{"id":28375682,"url":"https://github.com/farukalpay/quantumlib","last_synced_at":"2025-06-26T05:30:41.206Z","repository":{"id":281786533,"uuid":"946402180","full_name":"farukalpay/quantumlib","owner":"farukalpay","description":"A modular quantum computing library in Python featuring QAOA, Grover, HHL, and VQC — built on Qiskit, with future plans to become a QPU-agnostic, from-scratch quantum SDK.","archived":false,"fork":false,"pushed_at":"2025-03-11T17:05:28.000Z","size":98,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-05T23:26:32.631Z","etag":null,"topics":["grover","hhl","ibm-quantum","qaoa","qft","qiskit","qpe","qpu-agnostic","quantum-algorithms","quantum-annealing","quantum-computing","quantum-framework","quantum-gradient","quantum-machine-learning","quantum-optimization","quantum-research","quantum-sdk","quantum-simulation","quantumlib","vqc"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/farukalpay.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-11T04:46:24.000Z","updated_at":"2025-04-24T09:29:41.000Z","dependencies_parsed_at":"2025-03-11T06:40:11.945Z","dependency_job_id":null,"html_url":"https://github.com/farukalpay/quantumlib","commit_stats":null,"previous_names":["farukalpay/quantumlib"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/farukalpay/quantumlib","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farukalpay%2Fquantumlib","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farukalpay%2Fquantumlib/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farukalpay%2Fquantumlib/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farukalpay%2Fquantumlib/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/farukalpay","download_url":"https://codeload.github.com/farukalpay/quantumlib/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farukalpay%2Fquantumlib/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262008603,"owners_count":23244214,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["grover","hhl","ibm-quantum","qaoa","qft","qiskit","qpe","qpu-agnostic","quantum-algorithms","quantum-annealing","quantum-computing","quantum-framework","quantum-gradient","quantum-machine-learning","quantum-optimization","quantum-research","quantum-sdk","quantum-simulation","quantumlib","vqc"],"created_at":"2025-05-29T23:06:28.598Z","updated_at":"2025-06-26T05:30:41.195Z","avatar_url":"https://github.com/farukalpay.png","language":"Python","readme":"# QuantumLib ✨\n\n**QuantumLib** is a state-of-the-art Python library built on Qiskit, designed for quantum computing research and education. Optimized for macOS M4 Pro and compatible with IBM Quantum hardware, QuantumLib provides comprehensive tools to simulate, execute, and benchmark advanced quantum algorithms.\n\n## 🚀 Expanded Features\n\n### Quantum Algorithms\n- **Quantum Approximate Optimization Algorithm (QAOA)**: Solves combinatorial optimization problems.\n- **Unitary Coupled Cluster (UCC)**: Quantum simulations for electronic structure problems.\n- **Grover's Search Algorithm**: Efficiently searches unsorted databases with quantum speedup.\n- **Quantum Fourier Transform (QFT)**: Fundamental for phase estimation and algorithmic speedup.\n- **Quantum Phase Estimation (QPE)**: Accurately determines phases, essential for quantum simulations.\n- **Harrow-Hassidim-Lloyd (HHL) Algorithm**: Exponentially faster solutions to linear systems.\n- **Quantum Annealing**: Heuristic quantum optimization.\n- **Kernel-based Quantum Machine Learning**: Integrates quantum methods into machine learning.\n\n## 🚀 Hybrid Optimizers\n- Adam\n- RMSProp\n- Simultaneous Perturbation Stochastic Approximation (SPSA)\n- Quantum Natural Gradient (QNG)\n\n## 🛡 Error Mitigation\n- Richardson Extrapolation\n- Readout Calibration\n\n## 🛠 Interactive Developer Tools\n- **Command-Line Interface (CLI)**\n- Jupyter Notebooks demonstrating quantum applications in finance, cryptography, etc.\n\n## 📈 Performance Benchmarks\n- Simulator vs. IBM Quantum hardware performance evaluation.\n\n## 📦 Installation\n\n### Requirements\n- Python ≥ 3.9\n- Qiskit ≥ 1.0\n- NumPy, SciPy, Matplotlib\n\n### Quick Start\n\nClone QuantumLib and set up:\n```bash\ngit clone https://github.com/FarukAlpay/QuantumLib.git\ncd QuantumLib\n\nconda create -n quantum_env python=3.9\nconda activate quantum_env\npip install -r requirements.txt\npip install -e .\n```\n\n## 🎯 Usage\n\n### CLI Examples\n\nRun Grover's Algorithm:\n```bash\nrun_circuit grover --num_qubits 3 --marked_state 101 --iterations 1\n```\n\nOptimize QAOA:\n```bash\nrun_circuit qaoa --qubits 5 --optimizer spsa\n```\n\nSolve linear systems with HHL:\n```bash\nrun_circuit hhl\n```\n\nRun Variational Quantum Circuit (VQC):\n```bash\nrun_circuit vqc --num_qubits 3 --num_layers 2 --rotation_gate Ry --entanglement_pattern chain\n```\n\n### Python Integration\n\n```python\nfrom quantumlib.circuits import QAOACircuit\nfrom quantumlib.optimizers import SPSAOptimizer\n\ncircuit = QAOACircuit(qubits=5)\noptimizer = SPSAOptimizer(maxiter=300)\nresult = optimizer.optimize(circuit)\n```\n\n## 🧪 Testing\n\nExecute tests to ensure robust performance:\n```bash\npython test_all.py\n```\n\n## 🤝 Contributing\n\nContributions are warmly welcomed! Please:\n\n1. Fork and clone the repository.\n2. Create a new branch (`git checkout -b feature-name`).\n3. Implement and test your changes.\n4. Commit (`git commit -am \"Feature description\"`).\n5. Push (`git push origin feature-name`) and open a Pull Request.\n\n## 📜 License\n\nQuantumLib is released under the MIT License. See [LICENSE](LICENSE).\n\n## 📧 Contact\n\nQuestions, suggestions, or contributions? \n\n- Open an [issue on GitHub](https://github.com/FarukAlpay/QuantumLib/issues).\n- Email: faruk.alpay@example.com\n\n## 🧪 Testing\n\nRun comprehensive tests:\n```bash\npython test_all.py\n```\n\n## 🌟 Getting Started\n\nExplore QuantumLib quickly:\n\n- **Run a basic Grover algorithm:**\n```bash\nrun_circuit grover --num_qubits 3 --marked_state 101\n```\n- **Check out tutorials** provided in Jupyter notebooks to dive deeper.\n\n## 📂 Project Structure\n\n```\nquantumlib/\n├── cli/\n│   └── run_circuit.py\n├── circuits/\n│   ├── qft.py\n│   ├── grover.py\n│   ├── hhl.py\n│   └── vqc.py\n├── optimizers/\n│   ├── classical_opt.py\n│   └── quantum_native_opt.py\n├── execution/\n│   └── backend_manager.py\n├── tests/\n│   └── test_all.py\n├── requirements.txt\n└── README.md\n```\n\n## 📜 License\n\nQuantumLib is distributed under the MIT License.\n\n## ✨ Developer's Note\n\nCrafted passionately by **Faruk Alpay** in Nidderau, Germany, on 11 March 2025. Inspired by the synergy of vaporized herbs, innovative code, and the smooth performance of a MacBook M4 Pro.\n\n_Euphoria in every quantum bit!_ 🌿💻✨\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarukalpay%2Fquantumlib","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffarukalpay%2Fquantumlib","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarukalpay%2Fquantumlib/lists"}