arXiv (All)
open access
Learning unknown stabilizer codes using product measurements
Efficiently characterizing quantum error correcting codes is a key challenge on the path to fault-tolerant quantum computation. Stabilizer codes, a central class of such codes, are defined by a set of stabilizer generators. Here, we present an algorithm that uses random single-qubit measurements to
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Affine-Profile Stabilizer Thresholds for Magic in Codeword-Stabilized Quantum Codes#792834
- Affine-Profile Stabilizer Thresholds for Magic in Codeword-Stabilized Quantum Codes#788830
- Testing nonstabilizerness only with stabilizer states#1142563
- Learning to Concatenate Quantum Codes#925994
- Randomized and Diverse Input State Generation for Quantum Program Testing#155357
Record · ID 1012322
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive