Add QQA4CO — Parallel Quasi-Quantum Annealing for combinatorial optimisation (ICLR 2025)

[Yuma-Ichikawa]

Hello — thanks for maintaining this list.

I'd like to propose adding QQA4CO, an open-source PyTorch toolkit
implementing the ICLR 2025 paper:

Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based
Sampling — Yuma Ichikawa, Yamato Arai.
Paper: https://openreview.net/forum?id=9EfBeXaXf0
Code: https://github.com/Yuma-Ichikawa/QQA4CO

Why it fits the "Code" section:

• It is a quantum-inspired (Quasi-Quantum) annealing solver that runs
  entirely on classical GPUs — a natural complement to quantum-native
  libraries already in this list.
• One pip install qqa gives a CLI, a Streamlit dashboard and a Python
  API for benchmarking on QUBO / Ising / MaxCut / MIS / Graph Coloring.
• Apache-2.0 licensed, archived to Zenodo
  (DOI 10.5281/zenodo.19648231), CI-tested.

Happy to rephrase or move the entry to a different section if you prefer.