You’re chasing coherence in deep NISQ circuits, optimizing gates, and calibrating data, aiming for a pristine quantum state. However, the results tank despite these efforts. The culprit isn’t just random noise, but unitary contamination, which standard error correction often misses.
Unitary Contamination: A Deep NISQ Circuit Bane
Unitary contamination is a hidden coherence killer, where ‘mostly dead’ qubits outside the active unitary subtly poison the computation. This effect is not about isolated $T_1$ or $T_2$ values; a significant fraction of these contaminated qubits corrupt the unitary evolution and skew interference patterns. This pervasive, correlated decay is a blind spot for standard error mitigation.
Deep NISQ Circuits: The Unitary Contamination Problem
If your quantum algorithms crumble in deep NISQ circuits despite seemingly ‘good enough’ gate fidelities, consider unitary contamination. It is a significant factor in deep NISQ circuits. Until error correction can address it, benchmarks may remain stalled.
Deep NISQ Circuits: Taming Unitary Contamination
By applying V5’s disciplined exclusion of contaminated shots, a correct solution was extracted for the ECDLP benchmark at Job ID `ibm-boeing-20240723-145523.qiskit-0.46.1-1564780656` on a 21-qubit backend, where the raw fidelity was questionable. The noise was the signal, but only after filtering out the poisoning effect of the rogue qubits, demonstrating nontrivial computational progress.
Unitary Contamination in Deep NISQ Circuits
This shift involves measurement discipline and hardware-aware design, like the H.O.T. Framework with V5 Orphan Measurement Exclusion. This approach preserves the coherent signal by down-weighting compromised measurement outcomes, effectively isolating the viable computation. The solution is to embrace this challenge and develop programming models that acknowledge hardware realities.
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