Benchmarking
Our goal is to provide independent, unbiased benchmarking to provide best value to our clients.
- Hardware capabilities: single and multiple qubit failure rates
- Performance scaling and error mitigation on NISQ
- Integration into classical HPC workflows
- Recommendation for best hardware and algorithm solutions for specific domains
Recent posts:
- Quantum Economic Development ConsortiumApplication-Oriented Performance Benchmarks for Quantum Computing
- QMC methods- MontanaroClassic paper from A. Montanaro on quantum speedup of Monte Carlo methods.
- On implementing quantum Monte Carlo integrationPublished paper concerning quantum Monte Carlo integration on near-term quantum computers.
- Google surface codePublished paper from Google using a surface code to reduce quantum errors. They vary the size of the code and extract error budgets to highlight challenges going forward.
- SupermarQPublished paper from Princeton/University of Chicago about a proposed benchmark suite for quantum hardware.
- IonQ 11-qubit benchmarkPublished paper from IonQ, Inc about their 11-qubit quantum computer. Single and two qubit fidelities and SPAM errors. Includes two simple algorithms: Bernstein-Vazirani and Hidden Shift.