Tequila
Develop, differentiate, and optimize quantum algorithms using abstract data structures. Execute on diverse simulators and hardware backends for variational quantum computation.
This is an abstraction framework designed for (variational) quantum algorithms. It operates on abstract data structures, enabling the formulation, combination, automatic differentiation, and optimization of generalized objectives. The framework can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. It supports various quantum backends like Qulacs, Qiskit, Cirq, and Qibo, and integrates with quantum chemistry packages such as Psi4, Madness, and PySCF.
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