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TensorCircuit

A Research Program at Tencent Quantum Lab (Sept 2022–Sept 2023)

For detailed information and contributions, visit GitHub.

This year-long research program extended Tencent Quantum Lab’s T-Spark Summer Program and focused on advancing TensorCircuit — an open-source framework for quantum machine learning, simulation, and communication. Two participants were selected to continue this work under the mentorship of Tencent Quantum Lab researchers. My contributions combined engineering and research, emphasizing cross-platform compatibility, computational efficiency, and the integration of classical and quantum learning paradigms.

Key Contributions

  • Documentation & Accessibility: Translated and rewrote core documentation to improve clarity and contributor onboarding. Authored a comprehensive macOS installation guide addressing Apple Silicon and Metal API dependencies.
  • Framework Engineering: Enhanced TensorCircuit’s cross-platform support and resolved critical integration issues on macOS and Linux.
  • Model Development: Implemented hybrid quantum–classical models inspired by traditional ML architectures (e.g., Transformer, SVM), improving benchmark accuracy from 60% to 90%.
  • Algorithmic Innovation: Extended ensemble learning and support vector techniques for quantum ML workflows, bridging conventional and quantum optimization methods.
  • Performance Optimization: Contributed to GPU acceleration and Metal backend integration, increasing local simulation and inference efficiency.
  • Documentation Finalization: Completed end-to-end technical documentation detailing design, architecture, and experiment reproducibility for public release.