QECTOR Lab's quantum error correction decoder… — A…

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About this project

QECTOR is a source-available platform designed for quantum error correction decoding. It provides the community with the tools needed for the latest advancements in quantum computing, including detailed documentation, a React-based user interface, and a commitment to reproducible workflows.

The QECTOR Lab repository serves as a source for the QECTOR Decoder platform, a pioneering solution in quantum error correction. This project encompasses the Vite/React frontend for the QECTOR Decoder v3, which is directly hosted on the apex domain qector.store via GitHub Pages.

Overview

The QECTOR Decoder v3 is supported by an extensive Reference Manual, which can be accessed through the following DOI: 10.5281/zenodo.21941046. Additional resources include the decoder code repository at GitHub and a Python package available on PyPI: qector-decoder-v3.

Repository Structure

This repository features a well-organized layout including:

source/: Contains React components, TypeScript files, site content, public assets, and build configurations.
Root Static Files: The latest production build delivered via GitHub Pages, ensuring up-to-date content availability.

Development Setup

For local development, set up the environment as follows:

cd source
npm ci
npm run lint
npm run build
npm run dev

This build process generates prerendered route shells, optimizing performance for crawlers and direct requests to GitHub Pages.

Content and Evidence Policy

QECTOR prioritizes transparency and integrity in its published content. The website does not present hardware-specific benchmark data, but rather focuses on decoder contracts, methodologies, and reproducible workflows, allowing users to derive their own performance metrics. Logical results are scored in observable/coset space, enhancing the rigor of the output.

Moreover, the public blog features 20 detailed field notes covering foundational topics in quantum error correction, various decoder algorithms, qLDPC frameworks, noise models, and ecosystem integration.

Branding

The project's branding includes a distinct logo, utilized across the website for consistency in visual identity. This logo is integrated into various site elements, including the header, footer, and Open Graph metadata, ensuring accurate representation and discoverability on social media platforms.

For more detailed information about the QECTOR Decoder licensing, refer to the pages qector.store/license and qector.store/commercial.

Explore the full capabilities of the QECTOR platform at qector.store.