netket.hilbert.index.optimalConstrainedHilbertindex

netket.hilbert.index.optimalConstrainedHilbertindex#

netket.hilbert.index.optimalConstrainedHilbertindex(local_states, size, constraint)[source]#

Returns the optimal Hilbert Index to index into the uniform state with local degrees of freedom local_states, size sites and given constraint.

This function uses dispatch to select a potential optimal implementation, and generally returns a default implementation if None better is available.

Parameters:
  • local_states – The StaticRange Local states.

  • size – integer of the number of degrees of freedom.

  • constraint – callable class implementing the constraint.

netket.hilbert.index.optimalConstrainedHilbertindex(local_states, size, constraint)[source]
netket.hilbert.index.optimalConstrainedHilbertindex(local_states, size, constraint: netket.hilbert.constraint.multiple.ExtraConstraint)[source]

# Rule for ExtraConstraint, which is a constraint that is a sum of two constraints. # This wraps an optimised hilbert index into a cosntrained one if it exists.

netket.hilbert.index.optimalConstrainedHilbertindex(local_states, size, constraint: netket.hilbert.constraint.sum.SumConstraint)[source]
netket.hilbert.index.optimalConstrainedHilbertindex(local_states, size, constraint: netket.hilbert.constraint.sum_partition.SumOnPartitionConstraint)[source]