Some of the biggest challenges facing our world today rely on complex computations, many of which today’s classical supercomputers are simply incapable of solving. This means that we are currently forced to guess at solutions or are prevented from solving them altogether. Quantum computing promises to overcome these bottlenecks in computation, affecting countless industries in advancing research and delivering innovative products.
Quantum computers are poised to revolutionise machine learning by handling computations far beyond the reach of classical systems. Quantum machine learning (QML) leverages the unique properties of qubits to process and analyse information in ways that can reveal patterns faster and more efficiently.
This could accelerate tasks like training deep learning models, optimising large-scale systems, and improving predictive analytics across industries like healthcare, finance, and cybersecurity. By combining the power of quantum computing with machine learning, organisations can unlock more powerful AI capabilities.
Quantum computers offer powerful new tools for solving optimisation problems that are too complex for classical computers to solve. Many real-world challenges faced by organisations involve the search through enormous numbers of possibilities to find solutions – including use cases like scheduling, supply chain logistics, portfolio management, and traffic routing.
Quantum algorithms can explore these possibilities faster and more effectively than conventional computers, identifying optimal or near optimal solutions at unprecedented speed. This empowers organisations to reduce costs, improve efficiency, and make smarter decisions. By applying quantum computing to optimisation, businesses can gain a strategic edge in tackling these once-intractable problems
One of the most promising applications of quantum computing is in materials science, where quantum computers will enable simulations of molecules and chemical reactions with unprecedented accuracy. While classical computers struggle to model the quantum behaviour of even moderately complex molecules, quantum systems can naturally represent these interactions at the atomic level.
This opens the door to new breakthroughs in drug discovery or energy research – such as designing new catalysts, optimising for better batteries, or the development of new medicines. Through quantum computing, organisations in these fields can accelerate innovation, reduce costly trial-and-error experiments, and uncover new solutions to critical challenges.
Partial differential equations, or PDEs, are at the heart of modelling real-world systems in applications like finance, physics, and engineering. Classical methods for solving PDEs can be extremely resource-intensive, especially when solving high-dimensional or nonlinear problems.
Quantum algorithms run on powerful quantum computers can explore solution spaces far more efficiently.. This means faster and more accurate simulations of fluid dynamics, climate systems, materials science, and risk modelling – unlocking insights that were previously impossible or impractical using classical computers
Quantum computers are set to transform the field of cryptography by both challenging and strengthening digital security. As initially demonstrated in 1994 with Shor’s algorithm, fault-tolerant quantum computers will have sufficient computational power to break widely-used encryption methods, including RSA-2048.
Yet quantum computing is already driving the development of quantum-safe cryptography to be used by defenders – including new encryption techniques designed to withstand quantum attacks and new quantum-protected communication channels. By exploring quantum applications in cryptography, enterprise organisations and governments alike are better understanding the risks of a post-quantum world and adopting innovative methods to safeguard digital assets.
