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Application-Oriented Performance Benchmarks

The Quantum Economic Development Consortium (QED-C) Application-Oriented Performance Benchmark Repository.

 

Click: Here

A list of scientific papers produced by QED-C over the last 6 years:

 

The QED-C committee released its first paper (Oct 2021) describing the theory and methodology supporting this work at

 

Application-Oriented Performance Benchmarks for Quantum Computing

The QED-C committee released a second paper (Feb 2023) describing the addition of combinatorial optimization problems as advanced application-oriented benchmarks at:

Optimization Applications as Quantum Performance Benchmarks

The group added another paper (Feb 2024) with additional benchmark programs and improvements to the framework at:

Quantum Algorithm Exploration using Application-Oriented Performance Benchmarks

The group released a fourth paper (Sep 2024) and a fifth (Apr 2025) with a deep focus on measuring performance of Quantum Hamiltonians Simulations at:

 A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulationsand:

A Practical Framework for Assessing the Performance of Observable Estimation in Quantum Simulation

Recently, a sixth paper was produced by the 2025 summer intern group with a focus on integration with other benchmarking frameworks.

Platform-Agnostic Modular Architecture for Quantum Benchmarking

Sandia Quantum Performance Lab Papers

 

These papers provide some of the highest quality scientific perspective on the subject of assessing the performance of quantum computers

A Practical Introduction to Benchmarking and Characterization of Quantum Computers

Benchmarking quantum computers

Quantum Resources.

Quantum Computing Data™  conducts research in high-performance quantum computation, developing scalable simulation and benchmarking workflows that leverage modern HPC and GPU architectures. Our aim is to provide researchers and experimental teams with efficient, validated computational tools that accelerate scientific discovery, while reducing the need to construct or maintain complex infrastructure. 

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