Evaluating System-Level Fidelity with Peaked Random Circuits
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
Quantum computing is transitioning from experimental prototypes to commercially available turnkey systems, making architecture-agnostic performance metrics essential for cross-platform comparison. Peaked Random Circuits (PRCs) have recently been proposed as a viable path to demonstrate quantum advantage on NISQ devices: a quantum processor can reliably detect a single, peaked output state amid background noise, yet the circuits' characteristics render classical simulation infeasible. In this paper, we repurpose PRCs as a system-level fidelity benchmark. By successively running a matrix of PRCs with varying qubit counts and circuit depths, we quantify a system's ability to identify the deterministic peak despite cumulative noise, gate errors, and connectivity constraints. We apply the benchmark on IQM's superconducting and AQT's trapped-ion architectures. Our results show that PRCs provide a high-precision metric comparable to Quantum Volume while exhibiting greater sensitivity to interference effects. Consequently, PRCs enable a robust framework for assessing the computational reliability of NISQ hardware across platforms.