QSL - Quantum Search Language: Full-stack quantum computing framework with simulator, algorithms (QFT/Shor/QAOA/VQE), QML, hardware backends (IBM/AWS), AI scientist, and self-evolving meta-system
Project description
QSL — 量子搜索语言
用一句话描述你想找什么,剩下的交给量子计算。
v0.2.0 — 五级量子计算框架
一个完整的量子计算 Python 框架,从声明式搜索到自进化 AI 系统:
| 级别 | 模块 | 功能 |
|---|---|---|
| 一级 | Gates + Algorithms | 量子门 / QFT / Shor 因子分解 / QAOA / VQE |
| 二级 | QML | 量子神经网络 / 量子 SVM / 量子核函数 / QGAN |
| 三级 | Backends + Compiler | IBM / AWS Braket / 自动后端选择 / 门融合 / 布局映射 / 错误缓解 |
| 四级 | AI Scientist | LLM 问题翻译 / 量子自主智能体 / 假设测试 / 发现流水线 |
| 五级 | Meta + Network | 遗传算法搜索电路 / RL 编译优化 / 量子区块链 / 分布式节点 |
5 秒看懂
from qsl import QSLProgram, compile_and_run
program = QSLProgram(
name="3-SAT",
n_qubits=3,
premises=["x0 | ~x1", "x1 | x2", "~x0 | ~x2"],
shots=10
)
result = compile_and_run(program)
print(result.get_solutions()) # [3, 4] = 011 和 100
不用懂量子力学。
快速体验各模块
量子算法
from qsl import ShorSolver, QAOA, VQE, QuantumFourierTransform
# 量子傅里叶变换
qft = QuantumFourierTransform(3)
circuit = qft.build_circuit()
# Shor 算法分解 15 = 3 × 5
factors = ShorSolver(15).factor()
print(factors.factors) # [3, 5]
# VQE 计算 H2 基态能量
vqe = VQE(2, VQE.h2_hamiltonian())
energy, state = vqe.optimize()
# QAOA 求解优化问题
qaoa = QAOA(3, QAOA.maxcut_cost_matrix(3), p=2)
params, energy = qaoa.optimize()
量子机器学习
from qsl import QuantumLayer, QNN, QuantumSVM
# 量子神经网络
layer = QuantumLayer(n_qubits=3, n_features=4, encoding="angle")
qnn = QNN(n_qubits=3, n_features=4, n_classes=2)
qnn.fit(X_train, y_train, epochs=50)
preds = qnn.predict(X_test)
# 量子 SVM(兼容 sklearn API)
qsvm = QuantumSVM().fit(X_train, y_train)
print(qsvm.score(X_test, y_test))
硬件后端
from qsl import AutoBackend
# 自动选择最优后端
backend = AutoBackend(max_qubits=50)
result = backend.run(circuit)
AI 量子科学家
from qsl import ProblemTranslator, QuantumAgent
# 自然语言 → 量子程序
translator = ProblemTranslator()
program = translator.translate("破解 RSA-15 加密")
# 自主量子智能体
agent = QuantumAgent("寻找最优投资组合")
report = agent.run()
安装
# 核心(零外部依赖)
pip install qsl-quantum
# 带量子算法支持
pip install qsl-quantum[algorithms]
# 量子机器学习
pip install qsl-quantum[qml]
# 真实硬件 (IBM / AWS)
pip install qsl-quantum[ibm] # IBM Quantum
pip install qsl-quantum[aws] # AWS Braket
# 全部安装
pip install qsl-quantum[full]
项目结构
qsl/
├── core/ 量子态、布尔解析、Grover 搜索
├── compiler/ 编译器、DSL 解析、门优化、错误缓解
├── backends/ 模拟器 + IBM + AWS Braket + 自动选择
├── algorithms/ QFT / Shor / QAOA / VQE
├── qml/ 量子层 / QNN / 量子核 / QSVM / QGAN
├── ai/ LLM 翻译器 / 量子智能体 / 假设测试
├── pipelines/ 药物发现 / 密码分析 / 投资组合
├── meta/ 遗传电路搜索 / RL 编译 / 定理证明
├── network/ 分布式节点 / 量子区块链
└── utils/ 异常体系、输入验证
tests/ 351 个测试用例
运行测试
pip install -e ".[dev]"
pytest tests/ -v # 351 passed, 3 xfailed
作者
宋梓铭 · Gitee · 15011462616@163.com
许可证
MIT — 随意使用、修改、分发。
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