Observing the Quantum Compiler through Automatic Experiment Tracking for Qiskit

2026-08-05

AI Summary

This work addresses the limited observability in existing quantum compilers, where reliance solely on final circuit metrics hinders effective evaluation of compilation strategies. To overcome this, we propose an automated logging framework inspired by MLflow that enables end-to-end tracing of Qiskit compilation without manual instrumentation. By deploying compiler probes, our approach automatically captures execution data, backend characteristics, configuration parameters, and intermediate results across all compilation stages, storing them in an MLflow tracking server via an extended QProv model. This framework substantially enhances the observability and reproducibility of quantum compilation experiments, establishing a robust data foundation for fine-grained analysis, evaluation, and optimization of compilation strategies.

Abstract

Understanding the effectiveness of quantum compilation techniques requires visibility into the entire transpilation process, not just the final circuit metrics. This demonstration presents an MLflow-inspired autologging framework for Qiskit that automatically captures compiler provenance, including transpilation stages, pass-level execution data, backend characteristics, compiler configuration, and execution results. The framework extends the QProv provenance model with compiler-specific information and stores the collected data in an MLflow Tracking Server for analysis and visualization. By eliminating manual instrumentation, the proposed approach improves compiler observability and supports reproducible evaluation of quantum compilation workflows.

Problem

• quantum compilation
• compiler observability
• transpilation process
• provenance tracking
• Qiskit

Innovation

• quantum compilation
• automatic logging
• compiler provenance
• Qiskit
• MLflow