On the ibm_kingston processor, a coherence gap of 0.91 appears at feature depth 256 in NISQ classifiers, identifying coherent phase errors as the main scaling limit beyond standard noise models.
Supervised learning with quantum- enhanced feature spaces.Nature, 567(7747):209–212
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Quantifying the Hadamard Resilience Law: Discovery of the Coherence Gap in NISQ-Era Classifiers
On the ibm_kingston processor, a coherence gap of 0.91 appears at feature depth 256 in NISQ classifiers, identifying coherent phase errors as the main scaling limit beyond standard noise models.