Arline Benchmarks platform allows to benchmark various algorithms for quantum circuit mapping/compression against each other on a list of predefined hardware types and target circuit classes
metriq-gym is a framework for implementing and running standard quantum benchmarks on different quantum devices by different providers
In this work, we use LR-QAOA protocol as an easy-to-implement scalable benchmarking methodology that assesses quantum processing units (QPUs) at different widths (number of qubits) and 2-qubit gate depths.
Python code to run the Q-score (Max-Cut and Max-Clique) benchmark on various backends
Web application and API powering the Metriq platform
Metriq Platform website
An Execution-Level Benchmark Suite for Quantum Software Engineering
Surrogate benchmark for QAS. Includes code, datasets, and tools for fast evaluation and integration into custom QAS pipelines.
A Python replication of the study on noise-adaptive transpilation, using Qiskit and the SupermarQ benchmark to evaluate quantum algorithm performance across different optimization levels.
Quantum Circuit Simulator Benchmark Tool
Reproducible evidence, methodology, and regression validation for the QONTOS platform.
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