Platform-specific benchmarks
Benchmarks built for hardware outside the digital gate model: quantum annealers, photonic samplers, and analog quantum simulators.
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Estimates the many-body fidelity of an analog quantum simulator's quench dynamics from about a thousand bitstring samples, doing for Hamiltonian evolution what XEB does for random digital circuits.
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Open-source Python suite that generates Ising, QUBO, and higher-order optimization problems with planted, a-priori-known ground states and tunable hardness across five planting schemes.
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Frustrated cluster loops with a tunable coupling scale λ that conceals the planted structure, built to test whether annealer speedups survive against structure-exploiting classical solvers.
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Planted-solution Ising benchmark of the D-Wave 2000Q era: frustrated loops laid over ferromagnetic qubit clusters with tunable ruggedness, scored by time-to-solution against classical solvers.
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Photonic quantum-advantage benchmark: sample photon-number patterns from squeezed light sent through a large random interferometer, a task whose probabilities are #P-hard matrix hafnians.
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The standard quantum-annealing benchmark: wall-clock time to find the ground state at least once with 99% probability, compared against optimized classical solvers to test for quantum speedup.
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D-Wave's relaxation of time-to-solution that times solvers to a target energy (originally set by quantiles of a reference annealer's short-run samples) rather than to the exact ground state.