A compilation of quantum-native solver techniques that can be used to map and run on a quantum computer. Compiled by Onri.

Controlled interpolation between classical and quantum learning. Binarized Quantum Neural Network benchmark harness for systematic sweeping a quantumness parameter to map learning phase transitions.

An extensible register of student-scale local practical quantum advantage projects

Quantum Neural Network (QNN) Comparative Study on MNIST Dataset

Zero-overhead quantum error suppression via tetrahedral deficit correction. Hardware-validated +16.9% fidelity. Works with Amazon Braket & Qiskit.

PennyLane reproduction of 'On verifiable quantum advantage with peaked circuit sampling' (Aaronson & Zhang, arXiv:2404.14493), Section 3 — peakedness 0.20 reproduced at n=12

Do we really need quantum computing? A runnable essay: one matrix-free dial — the effective rank Φ₁ — flags which quantum speedups survive a classical attack, and which were never quantum at all.

⚛️ Explore quantum-native solvers that enable efficient mapping and execution on quantum computers for advanced computational techniques.