MindQuantum Documents
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MindQuantum is a general-purpose quantum computing library designed to train and infer multiple quantum neural networks. Developed by MindSpore and HiQ, it leverages the quantum computing simulator developed by HiQ and high-performance automatic differentiation of MindSpore, ensuring MindQuantum can efficiently solve problems in quantum machine learning, chemistry simulation, and optimization. It provides a platform for researchers, teachers, and students to quickly design and verify quantum machine learning algorithms.
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Typical Application Scenarios
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1. `Quantum Machine Learning `_
Add the quantum neural network to the training process to improve the convergence accuracy.
2. `Quantum Chemical Simulation `_
Use VQE to solve the ground state energy of molecular system.
3. `Quantum Combinatorial Optimization `_
Use QAOA to solve the Max-Cut problem.
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:caption: Installation
mindquantum_install
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:caption: Guide
parameterized_quantum_circuit
initial_experience_of_quantum_neural_network
get_gradient_of_PQC_with_mindquantum
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:caption: Variational Quantum Algorithm
classification_of_iris_by_qnn
quantum_approximate_optimization_algorithm
qnn_for_nlp
vqe_for_quantum_chemistry
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:caption: General Quantum Algorithm
quantum_phase_estimation
grover_search_algorithm
shor_algorithm
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:caption: API References
mindquantum.core
mindquantum.simulator
mindquantum.framework
mindquantum.algorithm
mindquantum.io
mindquantum.engine
mindquantum.utils
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:caption: RELEASE NOTES
RELEASE