Fig. 5: Late-time sample fluctuations.
From: Dynamical transition in controllable quantum neural networks with large depth
The standard deviations normalized by mean for the relative dQNTK λ∞ (a) and dynamical index ζ∞ (b) are plotted versus the number of parameters L. Red dashed lines represent power-law fitting results. Here the RPA is applied on n = 5 qubits with different L parameters (via tuning number of layers D). The observable is a state projector and the target value is O0 = 1.
