Quantum Computing Use Cases

Pharmaceuticals · chemistry

Using hybrid quantum-classical methods to accelerate drug discovery by simulating molecular interactions more accurately than classical methods alone.

Cybersecurity · cryptography

Transitioning critical infrastructure and communication systems to quantum-resistant cryptographic algorithms to protect against future quantum computer attacks.

Aviation · logistics

Quantum algorithms are applied to the aircraft loading problem — optimizing cargo placement while respecting weight, balance, and safety constraints. Demonstrations on IonQ trapped-ion processors have found optimal solutions for problem instances up to 28 qubits, addressing a challenge originally posed by Airbus.

Energy · energy

Quantum algorithms are being developed to simulate lithium-ion battery materials with higher accuracy than classical methods, targeting key properties such as cell voltage, ionic mobility, and thermal stability. These simulations could accelerate the discovery of next-generation battery chemistries for electric vehicles and grid storage.

Energy & Environment · energy

Quantum computing is being used to model the molecular interactions between CO2 and Metal-Organic Frameworks (MOFs), a leading class of materials for scalable carbon capture. Quantinuum and TotalEnergies have demonstrated VQE-based simulations of CO2 adsorption on aluminum fumarate MOFs.

Climate & Sustainability · simulation

Quantum computing and quantum machine learning are being applied to optimize multi-infrastructure systems for reduced greenhouse gas emissions across energy, logistics, and industrial sectors. McKinsey estimates that identified quantum computing use cases could eliminate over 7 gigatons of CO2 equivalent annually by 2035.

Energy & Chemistry · chemistry

Quantum and quantum-inspired computing methods are accelerating the discovery of catalysts for water electrolysis, a key process in green hydrogen production. Researchers have used quantum-inspired optimization to discover new catalyst families with mass activity eight times higher than state-of-the-art materials.

Finance · finance

Applying quantum amplitude estimation to credit risk analysis, enabling faster computation of Value at Risk and economic capital requirements compared to classical Monte Carlo methods. Research demonstrates quadratic speedups for estimating loss distributions across large credit portfolios.

Finance · finance

Quantum amplitude estimation enables quadratic speedups in pricing financial derivatives such as options and exotic instruments. Multiple research groups have demonstrated quantum algorithms for European, Bermudan, and multi-asset option pricing that outperform classical Monte Carlo in asymptotic scaling.

Finance · finance

Using quantum machine learning classifiers to detect fraudulent financial transactions. Variational quantum classifiers and quantum support vector machines have shown competitive or improved classification performance compared to classical methods on credit card fraud datasets.

Cybersecurity & Telecom · cryptography

Quantum Key Distribution (QKD) networks use quantum mechanical principles to generate provably secure encryption keys between distant parties. The EU's EuroQCI initiative, funded at 340 million euros, is building a pan-European QKD infrastructure spanning all 27 member states with both terrestrial fiber and satellite links.

Technology · machine-learning

Leveraging quantum kernel methods and variational quantum classifiers to enhance machine learning tasks, potentially offering computational advantages for specific classification problems.

Materials Science · chemistry

Using quantum simulation to design novel materials including battery electrodes, catalysts, and semiconductors by accurately modeling electronic structure at the quantum level.

Finance · finance

Applying quantum optimization algorithms to financial portfolio selection, aiming to find optimal asset allocations faster than classical solvers.

Manufacturing · logistics

Quantum and hybrid quantum-classical solvers are being applied to production scheduling problems in manufacturing, including flexible job shop scheduling and chemical reactor assignment. Real-world benchmarks at BASF show D-Wave hybrid solvers achieving competitive results with classical methods.

Pharmaceuticals · chemistry

Quantum algorithms are being developed to simulate protein folding, a fundamental problem in structural biology and drug design. Recent experiments on trapped-ion quantum processors have tackled protein folding for up to 12 amino acids, representing the largest quantum hardware implementations reported to date.

Cybersecurity · cryptography

Quantum Random Number Generators (QRNGs) exploit the inherent randomness of quantum mechanical processes to produce true random numbers for cryptographic key generation, Monte Carlo simulations, and security protocols. European company ID Quantique produces the first QRNG chips to receive NIST Entropy Source Validation certification.

Manufacturing · optimization

Applying quantum computing to optimize complex multi-tier supply chains, including supplier selection, inventory management, production scheduling, and distribution network design.

Telecommunications · optimization

Quantum optimization algorithms are being applied to telecommunications network planning problems including cell identifier assignment, spectrum allocation, and base station placement. TIM Telecom Italia has demonstrated QUBO-based optimization of Physical Cell Identifier planning for 4.5G and 5G networks on D-Wave quantum hardware.

Logistics · logistics

Applying quantum optimization algorithms to solve complex vehicle routing problems, enabling more efficient fleet management and delivery route planning.

Logistics · logistics

Quantum annealing is being applied to warehouse layout and storage assignment problems, optimizing product placement to minimize picking times and robot travel distances. Real-world industrial tests show quantum approaches achieving comparable quality to classical solvers with significant computational time savings.

Climate & Meteorology · simulation

Quantum machine learning and quantum simulation algorithms are being explored for weather and climate prediction, with quantum neural networks showing potential to outperform classical recurrent neural networks for wind speed prediction. Quantum PDE solvers have successfully simulated atmospheric vorticity dynamics with high accuracy.

Energy · energy

Using quantum optimization to manage complex energy distribution networks, balance renewable energy sources, and optimize grid stability in real-time.