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Roadmap

This document outlines the next major features and improvements planned for the Tesseract Code Stim implementation.

Upcoming Features

1. Pre-measurement Pauli Frame Correction

GitHub Issue: #6

Currently, Pauli frame corrections are applied after measurement, which differs from the original paper's approach. This feature will:

  • Modify the circuit flow to apply Pauli frame corrections before logical measurements
  • Align the implementation more closely with the experimental procedure described in the paper
  • Potentially improve quantitative reproduction of paper results

2. Logical vs Unencoded Qubit Benchmarking

Implement comprehensive benchmarking to compare the performance of encoded logical qubits against unencoded physical qubits under realistic conditions:

  • Add memory decoherence modeling for idle qubits (currently missing)
  • Implement realistic T1/T2 coherence times based on trapped-ion parameters
  • Generate comparative plots showing logical vs physical qubit fidelity over time

3. Alternative Noise Models

Extend the noise_cfg.py API to support custom and alternative noise models beyond depolarizing noise:

  • Implement amplitude damping and phase damping channels
  • Add support for correlated noise models
  • Enable user-defined custom noise channels via configuration
  • Add noise model parameter sweeps for comparative analysis
  • Support for experimental noise characterization data import

Contributing

We welcome contributions to any of these roadmap items! Please:

  1. Check existing GitHub issues for related discussions
  2. Open a new issue to discuss your proposed implementation approach
  3. Submit pull requests with tests and documentation

For questions or suggestions about the roadmap, please open an issue with the roadmap label.