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This research introduces PA-IRB, a diagnostic protocol that validates error rate estimates for quantum gates implemented via virtual phase updates rather than physical control pulses. By confirming that these software-defined operations do not measurably skew benchmarking results, the work strengthens the reliability of error metrics for superconducting processors using standard compilation stacks.
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Phase-Altered Interleaved Randomized Benchmarking for Compiled Non-Clifford Gates

arXiv3 min read

arXiv:2606.30327v2 Announce Type: replace Abstract: Interleaved randomized benchmarking (IRB) provides a scalable estimate of a gate's error rate, but its standard guarantees require the interleaved gate to be Clifford~\cite{Magesan2012Interleaved,magesan2012characterizing}. In superconducting processors, many non-Clifford phase gates in compiled circuits are implemented virtually as software-defined frame updates rather than as additional control pulses~\cite{mckay2017efficient}. This raises the question of whether inserting or removing such virtual phases measurably changes IRB error estimates. We introduce \emph{phase-altered interleaved randomized benchmarking} (PA-IRB), a paired-IRB diagnostic protocol comparing phase-stripped and phase-dressed Clifford interleaving gates derived from the same compiled implementation. PA-IRB reports $\Delta r=r_d-r_s$ with combined uncertainty to test whether virtual phase gates affect the extracted IRB decay beyond statistical error. As a case study, we apply PA-IRB to a compiled Toffoli gate executed on IBM superconducting processors, where the constituent $T/T^\dagger$ gates are implemented as virtual $Z$ rotations. Across tested calibration runs, $\Delta r$ is consistent with zero within uncertainty, indicating that virtual phase addition or removal does not measurably alter the IRB-derived error estimate under the employed compilation and execution stack. More generally, PA-IRB provides a lightweight, abstraction-aware diagnostic for benchmarking workflows involving software-defined phase operations. The same paired comparison can also be used to place operational bounds on the contribution of non-Clifford components to the compiled gate error, even when those components are physically executed rather than implemented virtually.

Abstract:Interleaved randomized benchmarking (IRB) provides a scalable estimate of a gate's error rate, but its standard guarantees require the interleaved gate to be Clifford~\cite{Magesan2012Interleaved,magesan2012characterizing}. In superconducting processors, many non-Clifford phase gates in compiled circuits are implemented virtually as software-defined frame updates rather than as additional control pulses~\cite{mckay2017efficient}. This raises the question of whether inserting or removing such virtual phases measurably changes IRB error estimates. We introduce \emph{phase-altered interleaved randomized benchmarking} (PA-IRB), a paired-IRB diagnostic protocol comparing phase-stripped and phase-dressed Clifford interleaving gates derived from the same compiled implementation. PA-IRB reports $\Delta r=r_d-r_s$ with combined uncertainty to test whether virtual phase gates affect the extracted IRB decay beyond statistical error. As a case study, we apply PA-IRB to a compiled Toffoli gate executed on IBM superconducting processors, where the constituent $T/T^\dagger$ gates are implemented as virtual $Z$ rotations. Across tested calibration runs, $\Delta r$ is consistent with zero within uncertainty, indicating that virtual phase addition or removal does not measurably alter the IRB-derived error estimate under the employed compilation and execution stack. More generally, PA-IRB provides a lightweight, abstraction-aware diagnostic for benchmarking workflows involving software-defined phase operations. The same paired comparison can also be used to place operational bounds on the contribution of non-Clifford components to the compiled gate error, even when those components are physically executed rather than implemented virtually.

arXiv:2606.30327 [quant-ph]

(or arXiv:2606.30327v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2606.30327 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 309 words

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