gate

Quantum gates

Classes

ArbitraryGate([name, nqubit, wires, minmax, ...])	A base class for customized gates.
Barrier([nqubit, wires, name])	Barrier.
CNOT([nqubit, wires, den_mat, tsr_mode])	CNOT gate.
CombinedSingleGate(gates[, name, nqubit, ...])	Combined single-qubit gate.
DoubleControlGate([name, nqubit, wires, ...])	A base class for two-qubit controlled gates.
DoubleGate([name, nqubit, wires, controls, ...])	A base class for two-qubit gates.
Fredkin([nqubit, wires, den_mat, tsr_mode])	Fredkin gate.
Hadamard([nqubit, wires, controls, ...])	Hadamard gate.
HamiltonianGate(hamiltonian[, t, nqubit, ...])	Hamiltonian gate.
Identity([nqubit, wires, den_mat, tsr_mode])	Identity gate.
ImaginarySwap([nqubit, wires, controls, ...])	Imaginary Swap gate.
LatentGate([inputs, nqubit, wires, minmax, ...])	Latent gate.
Move([nqubit, wires, postselect, tsr_mode])	Move, a two-qubit operation representing a reset of the second qubit followed by a swap.
ParametricDoubleGate([name, inputs, nqubit, ...])	A base class for two-qubit gates with parameters.
ParametricSingleGate([name, inputs, nqubit, ...])	A base class for single-qubit gates with parameters.
PauliX([nqubit, wires, controls, condition, ...])	PauliX gate.
PauliY([nqubit, wires, controls, condition, ...])	PauliY gate.
PauliZ([nqubit, wires, controls, condition, ...])	PauliZ gate.
PhaseShift([inputs, nqubit, wires, ...])	Phase shift gate.
ProjectionJ([inputs, nqubit, wires, plane, ...])	Matrix J to project the measurement basis.
ReconfigurableBeamSplitter([inputs, nqubit, ...])	Reconfigurable Beam Splitter gate.
Reset([nqubit, wires, postselect, tsr_mode])	Reset.
Rx([inputs, nqubit, wires, controls, ...])	Rx gate, rotation around x-axis.
Rxx([inputs, nqubit, wires, controls, ...])	Rxx gate.
Rxy([inputs, nqubit, wires, controls, ...])	Rxy gate.
Ry([inputs, nqubit, wires, controls, ...])	Ry gate, rotation around y-axis.
Ryy([inputs, nqubit, wires, controls, ...])	Ryy gate.
Rz([inputs, nqubit, wires, controls, ...])	Rz gate, rotation around z-axis.
Rzz([inputs, nqubit, wires, controls, ...])	Rzz gate.
SDaggerGate([nqubit, wires, controls, ...])	S dagger gate.
SGate([nqubit, wires, controls, condition, ...])	S gate.
SingleGate([name, nqubit, wires, controls, ...])	A base class for single-qubit gates.
Swap([nqubit, wires, controls, condition, ...])	Swap gate.
TDaggerGate([nqubit, wires, controls, ...])	T dagger gate.
TGate([nqubit, wires, controls, condition, ...])	T gate.
Toffoli([nqubit, wires, den_mat, tsr_mode])	Toffoli gate.
TripleGate([name, nqubit, wires, controls, ...])	A base class for three-qubit gates.
U3Gate([inputs, nqubit, wires, controls, ...])	U3 gate, a generic single-qubit rotation gate with 3 angles.
UAnyGate(unitary[, nqubit, wires, minmax, ...])	Arbitrary unitary gate.
WireCut([nqubit, wires])	Wire Cut.

class ArbitraryGate(name: str | None = None, nqubit: int = 1, wires: int | list[int] | None = None, minmax: list[int] | None = None, controls: int | list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: Gate

A base class for customized gates.

Parameters:

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• minmax (list[int] | None) – The minimum and maximum indices of the qubits that the quantum operation acts on. Only valid when wires is None. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

inverse() → ArbitraryGate

Get the inversed gate.

class Barrier(nqubit: int = 1, wires: int | list[int] | None = None, name: str = 'Barrier')

Bases: Gate

Barrier.

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• name (str) – The name of the gate. Default: 'Barrier'

forward(x: Any) → Any

Perform a forward pass.

pattern(nodes: list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class CNOT(nqubit: int = 2, wires: list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: DoubleControlGate

CNOT gate.

Matrix Representation:

\[\begin{split}\text{CNOT} = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 \\ 0 & 0 & 1 & 0 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

pattern(nodes: list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class CombinedSingleGate(gates: list[SingleGate], name: str | None = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

Combined single-qubit gate.

Parameters:

• gates (list[SingleGate]) – The list of single-qubit gates.

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

add(gate: SingleGate) → None

Add a single-qubit gate to the list and update the local unitary matrix.

get_derivative(inputs: Any) → Tensor

Get the derivatives of the local unitary matrix.

get_matrix() → Tensor

Get the local unitary matrix.

inverse() → CombinedSingleGate

Get the inversed gate.

update_matrix() → Tensor

Update the local unitary matrix.

update_npara() → None

Update the number of parameters.

class DoubleControlGate(name: str | None = None, nqubit: int = 2, wires: list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: DoubleGate

A base class for two-qubit controlled gates.

Parameters:

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

class DoubleGate(name: str | None = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: Gate

A base class for two-qubit gates.

Parameters:

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

class Fredkin(nqubit: int = 3, wires: list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: TripleGate

Fredkin gate.

Matrix Representation:

\[\begin{split}\text{Fredkin} = \begin{pmatrix} 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 3

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

class Hadamard(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

Hadamard gate.

Matrix Representation:

\[\begin{split}H = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

pattern(nodes: int | list[int], ancilla: int | list[int]) → Sequential

Get the MBQC pattern.

class HamiltonianGate(hamiltonian: Any, t: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, minmax: list[int] | None = None, controls: int | list[int] | None = None, name: str = 'HamiltonianGate', den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ArbitraryGate

Hamiltonian gate.

Parameters:

• hamiltonian (Any) – The Hamiltonian. It can be a list, e.g., [[0.5, 'x0y1'], [-1, 'z3y1']] for \(0.5 * \sigma^x_0 \otimes \sigma^y_1 - \sigma^y_1 \otimes \sigma^z_3\). It can also be a torch.Tensor when wires or minmax is specified.

• t (Any) – The evolution time. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Only valid when hamiltonian is not a list. Default: None

• minmax (list[int] | None) – The minimum and maximum indices of the qubits that the quantum operation acts on. Only valid when hamiltonian is not a list and wires is None. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• name (str) – The name of the gate. Default: 'HamiltonianGate'

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_derivative(t: Any) → Tensor

Get the derivative of the local unitary matrix.

get_matrix(hamiltonian: Any, t: Any) → Tensor

Get the local unitary matrix.

get_minmax(hamiltonian: list) → list[int]

Get minmax according to the Hamiltonian.

init_para(inputs: list | None = None) → None

Initialize the parameters.

inputs_to_tensor(inputs: list | None = None) → tuple[Tensor, Tensor]

Convert inputs to torch.Tensor.

update_matrix() → Tensor

Update the local unitary matrix.

class Identity(nqubit: int = 1, wires: int | list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: Gate

Identity gate.

Matrix Representation:

\[\begin{split}I = \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

forward(x: Any) → Any

Perform a forward pass.

get_unitary() → Tensor

Get the global unitary matrix.

class ImaginarySwap(nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: DoubleGate

Imaginary Swap gate.

Matrix Representation:

\[\begin{split}\text{iSWAP} = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & 0 & i & 0 \\ 0 & i & 0 & 0 \\ 0 & 0 & 0 & 1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

class LatentGate(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, minmax: list[int] | None = None, controls: int | list[int] | None = None, name: str = 'LatentGate', den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ArbitraryGate

Latent gate.

Parameters:

• inputs (Any) – Any given real matrix.

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• minmax (list[int] | None) – The minimum and maximum indices of the qubits that the quantum operation acts on. Only valid when wires is None. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• name (str) – The name of the gate. Default: 'LatentGate'

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameters are nn.Parameter or buffer. Default: False (which means buffer)

get_derivative(latent: Any) → Tensor

Get the derivatives of the local unitary matrix.

get_matrix(inputs: Any) → Tensor

Get the local unitary matrix.

init_para(inputs: Any = None) → None

Initialize the parameters.

inputs_to_tensor(inputs: Any = None) → Tensor

Convert inputs to torch.Tensor.

update_matrix() → Tensor

Update the local unitary matrix.

class Move(nqubit: int = 2, wires: list[int] | None = None, postselect: int | None = 0, tsr_mode: bool = False)

Bases: DoubleGate

Move, a two-qubit operation representing a reset of the second qubit followed by a swap.

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• postselect (int | None) – The postselected value. Default: 0 (None means no postselection, which is not compatible with vmap)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

forward(x: Tensor) → Tensor

Perform a forward pass.

qpd(label: int | None = None) → MoveQPD

Get the quasiprobability-decomposition representation.

class ParametricDoubleGate(name: str | None = None, inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: DoubleGate

A base class for two-qubit gates with parameters.

Parameters:

• name (str | None) – The name of the gate. Default: None

• inputs (Any) – The parameters of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameters are nn.Parameter or buffer. Default: False (which means buffer)

extra_repr() → str

get_derivative(theta: Any) → Tensor

Get the derivative of the local unitary matrix.

init_para(inputs: Any = None) → None

Initialize the parameters.

inputs_to_tensor(inputs: Any = None) → Tensor

Convert inputs to torch.Tensor.

inverse() → ParametricDoubleGate

Get the inversed gate.

update_matrix() → Tensor

Update the local unitary matrix.

class ParametricSingleGate(name: str | None = None, inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: SingleGate

A base class for single-qubit gates with parameters.

Parameters:

• name (str | None) – The name of the gate. Default: None

• inputs (Any) – The parameters of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameters are nn.Parameter or buffer. Default: False (which means buffer)

extra_repr() → str

get_derivative(theta: Any) → Tensor

Get the derivative of the local unitary matrix.

init_para(inputs: Any = None) → None

Initialize the parameters.

inputs_to_tensor(inputs: Any = None) → Tensor

Convert inputs to torch.Tensor.

inverse() → ParametricSingleGate

Get the inversed gate.

update_matrix() → Tensor

Update the local unitary matrix.

class PauliX(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

PauliX gate.

Matrix Representation:

\[\begin{split}X = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

pattern(nodes: int | list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class PauliY(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

PauliY gate.

Matrix Representation:

\[\begin{split}Y = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

pattern(nodes: int | list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class PauliZ(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

PauliZ gate.

Matrix Representation:

\[\begin{split}Z = \begin{pmatrix} 1 & 0 \\ 0 & -1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

pattern(nodes: int | list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class PhaseShift(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

Phase shift gate.

Matrix Representation:

\[\begin{split}P(\theta) = \begin{pmatrix} 1 & 0 \\ 0 & e^{i\theta} \end{pmatrix}\end{split}\]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

inputs_to_tensor(inputs: Any = None) → Tensor

Convert inputs to torch.Tensor.

class ProjectionJ(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, plane: str = 'xy', controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

Matrix J to project the measurement basis.

The matrix \(J(\theta)\) transforms the measurement in the XY, YZ, or ZX plane to Z measurement. The transformation means \(M(\theta)|\psi\rangle = M_z J(\theta)|\psi\rangle\), where \(M_z\) is the Z-basis measurement.

Matrix Representation:

\[\begin{split}J_{\text{XY}}(\theta) = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & e^{-i\theta} \\ 1 & -e^{-i\theta} \end{pmatrix}\end{split}\]

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}J_{\text{YZ}}(\theta) = \frac{1}{\sqrt{2}} \begin{pmatrix} \cos(\th) + \sin(\th) & -i(\cos(\th) - \sin(\th)) \\ \cos(\th) - \sin(\th) & i(\cos(\th) + \sin(\th)) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}J_{\text{ZX}}(\theta) = \begin{pmatrix} \cos(\th) & \sin(\th) \\ \sin(\th) & -\cos(\th) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• plane (str) – The measurement plane ('xy', 'yz', or 'zx'). Default: 'xy'

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

extra_repr() → str

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

class ReconfigurableBeamSplitter(inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricDoubleGate

Reconfigurable Beam Splitter gate.

Matrix Representation:

\[\begin{split}\text{RBS}(\theta) = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & \cos\left(\theta\right) & \sin\left(\theta\right) & 0 \\ 0 & -\sin\left(\theta\right) & \cos\left(\theta\right) & 0 \\ 0 & 0 & 0 & 1 \end{pmatrix}\end{split}\]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

inputs_to_tensor(inputs: Any = None) → Tensor

Convert inputs to torch.Tensor.

class Reset(nqubit: int = 1, wires: int | list[int] | None = None, postselect: int | None = 0, tsr_mode: bool = False)

Bases: Gate

Reset.

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• postselect (int | None) – The postselected value. Default: 0 (None means no postselection, which is not compatible with vmap)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

op_state(x: Tensor) → Tensor

Perform a forward pass for state vectors.

class Rx(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

Rx gate, rotation around x-axis.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_x(\theta) = \begin{pmatrix} \cos\left(\th\right) & -i\sin\left(\th\right) \\ -i\sin\left(\th\right) & \cos\left(\th\right) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

pattern(nodes: int | list[int], ancilla: list[int], angle: Any, requires_grad: bool = False) → Sequential

Get the MBQC pattern.

class Rxx(inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricDoubleGate

Rxx gate.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_{xx}(\theta) = \exp\left(-i \th X{\otimes}X\right) = \begin{pmatrix} \cos\left(\th\right) & 0 & 0 & -i\sin\left(\th\right) \\ 0 & \cos\left(\th\right) & -i\sin\left(\th\right) & 0 \\ 0 & -i\sin\left(\th\right) & \cos\left(\th\right) & 0 \\ -i\sin\left(\th\right) & 0 & 0 & \cos\left(\th\right) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

class Rxy(inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricDoubleGate

Rxy gate.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_{xy}(\theta) = \exp\left(-i \th X{\otimes}Y\right) = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & \cos\left(\th\right) & -i\sin\left(\th\right) & 0 \\ 0 & -i\sin\left(\th\right) & \cos\left(\th\right) & 0 \\ 0 & 0 & 0 & 1 \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

class Ry(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

Ry gate, rotation around y-axis.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_y(\theta) = \begin{pmatrix} \cos\left(\th\right) & -\sin\left(\th\right) \\ \sin\left(\th\right) & \cos\left(\th\right) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

pattern(nodes: int | list[int], ancilla: list[int], angle: Any, requires_grad: bool = False) → Sequential

Get the MBQC pattern.

class Ryy(inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricDoubleGate

Ryy gate.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_{yy}(\theta) = \exp\left(-i \th Y{\otimes}Y\right) = \begin{pmatrix} \cos\left(\th\right) & 0 & 0 & i\sin\left(\th\right) \\ 0 & \cos\left(\th\right) & -i\sin\left(\th\right) & 0 \\ 0 & -i\sin\left(\th\right) & \cos\left(\th\right) & 0 \\ i\sin\left(\th\right) & 0 & 0 & \cos\left(\th\right) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

class Rz(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

Rz gate, rotation around z-axis.

Matrix Representation:

\[\begin{split}R_z(\theta) = \begin{pmatrix} e^{-i\frac{\theta}{2}} & 0 \\ 0 & e^{i\frac{\theta}{2}} \end{pmatrix}\end{split}\]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

pattern(nodes: int | list[int], ancilla: list[int], angle: Any, requires_grad: bool = False) → Sequential

Get the MBQC pattern.

class Rzz(inputs: Any = None, nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricDoubleGate

Rzz gate.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}R_{zz}(\theta) = \exp\left(-i \th Z{\otimes}Z\right) = \begin{pmatrix} e^{-i \th} & 0 & 0 & 0 \\ 0 & e^{i \th} & 0 & 0 \\ 0 & 0 & e^{i \th} & 0 \\ 0 & 0 & 0 & e^{-i \th} \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameter of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

get_matrix(theta: Any) → Tensor

Get the local unitary matrix.

class SDaggerGate(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

S dagger gate.

Matrix Representation:

\[\begin{split}S^{\dagger} = \begin{pmatrix} 1 & 0 \\ 0 & -i \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

inverse() → SGate

Get the inversed gate.

class SGate(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

S gate.

Matrix Representation:

\[\begin{split}S = \begin{pmatrix} 1 & 0 \\ 0 & i \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

inverse() → SDaggerGate

Get the inversed gate.

pattern(nodes: int | list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class SingleGate(name: str | None = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: Gate

A base class for single-qubit gates.

Parameters:

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

op_dist_state(x: DistributedQubitState) → DistributedQubitState

Perform a forward pass of a gate for a distributed state vector.

class Swap(nqubit: int = 2, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: DoubleGate

Swap gate.

Matrix Representation:

\[\begin{split}\text{SWAP} = \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & 0 & 1 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 2

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

op_dist_state(x: DistributedQubitState) → DistributedQubitState

Perform a forward pass of a gate for a distributed state vector.

class TDaggerGate(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

T dagger gate.

Matrix Representation:

\[\begin{split}T^{\dagger} = \begin{pmatrix} 1 & 0 \\ 0 & e^{-i\pi/4} \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

inverse() → TGate

Get the inversed gate.

class TGate(nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: SingleGate

T gate.

Matrix Representation:

\[\begin{split}T = \begin{pmatrix} 1 & 0 \\ 0 & e^{i\pi/4} \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

inverse() → TDaggerGate

Get the inversed gate.

class Toffoli(nqubit: int = 3, wires: list[int] | None = None, den_mat: bool = False, tsr_mode: bool = False)

Bases: TripleGate

Toffoli gate.

Matrix Representation:

\[\begin{split}\text{Toffoli} = \begin{pmatrix} 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\ 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 \end{pmatrix}\end{split}\]

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 3

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

get_unitary() → Tensor

Get the global unitary matrix.

pattern(nodes: list[int], ancilla: list[int]) → Sequential

Get the MBQC pattern.

class TripleGate(name: str | None = None, nqubit: int = 3, wires: list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False)

Bases: Gate

A base class for three-qubit gates.

Parameters:

• name (str | None) – The name of the gate. Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 3

• wires (list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

class U3Gate(inputs: Any = None, nqubit: int = 1, wires: int | list[int] | None = None, controls: int | list[int] | None = None, condition: bool = False, den_mat: bool = False, tsr_mode: bool = False, requires_grad: bool = False)

Bases: ParametricSingleGate

U3 gate, a generic single-qubit rotation gate with 3 angles.

Matrix Representation:

\[ \begin{align}\begin{aligned}\newcommand{\th}{\frac{\theta}{2}}\\\begin{split}U_3(\theta, \phi, \lambda) = \begin{pmatrix} \cos\left(\th\right) & -e^{i\lambda}\sin\left(\th\right) \\ e^{i\phi}\sin\left(\th\right) & e^{i(\phi+\lambda)}\cos\left(\th\right) \end{pmatrix}\end{split}\end{aligned}\end{align} \]

Parameters:

• inputs (Any) – The parameters of the gate (\(\theta\), \(\phi\) and \(\lambda\)). Default: None

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• condition (bool) – Whether to use controls as conditional measurement. Default: False

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

• requires_grad (bool) – Whether the parameters are nn.Parameter or buffer. Default: False (which means buffer)

extra_repr() → str

get_derivative(inputs: Any) → Tensor

Get the derivatives of the local unitary matrix.

get_matrix(theta: Any, phi: Any, lambd: Any) → Tensor

Get the local unitary matrix.

init_para(inputs: Any = None) → None

Initialize the parameters.

inputs_to_tensor(inputs: Any = None) → tuple[Tensor, Tensor, Tensor]

Convert inputs to torch.Tensor.

update_matrix() → Tensor

Update the local unitary matrix.

class UAnyGate(unitary: Any, nqubit: int = 1, wires: int | list[int] | None = None, minmax: list[int] | None = None, controls: int | list[int] | None = None, name: str = 'UAnyGate', den_mat: bool = False, tsr_mode: bool = False)

Bases: ArbitraryGate

Arbitrary unitary gate.

Parameters:

• unitary (Any) – Any given unitary matrix.

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int] | None) – The indices of the qubits that the quantum operation acts on. Default: None

• minmax (list[int] | None) – The minimum and maximum indices of the qubits that the quantum operation acts on. Only valid when wires is None. Default: None

• controls (int | list[int] | None) – The indices of the control qubits. Default: None

• name (str) – The name of the gate. Default: 'UAnyGate'

• den_mat (bool) – Whether the quantum operation acts on density matrices or state vectors. Default: False (which means state vectors)

• tsr_mode (bool) – Whether the quantum operation is in tensor mode, which means the input and output are represented by a tensor of shape \((\text{batch}, 2, ..., 2)\). Default: False

update_matrix() → Tensor

Update the local unitary matrix.

class WireCut(nqubit: int = 1, wires: int | list[int] = 0)

Bases: Barrier

Wire Cut.

Parameters:

• nqubit (int) – The number of qubits that the quantum operation acts on. Default: 1

• wires (int | list[int]) – The indices of the qubits that the quantum operation acts on. Default: 0