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A catalog of the quantum machine learning components shipped with Haiqu SDK. Each entry links to the workflow guide that shows it in context and to the API reference for exact signatures and return types.

Gates and ansatze

ComponentDescriptionLearn more
su2_equivariant_2_qubit_gateThe unique 2-qubit SU(2)-equivariant primitive gate: phases the singlet sector and leaves the triplet sector unchanged.Guide · Reference
su2_equivariant_3_qubit_gateThe exact 3-qubit SU(2)-equivariant gate; four angles parameterize the allowed mixing between the two spin-1/2 copies.Guide · Reference
su2_equivariant_ansatzParameterized spin-symmetry-preserving ansatz built from the 2-qubit primitive; supports brickwork, linear, and custom pair layouts.Guide · Reference

Symmetry and verification helpers

ComponentDescriptionLearn more
is_su2_equivariantCheck whether a dense unitary commutes with all three global spin generators.Guide · Reference
spin_generatorsDense global spin generators (S_x, S_y, S_z) for diagnostics and symmetry-aware observables.Guide · Reference
total_spin_opsDense total spin operators (S^2, S_z).Guide · Reference
brickwork_patternNearest-neighbor even-then-odd qubit pair layout used by the brickwork ansatz.Guide · Reference

Variational solvers

SolverDescriptionLearn more
haiqu.variational_optimizationMinimize an observable expectation value, or a nonlinear objective over several observables, for a parameterized ansatz using NFT or SciPy optimizers.Guide · Reference
haiqu.pretrainPretrain ansatz parameters against the problem objective to warm-start a variational optimization.Reference
haiqu.su2_equivariant_compilationFit a shallow brickwork circuit of 2-qubit SU(2)-equivariant gates to an equivariant target unitary.Guide · Reference