Emergent Bifurcations in Quantum Circuit Stability from Hidden Parameter Statistics

TL;DR

This paper reveals that quantum circuit stability bifurcates into robust and fragile classes based on statistical properties of gate parameters, with fragile circuits being more sensitive due to a paradoxical importance of small-angle gates.

Contribution

It uncovers the statistical origin of circuit bifurcation and introduces a new framework focusing on microscopic parameter properties for resilient quantum circuit design.

Findings

Fragile circuits show low parameter variability and few small-angle gates.

Bifurcation into robustness classes is driven by statistical properties, not structure.

Small-angle gates are more critical in fragile circuits, revealing paradoxical importance.

Abstract

The compression of quantum circuits is a foundational challenge for near-term quantum computing, yet the principles governing circuit stability remain poorly understood. We investigate this problem through a large-scale numerical analysis of 300 structurally-uniform circuits across 10, 12, and 14 qubits. Despite their macroscopic uniformity, we find that each ensemble universally bifurcates into distinct robust and fragile classes. We solve the puzzle of this emergent bifurcation, demonstrating that its origin is not structural, but is instead encoded in the statistical properties of the gate rotation parameters. Fragile circuits consistently exhibit a universal signature of ``statistical brittleness,'' characterized by low parameter variability and a scarcity of small-angle gates. We uncover the underlying physical mechanism for this phenomenon: Paradoxical Importance where smaller-angle gates are counter-intuitively more critical to the circuit's function, an effect most pronounced in fragile circuits. This reliance on fine-tuning explains why statistically brittle circuits are uniquely vulnerable to failure under compression. These findings establish a new framework for engineering resilient quantum algorithms, shifting the focus from macroscopic structure to the microscopic statistical properties of a circuit's parameters.