ternary_tree

ternary_tree(operator, encoding, num_qubits)

Map an operator to a SparseObservable under a ternary-tree encoding.

This is the type-agnostic entry point to the ternary-tree mappers, mirroring jordan_wigner(). It dispatches on the concrete type of operator to the matching direct implementation, listed under Ternary-tree encodings in the library documentation. An operator type without one raises a TypeError.

Parameters:

  • operator (OperatorTrait) – the operator to map.

  • encoding (TernaryTreeEncoding) – the compiled encoding to map through. Compile it once with TernaryTreeEncoding and reuse it across every operator mapped through the same tree.

  • num_qubits (int) – the number of qubits for the resulting qubit operator. Must be at least the encoding’s mode count; a larger value pads with the identity.

Returns:

The mapped qubit operator, subject to the same simplification and grouping caveats as fermion_ternary_tree().

Raises:

  • TypeError – if operator is of a type for which no ternary-tree implementation exists.

  • ValueError – if operator acts on a mode the encoding does not cover, or num_qubits is smaller than the encoding’s mode count.

Return type:

SparseObservable

>>> from qiskit_fermions.mappers import TernaryTree, TernaryTreeEncoding
>>> from qiskit_fermions.mappers.library import ternary_tree
>>> from qiskit_fermions.operators import FermionOperator
>>> fop = FermionOperator.from_dict({((True, 0), (False, 0)): 0.1})
>>> enc = TernaryTreeEncoding(TernaryTree.breadth_first(2, 3))
>>> ternary_tree(fop, enc, 2).simplify()
<SparseObservable with 2 terms on 2 qubits: (0.05+0j)() + (-0.05+0j)(Z_1 Z_0)>

A chain along Z reproduces jordan_wigner(), which is what makes the tree a generalisation of it rather than an alternative to it:

>>> from qiskit_fermions.mappers.library import jordan_wigner
>>> chain = TernaryTreeEncoding(TernaryTree.chain(2, "Z"))
>>> bool((ternary_tree(fop, chain, 2) - jordan_wigner(fop, 2)).simplify().num_terms == 0)
True

Every operator type has a direct implementation, so the dispatch is total over them. Anything else (an object that is not a fermionic operator at all) raises a TypeError:

>>> from qiskit.quantum_info import SparseObservable
>>> ternary_tree(SparseObservable.identity(2), enc, 2)
Traceback (most recent call last):
...
TypeError: ternary_tree does not support operator type 'SparseObservable'.