EPAR: Electromagnetic Pathways to Architectural Reliability in Quantum Processors

2026-03-26

AI Summary

This work addresses the lack of effective modeling of how physical layout impacts qubit interactions and architectural reliability in scaling superconducting quantum processors. It presents the first predictive framework that directly links electromagnetic physical design to architecture-level reliability by reconstructing effective Hamiltonians through electromagnetic simulation, modeling mediated coupling pathways, analyzing control pulse responses, and introducing a structural robustness scoring mechanism. The framework reveals that, under identical calibration errors, edge layouts exhibit over tenfold differences in robustness—surpassing the limitations of conventional metrics. Across all tested layouts, the structural robustness score consistently aligns with the trend of two-qubit gate errors, offering compilers fine-grained, actionable guidance for optimization.

Technology Category

• Machine Learning: Quantum Machine Learning
• Planning, Routing, and Scheduling: Planning with Language Models
• Natural Language Processing: Safety and Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

Abstract

As superconducting processors scale, understanding how physical layout shapes qubit interactions is essential for architectural reliability. Existing methods offer limited insight into how electromagnetic design choices translate into execution-level behavior. We present EPAR, an electromagnetic-to-architecture framework that predicts robustness early directly from physical design by reconstructing how design distortion modifies the effective Hamiltonian, reroutes mediated connectivity, and influences control-pulse response. Across all tested layouts, EPAR's structural scores show 100% agreement with two-qubit error trends yet reveal over 10X robustness differences among edges with identical calibrated error rates, going beyond conventional metrics to provide improved and actionable compiler guidance.

Problem

• quantum processors
• architectural reliability
• electromagnetic design
• qubit interactions
• physical layout

Innovation

• electromagnetic-to-architecture framework
• quantum processor reliability
• effective Hamiltonian reconstruction
• mediated connectivity rerouting
• robustness-aware compiler guidance