Continuous Integration

Supermarq: A Scalable Quantum Benchmark Suite

Supermarq is a suite of application-oriented benchmarks used to measure the performance of quantum computing systems.

Installation

The Supermarq package is available via pip and can be installed in your current Python environment with the command:

pip install supermarq

Install Dev Requirements

This is required if you intend to run checks locally

pip install .[dev]

Using Supermarq

The benchmarks are defined as classes within supermarq/benchmarks/. Each application defines two methods; circuit and score. These methods are used to generate the benchmarking circuit and evaluate its performance after execution on hardware.

The quantum benchmarks within Supermarq are designed to be scalable, meaning that the benchmarks can be instantiated and generated for a wide range of circuit sizes and depths.

The Supermarq tutorial notebooks contain an end-to-end example of how to execute the GHZ benchmark using Superstaq. The general workflow is as follows:

import supermarq

ghz = supermarq.benchmarks.ghz.GHZ(num_qubits=3)
ghz_circuit = ghz.circuit()
counts = execute_circuit_on_quantum_hardware(ghz_circuit) # For example, via AWS Braket, IBM Qiskit, or Superstaq
score = ghz.score(counts)

Project links

Key dates

PyPI data
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  • Released:
Newer release available (0.5.68)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for vtomole from gravatar.com vtomole

Credits

Author: Superstaq development team

License

Apache-2.0

Requires

Python >=3.9.0

Provides Extra

dev

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