Simpson’s paradox in cross-platform quantum deviceanalysis: A methodological case study using Josephsonjunction decoherence data
Abstract
Abstract Cross-platform comparison of quantum devices requires careful statistical methodologyto avoid spurious conclusions. We present a methodological case study demonstrating howSimpson’s paradox can arise in meta-analyses of superconducting circuit data. We introducetwo physically motivated scaling parameters—a dimensionless normalized temperature T∗ =kBT/hf and a resistance-like decoherence parameter A = (hf/eIc)(ln Q/2π)—and applythem to a secondary analysis of published data from Transmon, SNS, and SINIS devices(N = 10 data points from 3 studies).Across the pooled dataset, we observe a strong correlation (r = 0.910) between A and T∗.However, we demonstrate that this correlation is a statistical artifact arising from completeconfounding between temperature and device type: the three platforms operate in nonoverlappingtemperature regimes, and within-group correlations are consistently negative(though not statistically significant given the small sample sizes of n = 3–4 per group).Mixed-effects modeling indicates that platform identity accounts for the dominant share ofvariance in A (ICC ≈ 0.98), though we caution that variance component estimates from onlyk = 3 groups carry substantial uncertainty.Our analysis serves as a methodological warning for cross-platform data aggregation inquantum physics, illustrating how pooled correlations can reverse direction when data aredisaggregated—a hallmark of Simpson’s paradox. The proposed scaling framework may proveuseful for…
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