries hope to advance by using quantum computers. As quantum computers are scaled up in terms of size and capabilities, further complex operations will become possible.
References
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