Quantum Computing
Definition
Computing technology that uses quantum mechanical phenomena to perform calculations exponentially faster than classical computers for certain problems.
Use Cases
- Volkswagen: Traffic flow optimization and route planning — Worked with quantum computing partners to prototype optimization approaches (including quantum-inspired and quantum algorithms) for routing scenarios and evaluate them against classical methods. (Demonstrated feasibility of using quantum approaches for complex routing/optimization prototypes; helped inform future R&D on scaling optimization methods.)
- JPMorgan Chase: Financial modeling and risk analysis research (e.g., option pricing and portfolio-related computations) — Conducted quantum algorithm research and experiments using cloud-accessible quantum hardware and simulators to test techniques such as quantum amplitude estimation and other methods relevant to finance. (Produced research insights and proof-of-concept experiments; advanced internal understanding of where quantum may provide future advantage, though most workloads remain classical today.)
- BMW Group: Manufacturing and logistics optimization (e.g., production planning and supply chain-related optimization research) — Collaborated with quantum technology providers and cloud platforms to explore quantum and quantum-inspired optimization workflows, typically starting with simulators and small hardware runs. (Generated prototypes and benchmarking data to evaluate potential benefits and constraints; supported longer-term innovation planning rather than immediate production replacement.)
Provider Equivalents
- AWS: Amazon Braket
- Azure: Azure Quantum
- GCP: Google Cloud quantum computing via partners (e.g., Quantinuum) and Google Quantum AI (research; limited direct cloud product)
Frequently Asked Questions
- What's the difference between Quantum Computing and classical computing?
- Classical computers use bits that are either 0 or 1. Quantum computers use quantum bits (qubits) that can represent combinations of 0 and 1 and can be linked through quantum effects. This can make some types of problems—especially certain optimization, simulation, and cryptography-related tasks—potentially faster, but it does not make all computing faster.
- When should I use Quantum Computing?
- Use quantum computing when you have a problem that is a known candidate for quantum advantage (or strong research progress), such as certain optimization problems, quantum chemistry/materials simulation, or specific sampling/linear algebra subroutines—and when you can tolerate experimentation. For most business applications today, start with a proof of concept using simulators and small hardware runs, and compare against strong classical baselines (including GPU and specialized solvers).
- How much does Quantum Computing cost?
- Costs depend on (1) whether you use a simulator or real quantum hardware, (2) the provider and device type, (3) how many shots/iterations you run, (4) circuit complexity and runtime limits, and (5) data transfer and orchestration costs in the cloud. In practice, teams often spend modest amounts on early experiments (simulators and limited hardware time) and more on engineering time, algorithm development, and benchmarking than on raw quantum compute.
Category: emerging
Difficulty: advanced
See Also