MindQuantum Documents
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MindQuantum is a new-generation quantum computing suite based on MindSpore, supporting training and inference of multiple quantum neural networks.
MindQuantum focuses on the implementation of NISQ algorithms. It combines the HiQ high-performance quantum computing simulator with the parallel automatic differentiation capability of MindSpore. MindQuantum is easy-to-use with ultra-high performance. It can efficiently handle problems like quantum machine learning, quantum chemistry simulation, and quantum optimization. MindQuantum provides an efficient platform for researchers, teachers and students to quickly design and verify quantum algorithms, making quantum computing at your fingertips.
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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