Quasilinear Equivalence Checking for Detector Error Models (arXiv: 2606.14677v1). A Detector Error Model (DEM) is a structured representation of error mechanisms ...
Scanned 9/11/2026
Install to Claude Code
npx -y skills add hiyenwong/ai_collection --skill quasilinear-equivalence-checking-detector-error --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Quasilinear Equivalence Checking Detector Error?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/hiyenwong-quasilinear-equivalence-checking-detector-error-ai-collection)More formats (shields.io, HTML) on the badges page.
---
name: quasilinear-equivalence-checking-detector-error
description: "Quasilinear Equivalence Checking for Detector Error Models (arXiv: 2606.14677v1). A Detector Error Model (DEM) is a structured representation of error mechanisms ..."
---
# Quasilinear Equivalence Checking for Detector Error Models
A Detector Error Model (DEM) is a structured representation of error mechanisms in quantum circuits, which has gained popularity in quantum compilation pipelines for its ability to capture fault-tolerance at a circuit level. It lists error mechanisms as instructions targeting detectors and observabl
## Paper Information
- **arXiv ID**: 2606.14677v1
- **Authors**: Quantum Systems Engineering Research
- **Published**: 2026-06-12
- **Category**: quant-ph, cs.SE
- **Links**:
- Abstract: https://arxiv.org/abs/2606.14677v1
- PDF: https://arxiv.org/pdf/2606.14677v1
## Core Methodology
A Detector Error Model (DEM) is a structured representation of error mechanisms in quantum circuits, which has gained popularity in quantum compilation pipelines for its ability to capture fault-tolerance at a circuit level. It lists error mechanisms as instructions targeting detectors and observables, specifying for each physical fault channel the probability that the fault fires, the detectors it triggers, and the observables it flips.
In this paper, we develop an equational theory for DEMs, with its associated categorical semantics. We present a sound, terminating, confluent rewriting system for DEM terms, formulating it as a symmetric monoidal theory (a PROP) over the Giry monad. We prove that every DEM term has a unique normal form, which can be computed efficiently in quasilinear time O(k|E|log|E|), where |E| is the number of instructions and k bounds the size of a target set. This provides a complete set of invariants (via Tanner graphs) for structural DEM equivalence. We provide the first static decision procedure for DEM equivalence, with rigorous correctness guarantees. It is complete (decides full decoder-equivalence exactly) for non-adaptive quantum error correction (QEC) pipelines, and scales to a sound and applicable decision procedure for partially-adaptive circuits (lattice surgery, distributed QEC, ...) without suffering exponential overhead. We discuss its application to the verification and optimisation of quantum compilers.
## Key Contributions
1. Novel approach to systems engineering
2. Category: quant-ph, cs.SE
3. Research domain: Quantum Systems
## Technical Approach
### Problem Domain
A Detector Error Model (DEM) is a structured representation of error mechanisms in quantum circuits, which has gained popularity in quantum compilation pipelines for its ability to capture fault-toler
### Methodology Highlights
- Systems engineering principles
- Quantum error correction
- Verification and optimization patterns
## Activation Keywords
- systems engineering
- quasilinear-equivalence-checking-detector-error
- quantum systems
- verification
## Related Skills
- systems-engineering-apr2026
- modern-systems-engineering-patterns
- quantum-systems-engineering
## Applications
- Quantum compiler verification
- Systems verification
- Error detection and correction
## Limitations & Pitfalls
- Preprint status (not peer-reviewed)
- Specialized domain knowledge may be required
- Check for updated versions on arXiv
## Implementation Notes
This skill captures the research methodology from the arXiv paper. Apply the patterns and approaches described in the abstract to relevant systems engineering problems.
## Source
arXiv: 2606.14677v1 - Quasilinear Equivalence Checking for Detector Error Models
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!