FermionicGate

The number of fermionic modes that this gate acts upon.

Get the base class of this instruction. This is guaranteed to be in the inheritance tree of self.

The “base class” of an instruction is the lowest class in its inheritance tree that the object should be considered entirely compatible with for _all_ circuit applications. This typically means that the subclass is defined purely to offer some sort of programmer convenience over the base class, and the base class is the “true” class for a behavioral perspective. In particular, you should not override base_class if you are defining a custom version of an instruction that will be implemented differently by hardware, such as an alternative measurement strategy, or a version of a parametrized gate with a particular set of parameters for the purposes of distinguishing it in a Target from the full parametrized gate.

This is often exactly equivalent to type(obj), except in the case of singleton instances of standard-library instructions. These singleton instances are special subclasses of their base class, and this property will return that base. For example:

>>> isinstance(XGate(), XGate)
True
>>> type(XGate()) is XGate
False
>>> XGate().base_class is XGate
True

In general, you should not rely on the precise class of an instruction; within a given circuit, it is expected that Instruction.name should be a more suitable discriminator in most situations.

Get the decompositions of the instruction from the SessionEquivalenceLibrary.

Return definition in terms of other basic gates.

Return instruction label

Is this instance is a mutable unique instance or not.

If this attribute is False the gate instance is a shared singleton and is not mutable.

Return the name.

Return the number of clbits.

Return the number of qubits.

The parameters of this Instruction. Ideally these will be gate angles.

_apply_unitary_(vec, norb, nelec, copy)

Applies this gate to an ffsim state vector, implementing ffsim’s protocol.

This is the identity-placement entry point of ffsim’s ffsim.SupportsApplyUnitary protocol (mirrored locally as SupportsApplyUnitary): it assumes the gate acts on the modes 0..num_modes of the state vector and delegates to the placement-aware _apply_unitary_placed_() (see SupportsApplyUnitaryPlaced), which every concrete fermionic gate implements. See that method for the semantics of vec (including whether a None vector is accepted), norb, nelec, and copy.

Raises

NotImplementedError – if this gate does not implement _apply_unitary_placed_ (a bare FermionicGate used only as a type marker), and therefore cannot be applied to a state vector.

Parameters

• vec (np.ndarray | None)
• norb (int)
• nelec (int |tuple[int, int])
• copy (bool)

Return type

np.ndarray

add_decomposition(decomposition)

Add a decomposition of the instruction to the SessionEquivalenceLibrary.

broadcast_arguments(qargs, cargs)

Validation and handling of the arguments and its relationship.

For example, cx([q[0],q[1]], q[2]) means cx(q[0], q[2]); cx(q[1], q[2]). This method yields the arguments in the right grouping. In the given example:

in: [[q[0],q[1]], q[2]],[]
outs: [q[0], q[2]], []
      [q[1], q[2]], []

The general broadcasting rules are:

• If len(qargs) == 1:

  [q[0], q[1]] -> [q[0]],[q[1]]

• If len(qargs) == 2:

  [[q[0], q[1]], [r[0], r[1]]] -> [q[0], r[0]], [q[1], r[1]]
  [[q[0]], [r[0], r[1]]]       -> [q[0], r[0]], [q[0], r[1]]
  [[q[0], q[1]], [r[0]]]       -> [q[0], r[0]], [q[1], r[0]]

• If len(qargs) >= 3:

  [q[0], q[1]], [r[0], r[1]],  ...] -> [q[0], r[0], ...], [q[1], r[1], ...]

Parameters

• qargs (list) – List of quantum bit arguments.
• cargs (list) – List of classical bit arguments.

Returns

A tuple with single arguments.

Raises

CircuitError – If the input is not valid. For example, the number of arguments does not match the gate expectation.

Return type

Iterable[tuple[list, list]]

control(num_ctrl_qubits=1, label=None, ctrl_state=None, annotated=None)

Return the controlled version of itself.

The controlled gate is implemented as ControlledGate when annotated is False, and as AnnotatedOperation when annotated is True.

Parameters

• num_ctrl_qubits (int) – Number of controls to add. Defaults to 1.
• label (str | None) – Optional gate label. Defaults to None. Ignored if the controlled gate is implemented as an annotated operation.
• ctrl_state (int |str | None) – The control state of the gate, specified either as an integer or a bitstring (e.g. "110"). If None, defaults to the all-ones state 2**num_ctrl_qubits - 1.
• annotated (bool | None) – Indicates whether the controlled gate should be implemented as a controlled gate or as an annotated operation. If None, treated as False.

Returns

A controlled version of this gate.

Raises

QiskitError – invalid num_ctrl_qubits or ctrl_state.

copy(name=None)

Copy of the instruction.

Parameters

name (str) – name to be given to the copied circuit, if None then the name stays the same.

Returns

a copy of the current instruction, with the name updated if it was provided

Return type

qiskit.circuit.Instruction

inverse(annotated=False)

Invert this instruction.

If annotated is False, the inverse instruction is implemented as a fresh instruction with the recursively inverted definition.

If annotated is True, the inverse instruction is implemented as AnnotatedOperation, and corresponds to the given instruction annotated with the “inverse modifier”.

Special instructions inheriting from Instruction can implement their own inverse (e.g. T and Tdg, Barrier, etc.) In particular, they can choose how to handle the argument annotated which may include ignoring it and always returning a concrete gate class if the inverse is defined as a standard gate.

Parameters

annotated (bool) – if set to True the output inverse gate will be returned as AnnotatedOperation.

Returns

The inverse operation.

Raises

CircuitError – if the instruction is not composite and an inverse has not been implemented for it.

is_parameterized()

Return whether the Instruction contains compile-time parameters.

power(exponent, annotated=False)

Raise this gate to the power of exponent.

Implemented either as a unitary gate (ref. UnitaryGate) or as an annotated operation (ref. AnnotatedOperation). In the case of several standard gates, such as RXGate, when the power of a gate can be expressed in terms of another standard gate that is returned directly.

Parameters

• exponent (float) – the power to raise the gate to
• annotated (bool) – indicates whether the power gate can be implemented as an annotated operation. In the case of several standard gates, such as RXGate, this argument is ignored when the power of a gate can be expressed in terms of another standard gate.

Returns

An operation implementing gate^exponent

Raises

CircuitError – If gate is not unitary

repeat(n)

Creates an instruction with self repeated $n$ times.

Parameters

n (int) – Number of times to repeat the instruction

Returns

Containing the definition.

Return type

qiskit.circuit.Instruction

Raises

CircuitError – If n < 1.

reverse_ops()

For a composite instruction, reverse the order of sub-instructions.

This is done by recursively reversing all sub-instructions. It does not invert any gate.

Returns

a new instruction with

sub-instructions reversed.

Return type

qiskit.circuit.Instruction

soft_compare(other)

Soft comparison between gates. Their names, number of qubits, and classical bit numbers must match. The number of parameters must match. Each parameter is compared. If one is a ParameterExpression then it is not taken into account.

Parameters

other (instruction) – other instruction.

Returns

are self and other equal up to parameter expressions.

Return type

bool

to_matrix()

Return a Numpy.array for the gate unitary matrix.

Returns

if the Gate subclass has a matrix definition.

Return type

np.ndarray

Raises

CircuitError – If a Gate subclass does not implement this method an exception will be raised when this base class method is called.

to_mutable()

Return a mutable copy of this gate.

This method will return a new mutable copy of this gate instance. If a singleton instance is being used this will be a new unique instance that can be mutated. If the instance is already mutable it will be a deepcopy of that instance.

validate_parameter(parameter)

Gate parameters should be int, float, or ParameterExpression