Catching Transpilation Drift with a CI/CD Workflow in Quantum Software Development

• URL: http://arxiv.org/abs/2608.08248v1
• Date: Sat, 08 Aug 2026 17:22:04 GMT
• Title: Catching Transpilation Drift with a CI/CD Workflow in Quantum Software Development
• Abstract summary: This paper proposes a workflow for detecting transpilation drift before execution.<n>The contribution is a practical CI/CD guardrail for making quantum compilation behavior observable, testable, and auditable.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum software workflows rely on compiler and provider toolchains that evolve independently of application source code. Consequently, an unchanged quantum circuit may transpile into a different target-specific realization after changes in SDK versions, optimization settings, basis gates, coupling maps, or backend descriptions. Such transpilation drift can affect circuit depth, gate composition, qubit mapping, and execution behavior, yet it is rarely monitored in CI/CD pipelines. This paper proposes a Quantum DevOps workflow for detecting transpilation drift before execution. The workflow transpiles source circuits against configured target profiles, computes structural drift metrics, records provenance and artifacts in MLflow, and raises configurable warnings or failures in GitHub Actions. Using representative circuits and target profiles, we show how drift checks can expose toolchain-induced changes and support reproducibility audits. The contribution is a practical CI/CD guardrail for making quantum compilation behavior observable, testable, and auditable.

Related papers

• Observing the Quantum Compiler through Automatic Experiment Tracking for Qiskit [1.7188280334580195]
  This demonstration presents an MLflow-inspired autologging framework for Qiskit that automatically captures compiler provenance.<n>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.
  arXiv  Detail & Related papers  (2026-08-05T16:51:15Z)
• LoopsBench: From Harness Engineering to Loop Engineering in Benchmarking Coding Agent [60.27239351179265]
  LOOPSBENCH is a benchmark for loop engineering in coding agent evaluation.<n>It comprises 112 tasks from authentic sources spanning 8 programming languages and 9 domains.<n>Its flow-aware runtime releases tests along the ready frontier and retains completed nodes as regression obligations.
  arXiv  Detail & Related papers  (2026-07-31T20:18:25Z)
• CLOSER-Bench: Evaluating Budgeted Cross-Stage Design Closure for Hardware Agents [5.604484678527336]
  CLOSER-Bench is a controlled evaluation protocol for budgeted cross-stage design closure.<n>It pairs spec-to-RTL, RTL-to-GDS, and spec-to-GDS tasks, records every simulator, synthesis, STA, and place-and-route invocation.<n>It measures final quality, anytime progress, tool cost, and cross-stage recovery.
  arXiv  Detail & Related papers  (2026-07-18T04:28:47Z)
• Visual-to-Code Authoring, Tensor-Network Debugging, and Quantum-Circuit Inspection Tools in Python [51.892236819637354]
  Network and quantum circuits are structural objects whose meaning depends on connectivity, indices, contraction order, gate placement, measurements, and related design choices.<n>They are often easier to reason about visually than as code, yet in Python they are frequently constructed, transformed, and checked through backend-specific objects or compact symbolic expressions.<n>This paper presents three complementary packages:Network-Visualization for visual and structural inspection of supported networks and traced einsum equivalence; Quantum-Network-Editor for visual-to-code authoring, backend code generation, export, and design-level analysis; and Quantum Circuit Drawer for clear circuit rendering, inspection, and
  arXiv  Detail & Related papers  (2026-06-07T18:01:31Z)
• Learning to Compose for Cross-domain Agentic Workflow Generation [56.630382886594184]
  We create an open-source LLM for cross-domain workflow generation.<n>We learn a compact set of reusable workflow capabilities across diverse domains.<n>Our 1-pass generator surpasses SOTA refinement baselines that consume 20 iterations.
  arXiv  Detail & Related papers  (2026-02-11T18:27:22Z)
• Emergence-as-Code for Self-Governing Reliable Systems [0.0]
  We propose Emergence-as-Code (EmaC), a vision for making journey reliability computable and governable via intent plus evidence.<n>An EmaC spec declares journey intent (objective, control-flow operators, allowed actions) and binds it to SLOs and telemetry.<n>A runtime inference component consumes operational artifacts (e.g., tracing and traffic configuration) to synthesize a candidate journey model with provenance and confidence.<n>An anonymized artifact repository provides a run example specification and generated outputs.
  arXiv  Detail & Related papers  (2026-02-05T09:04:33Z)
• The Parity Flow Formalism: Tracking Quantum Information Throughout Computation [0.0]
  We propose the Parity Flow formalism, a method for tracking the information flow in quantum circuits.<n>This method adds labels to quantum circuit diagrams such that the action of Clifford gates can be understood as a recoding of quantum information.
  arXiv  Detail & Related papers  (2025-05-14T15:20:05Z)
• Position-aware Automatic Circuit Discovery [59.64762573617173]
  We identify a gap in existing circuit discovery methods, treating model components as equally relevant across input positions.<n>We propose two improvements to incorporate positionality into circuits, even on tasks containing variable-length examples.<n>Our approach enables fully automated discovery of position-sensitive circuits, yielding better trade-offs between circuit size and faithfulness compared to prior work.
  arXiv  Detail & Related papers  (2025-02-07T00:18:20Z)
• The Hidden Costs of Automation: An Empirical Study on GitHub Actions Workflow Maintenance [45.53834452021771]
  GitHub Actions (GA) is an orchestration platform that streamlines the automatic execution of engineering tasks. Human intervention is necessary to correct defects, update dependencies, or existing workflow files.
  arXiv  Detail & Related papers  (2024-09-04T01:33:16Z)
• Get my drift? Catching LLM Task Drift with Activation Deltas [55.75645403965326]
  Task drift allows attackers to exfiltrate data or influence the LLM's output for other users.<n>We show that a simple linear classifier can detect drift with near-perfect ROC AUC on an out-of-distribution test set.<n>We observe that this approach generalizes surprisingly well to unseen task domains, such as prompt injections, jailbreaks, and malicious instructions.
  arXiv  Detail & Related papers  (2024-06-02T16:53:21Z)
• A High Performance Compiler for Very Large Scale Surface Code Computations [38.26470870650882]
  We present the first high performance compiler for very large scale quantum error correction. It translates an arbitrary quantum circuit to surface code operations based on lattice surgery. The compiler can process millions of gates using a streaming pipeline at a speed geared towards real-time operation of a physical device.
  arXiv  Detail & Related papers  (2023-02-05T19:06:49Z)
• AQD: Towards Accurate Fully-Quantized Object Detection [94.06347866374927]
  We propose an Accurate Quantized object Detection solution, termed AQD, to get rid of floating-point computation. Our AQD achieves comparable or even better performance compared with the full-precision counterpart under extremely low-bit schemes.
  arXiv  Detail & Related papers  (2020-07-14T09:07:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.