Important Announcement: The Future of TensorCircuit Project is TensorCircuit-NG

[refraction-ray]

Dear TensorCircuit Community,

As the founding authors and core development team who originally designed and built TensorCircuit, we have a vital update regarding the project’s future and long-term maintenance.

A New Chapter: TensorCircuit-NG

To ensure the project continues to meet the high standards of performance and functionality required by the community, the core team has transitioned development to a new, community-driven home: TensorCircuit-NG.

Why the transition? The original founding team has departed from the previous hosting organization. While the legacy repository remains, it is no longer under our supervision or active maintenance. To protect the integrity of the software and the interests of its users, we have launched TensorCircuit-NG as the primary vehicle for:

• Security Hardening: Unlike other legacy distributions that have inadvertently exposed sensitive credentials in their recent commit histories, TensorCircuit-NG maintains a clean and hardened codebase.
• Legal Compliance: We have strictly adhered to the original Apache-2.0 License. This avoids the legal ambiguity and compliance risks introduced by recent non-standard license modifications found in other mirrors of this project.
• Architectural Superiority: By moving development to this independent organization, we have successfully integrated advanced features that are unavailable in the legacy repository:
  • Stabilizer & Analog Simulation: Built-in support for specialized quantum circuits.
  • Distributed Architecture: Native multi-node simulation capabilities for large-scale tensor networks.
  • Up-to-date Dependencies: Guaranteed compatibility with the latest Python environments and scientific computing ecosystems.

Action Recommended for Users

To ensure you are using a stable, secure, and actively supported version of the framework, we recommend migrating to the community-maintained distribution.

Installation:

pip install tensorcircuit-ng

Note: We have ensured 100% backward compatibility. Your existing code remains functional with import tensorcircuit.

Our Commitment

We are the same team that wrote the original codebase, and our passion for tensor-network-based quantum software is stronger than ever. TensorCircuit-NG is not just a fork; it is the technical evolution of our original vision, now free to grow alongside the community.

We invite all contributors and users to join us at the new repository for all future issues, pull requests, and discussions.

Sincerely, The Original TensorCircuit Founding Team