Quantum programming, as simple as writing Python.
No QuantumCircuit to learn, no backend to understand, no manual measure.
If you can write Python, you can write quantum programs.
The Problem
Quantum programming today is unnecessarily complex. Writing a simple Bell state in Qiskit requires 10+ lines, understanding circuit objects, backend selection, and manual measurement. Switching frameworks means rewriting everything.
Too Many ConceptsQuantumCircuit, backend, transpile, measure_all — 8+ new concepts before writing a single gate. |
Framework Lock-inCode written for Qiskit can't run on Cirq. Switching frameworks means rewriting everything. |
No Smart DefaultsChoosing the wrong simulation method can be 1000x slower. Users shouldn't need to know internals. |
The Solution
QuoNic abstracts away the complexity. Three lines of code, any backend, any hardware.
from quonic import qgate, qshow
from quonic.gates import H, CX
qgate(H, 0)
qgate(CX, 0, 1)
qshow()
pip install quonic
Features
| Feature | Description |
|---|---|
| 3-line syntax | qgate + qshow — that's it |
| 12+ backends | One argument: qshow(backend='qiskit') |
| 77 algorithms | Grover, Shor, VQE, QAOA, QFT, error correction, quantum ML |
| Smart scheduler | Auto-selects fastest method (statevector / stabilizer / MPS / density matrix) |
| GPU acceleration | qshow(backend='gpu') — 10x speedup |
| Real hardware | Origin Quantum, AWS Braket, Quantum Inspire verified |
| Noise simulation | Depolarizing, bit-flip, phase-flip, decoherence |
| Error mitigation | ZNE, readout calibration |
| 23 visualizations | Circuit diagrams, Bloch sphere, histograms |
Tech Stack
| Component | Technology | Description |
|---|---|---|
| Core | Python 3.9+ | IR, scheduler, compiler, noise models |
| Backends | Qiskit · Cirq · Qulacs · TensorCircuit · CUDA-Q · MindQuantum · QPanda3 | 12+ quantum backends |
| GPU | CuPy · Qulacs GPU · CUDA-Q | GPU-accelerated simulation |
| Hardware | Origin Quantum · AWS Braket · Quantum Inspire | Real quantum hardware |
| Visualization | Matplotlib | 23 chart types, lazy-loaded |
Real Hardware
| Platform | Device | Status |
|---|---|---|
| Origin Quantum | WK_C180 | ✅ Verified |
| AWS Braket | Rigetti Cepheus-1-108Q | ✅ Verified |
| Quantum Inspire | Tuna-9 / Tuna-17 | ✅ Verified |
qshow(backend='qpanda', device='WK_C180')
qshow(backend='qi', device='tuna9')
Algorithms
from quonic.algorithms import grover, vqe, qft, qaoa_maxcut
grover("11", 2) # Search
vqe(hamiltonian, 2) # Chemistry
qft(n_qubits=4) # Fourier Transform
qaoa_maxcut(edges, n_qubits=3) # Optimization
| Domain | Algorithms |
|---|---|
| Foundational | QFT, Deutsch-Jozsa, Bernstein-Vazirani, Simon, QPE |
| Search & Optimization | Grover, QAOA (MaxCut/TSP/MIS/Knapsack), quantum annealing |
| Chemistry | VQE, Hamiltonian simulation, Trotter, Jordan-Wigner |
| Machine Learning | QNN, QSVM, QGAN, QCNN, QGNN, QPCA, QRL |
| Error Correction | Bit/phase flip, Shor code, Steane code, surface code, color code |
| Communication | Teleportation, BB84, E91, superdense coding |
Roadmap
- Core API:
qgate,qshow,reset— minimal syntax - 12+ backends: Qiskit, Cirq, Qulacs, TensorCircuit, CUDA-Q, MindQuantum, QPanda3
- 77 algorithm templates: From Grover to quantum ML
- Smart scheduler: Auto-select fastest simulation method
- GPU acceleration: CuPy, Qulacs GPU, CUDA-Q
- Real hardware: Origin Quantum, AWS Braket, Quantum Inspire
- Noise simulation: Depolarizing, bit-flip, phase-flip, decoherence
- Error mitigation: ZNE, readout calibration
- Visualization: 23 chart types with Matplotlib
- Documentation: 92 examples, bilingual (EN/ZH)
- More backends: IonQ, Rigetti, Xanadu, QuEra
- Quantum networking: Multi-node quantum communication
- Fault-tolerant computing: Logical qubit operations
Docs
- Quick Start — 5 minutes
- Examples — 92 examples, bilingual
- API Reference — all modules
- Tutorials — step-by-step guides
Contributing
Fork → branch → PR.
See CONTRIBUTING.md for setup and code style.
License
Apache 2.0 — friendly to commercial use, with patent protection.
Built with ❤️ by Lee LapYuen · 中文文档
1 maintainer
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