0.3.0

Added

• Added tournament selection as an alternative selection method for EVQE ([Issue #25])
• Add the ability to initialize EVQE individuals with more than one circuit layer ([Issue #26])
• Added the ability to use the Critival Value at Risk instead of the Expectation Value ([Issue #32])
• Added JSON serialization classes to enable the serialization of EvolvingAnsatzMinimumEigensolverResults ([Issue #35])
• Added a termination criterion for qiskit_algorithm's SPSA optimizer ([Issue #37])
• Added the ability to use a qiskit PassManager for local quantum circuit transpilation ([Issue #39])

Fixed

• Fix Pauli strings being in inverse bit order ([Issue #23])
• Fix erroneous interaction of penalty terms in the JSSP Hamiltonian ([Issue #23])
• Fix erroneous normalization of the early start Term in the JSSP Hamiltonian ([Issue #29])

Changed

• Made termination criteria more consistent ([Issue #31])
• Partially removed the dependence on qiskit_algorithms _DiagonalSampler ([Issue #32])
• Store the amount of expectation value evaluations per generation instead of as one number for the whole optimization ([Issue #35])
• If a circuit is prepended to the individuals for state preparation, store that circuit in the EvolvingAnsatzMinimumEigensolverResult ([Issue #35])
• Update QUEASARS to use the qiskit V2 primitives instead of the qiskit V1 primitives ([Issue #39])
• Require a ConfiguredSampler and ConfiguredEstimator wrapper as input instead of the Sampler and Estimator primitives by themselves ([Issue #39])

See PyPI for the release files.

0.2.0

• Implement a general algorithm structure for Evolving Ansatz VQE algorithms
• Implement the Evolutionary Variational Quantum Eigensolver (E-VQE)
• Implement Job Shop Scheduling Datastructures and Hamiltonian Encoding, as an example optimization problem

See PyPI for the release files.

v0.1.0

Initial codeless pypi commit for reserving the namespace.

See PyPI for the release files.