Top 9 Applications of Quantum Computing In 2024
The Most Powerful Applications of Quantum Computing
Although the first quantum computer was built in 1998, quantum computing has only recently become a household term. Thanks to leaps in quantum development, such as Google’s quantum computing breakthrough and the development of quantum networks, quantum computing is generating quite a buzz.
With the potential to revolutionize fields, such as cybersecurity, and the ability to handle both larger and more complex problems than classical computers, many fields and professions stand to benefit from further development in the quantum space.
Unlike classical computing, which uses binary bits to transmit data in a series of 0s and 1s, quantum computing uses qubits (quantum bits). Qubits are different from binary bits in that they can represent 0, 1, or a superposition of 0 and 1. Qubits are also unlike bits in that they can be entangled with other quantum bits and be purposefully introduced to interference in order to affect measurement.
The more complex properties of qubits when compared to classical bits allow quantum computers to handle larger and more complex problems than classical computers. Today, we will explore some of the fields which will be affected by quantum computing.
Top 9 Quantum Computing Applications in 2024
1. Quantum Cryptography and Secure Communications
One of the most exciting, and startling, applications of quantum computing is in cybersecurity, especially in the field of cryptography. The sheer computing power of quantum brings risks regarding brute-force attacks, and the ability to break current encryption methods used to protect data. However, the rewards outweigh the risks when it comes to quantum computing and cybersecurity.
Whether it is in transit or at rest, protecting personal and company data is at the heart of most cybersecurity concerns. One way this is done is through encryption, which uses digital keys to scramble and unscramble data. Encryption helps maintain security by ensuring that even if a threat actor — a person or group who intentionally harms digital devices and symptoms — were to gain access to data, they would not be able to read or use it.
Encryption uses mathematical algorithms, and modern encryption is relatively safe from brute-force attacks due to the sheer number of possible guesses. In many cases, it would take a classical computer hundreds or even thousands of years to break encryption.
The processing power available in quantum computing has brought rise to concerns that even our modern algorithms may not be enough to withstand brute-force attacks in the age of quantum. However, quantum computing will also lead to the development of new, stronger quantum algorithms that will be more resistant to brute-force attacks.
Another aspect of encryption that will be affected by quantum is the exchange of keys required to encrypt and decrypt data. Even if a threat actor manages to gain access to encrypted data, it is unlikely they will be able to use or view the data without access to at least one of the keys. Although key exchange is one of the best tools we have, it is vulnerable to a variety of exploits, including man-in-the-middle attacks.
Quantum Key Distribution (QKD) is another function of quantum computing that will improve cybersecurity and data protection. QKD systems use authentication at the same time at both ends of the key exchange, which makes many of the exploits available to current key exchange processes unlikely in QKD.
Although QKD and quantum algorithms are still in development, cybersecurity and quantum experts anticipate that these fields will be some of the first to be impacted by quantum computing.
2. Optimization and Operations Research
Other industries that will see significant changes from quantum computing include logistics, finance and supply chain management. Each of these industries relies on massive amounts of data that grow daily as the industries become more complex and more processes move online.
Unthinkable amounts of data are required for these tasks, from tracking the location of shipping boats in the Suez Canal to banking transactions from companies around the globe, maintaining the most cost-effective route, choosing the best investments, or creating the most up-to-date plan for global freight.
Many of these industries rely on optimization methods to identify the most efficient way of solving problems within the field. From finding high-yield, low-risk investments to determining how best to maintain a supply route in the face of disruption, quantum computing can process larger amounts of data more readily and more quickly than classical computing.
Already, quantum computing is being investigated for data analytics issues, such as predicting customer behavior. This could be used to optimize ads for maximum impact with minimum spend, an issue many brands struggle with. As quantum computing continues to develop, more opportunities for optimization will undoubtedly arise.
3. Drug Discovery and Material Science
Pharmaceutical research and material sciences stand to gain significantly from quantum computing as well. After quantum computing has matured, experts in the medical and computing industries anticipate augmenting current research methods with quantum computing in order to discover new molecules, decode and predict changes in proteins, or develop new treatment protocols through machine learning.
With current computing methods, discovering and testing new drugs can take over 10 years and more than 2 billion dollars on average. This is because pharmaceutical research requires lengthy trial and error testing, which relies on error-prone technology such as X-ray, and due to the complexities of developing clinical trials.
Quantum computing will likely affect the accuracy of testing due to improved quantum sensing in medical equipment, which may augment or replace traditional technology. It is also anticipated to impact the length of clinical trials, which require a period of time in which researchers make use of artificial intelligence (AI) and machine learning (ML) to effectively select patients and divide them into subgroups for testing.
Quantum computing can work through processes with more variables than classical computing, making it more effective at creating subgroups of patients and choosing patients for clinical trials. Quantum computing can also help researchers create simulations of patient outcomes before clinical trials in order to further increase their effectiveness.
4. Machine Learning and AI
Artificial Intelligence (AI) and Machine Learning (ML) are already making huge leaps in development and application. From generative chat AI like ChatGPT to generative image development like DALL-E, AI is becoming a household term. However, as AI continues to develop, the amount of computing power it requires also increases.
Further development of AI models is limited by the amount of data that classical computers can process in a timely manner, which can lead to under-fitting in large models, making AI predictions and outcomes less accurate. The limits of classical computing when it comes to data processing and algorithms will eventually stall the development of further AI.
Quantum computing can circumvent many of these issues, allowing more complex, “smarter” AI to develop.
AI and ML are taking hold in industries such as pharmaceuticals, aerospace, industrial machining, biomedical sciences, telecom and more. By improving on AI and ML processes already in use, and by developing new forms of artificial intelligence and machine learning, quantum computing will likely help decrease time to market (TTM) for autonomous vehicles, improve the accuracy of clinical trials for medications. Other applications include assisting financial institutions with detecting and fighting fraud and improve cybersecurity software by detecting abnormal network activity and network intrusions more effectively than existing software.
5. Quantum Simulation
Many scientific fields rely on classical computing models to explain how quantum systems (the properties of subatomic particles) work. Due to the nature and unpredictability of these particles, our current computing systems are unable to accurately reproduce and model their behavior.
However, since quantum computing utilizes qubits and can exist in multiple states at once, it will be able to create accurate, usable models of quantum systems. These models may help provide answers to questions regarding the nature of the universe, as well as provide us with further insight into many math and physics problems we do not fully understand.
Quantum simulation has the potential to improve calculations on fluid dynamics for fields such as aerospace, as well as assist with the discovery of new drugs for pharmaceutical companies. The advances in materials development that quantum offers will help us discover new molecules and compounds for more than just pharmaceuticals, however.
This can also affect the energy industry, as quantum simulation may lead to the development of better batteries and other energy storage technology. Quantum simulation is unlikely to completely replace traditional simulations but will augment and enhance current classical computing methods.
6. Financial Modeling and Risk Analysis
As mentioned earlier, the finance industry has high hopes for the effects of quantum computing. The impact of quantum on finance stands to range from improving the optimization of investment portfolios to creating more accurate financial models for company outlook.
With quantum computing’s advancements in modeling, AI and ML will allow analysts to consider more data points accurately when creating financial models for businesses, banks and the stock market. Current models also stand to improve from the increased speed that quantum computing can bring to analytics.
These benefits extend to risk analysis, which is an integral part of the financial sector. A traditional risk assessment using the Monte Carlo simulation can take days. With quantum computing, this time could become mere hours.
These faster risk assessments can be undertaken more often than a traditional risk assessment, helping protect a bank’s investments and providing more accurate results than one that is performed less often. Quantum AI can also help with these simulations by improving the quality of data chosen for assessments.
7. Supply Chain Optimization
Whether or not you were aware of the global supply chain before 2020, you’ve probably become more familiar with it in recent years. From infamous shortages to increased prices on everything from household staples to new and used cars, disruptions in the supply chain can affect everyone.
Even the best computers struggle to process and comprehend the data from an ever-growing global supply chain, which relies on factors such as weather, geopolitical unrest and buying trends around the globe.
Supply chain experts look to quantum computing as an important piece of the puzzle when it comes to solving for and mitigating future disruptions, with an anticipated savings of around 1 billion dollars per year. It is believed that quantum simulations and quantum AI will help solve the issues with classical computing’s comprehension of supply chain networks, although this will be dependent on the accuracy and availability of supply chain data.
8. Quantum Sensing and Metrology
Quantum sensing is another application of quantum computing that has a lot of buzz around it. At its core, quantum sensing is a way to detect changes and collect data at an atomic or subatomic level.
This can have impacts on medical science, allowing doctors to collect more accurate information for diagnoses, assist in the development of better
Global Positioning System (GPS) devices, and improve navigation and guidance systems for underwater and aerospace vehicles. By measuring the changes in atoms with a high degree of accuracy, quantum sensing will unlock better ways of detecting and sensing minute changes and subatomic particles.
9. Quantum Manufacturing
Manufacturing is a field with a high likelihood of being affected by the quantum revolution. There are many ways quantum computing may augment manufacturing processes, including design, quality control and materials discovery.
Many of these processes already use AI and machine learning to optimize and perform complex tasks and modeling, and more complicated manufacturing processes already test the bounds of modern computing.
With the addition of quantum computers, these tasks will be simplified and customized. This will allow for more accurate and customized manufacturing, which can in turn lead to improvements in processes such as the development of new vehicles, batteries and more.
Future Applications of Quantum Computing
Quantum computing is an exciting technological development poised to impact a wide variety of fields and industries. From chemistry to aerospace engineering to the stock market, it is impossible to overstate the potential that quantum computing brings to the table.
Quantum computing is still developing, so there are likely many applications that we cannot yet imagine. There will no doubt be many exciting discoveries to come as organizations, schools, and companies across the globe race to develop the future of quantum computing.
The EPB Quantum NetworkSM launched in 2022 and was designed to generate, distribute and measure qubits across an established fiber optic network. The network is available to both public and private sectors who want to run existing applications, test new quantum technologies or validate equipment performance. Learn more about the EPB Quantum Network.
