Benchmark: Cross-entropy benchmarking (XEB)
Benchmarks / System level (whole processor)
The fidelity with which a processor samples from random circuits, estimated from the ideal probabilities of the bit strings it outputs.
- Level
- System level (whole processor)
- Maintained by
- Introduced by Boixo et al. (2018); used mainly by Google Quantum AI.
- European
- No
- Reference
- https://arxiv.org/abs/1608.00263
How it is measured
Random circuits are run, the ideal probabilities of the measured bit strings are computed classically, and a linear cross-entropy estimator gives the fidelity; it underlies random circuit sampling claims.
Limitations and criticisms
- The ideal probabilities must be computed classically, which is exactly what becomes infeasible at scale; large-scale values are extrapolated.
- Classical spoofing algorithms have reproduced some claimed results (Pan et al. 2022).
Used in European procurements
None of the procurement documents read for this release names it.
Sources
- S. Boixo et al. (2018). Characterizing Quantum Supremacy in Near-Term Devices. Nature Physics 14, 595 (2018); arXiv:1608.00263. Read: abstract page, retrieved 2026-10-23.
- A. Morvan et al. (2024). Phase transition in Random Circuit Sampling. Nature 634, 328 (2024); arXiv:2304.11119. Read: abstract page, retrieved 2026-10-23.
- F. Pan, K. Chen, P. Zhang (2022). Solving the sampling problem of the Sycamore quantum circuits. Phys. Rev. Lett. 129, 090502 (2022); arXiv:2111.03011. Read: abstract page, retrieved 2026-10-23.