pyqpanda_alg
¶
A Quantum Optimization Algorithm Set, based on pyqpanda.
The QMengJi is a collection of fundamental quantum optimization algorithms and functions that are commonly used in developer’s optimization problems.
The QMengJi provides standardized set of tools and building blocks for writing quantum programs.
Some key functions included in the QMengJi are:
Quantum Approximate Optimization Algorithm : This is a quantum algorithm that can be used to search the lowest energy eigenstate of a Hamiltonian. It is considered to be one of the candidate algorithms for quantum advantage. Developer can construct object by QAOA(problem, arg1, arg2…) and directly call QAOA.run(args) to optimize their user-defined problem.
Overall, the QMengJi provides a standardized set of tools for developers, allowing them to optimize functions with binary variables, such as combinatorial optimization problems, that may have many practical implications. Developers can use quantum algorithms directly to obtain results without knowing anything about quantum computing, or build their own suitable quantum circuits to obtain more customized results according to their requirements.It is an important resource for solving optimization problems and advancing research on quantum optimization algorithms.
Subpackages¶
pyqpanda_alg.QAOA
pyqpanda_alg.QARM
pyqpanda_alg.QFinance
pyqpanda_alg.QKmeans
pyqpanda_alg.QLuoShu
pyqpanda_alg.QLuoShu.ConModAdd
pyqpanda_alg.QLuoShu.ConModExp
pyqpanda_alg.QLuoShu.ConModMul
pyqpanda_alg.QLuoShu.ConModaddmul
pyqpanda_alg.QLuoShu.QFTConAdd
pyqpanda_alg.QLuoShu.VarModAdd
pyqpanda_alg.QLuoShu.VarModDou
pyqpanda_alg.QLuoShu.VarModInv
pyqpanda_alg.QLuoShu.VarModMul
pyqpanda_alg.QLuoShu.VarModNeg
pyqpanda_alg.QLuoShu.VarModSqr
pyqpanda_alg.QLuoShu.lshift
pyqpanda_alg.QLuoShu.q_elliptic_padd
pyqpanda_alg.QLuoShu.q_elliptic_pdou
pyqpanda_alg.QPCA
pyqpanda_alg.QSVM
pyqpanda_alg.QSolver
pyqpanda_alg.VQE