deepquantum.mbqc package#

Submodules#

deepquantum.mbqc.command module#

MBQC commands

class deepquantum.mbqc.command.Node(nodes: int | List[int])#

基类：Command

Node (qubit) preparation command.

参数:: nodes (int or List[int]) – The indices of the nodes to prepare.

forward(x: GraphState) → GraphState#: Perform a forward pass by adding SubGraphState in the GraphState.

class deepquantum.mbqc.command.Entanglement(node1: int, node2: int)#

基类：Command

Entanglement command.

参数:

node1 (int) – The first node index.
node2 (int) – The second node index.

forward(x: GraphState) → GraphState#: Perform a forward pass by adding an edge in the GraphState.

基类：Command

Measurement command.

参数:

nodes (int or List[int]) – The indices of the nodes to measure.
plane (str, optional) – The measurement plane ('xy', 'yz' or 'zx'). Default: 'xy'
angle (Any, optional) – The measurement angle in radians. Default: 0.
s_domain (Union[int, Iterable[int], None], optional) – The indices of the nodes that contribute to signal domain s. Default: None
t_domain (Union[int, Iterable[int], None], optional) – The indices of the nodes that contribute to signal domain t. Default: None
requires_grad (bool, optional) – Whether the parameter is nn.Parameter or buffer. Default: False (which means buffer)

inputs_to_tensor(inputs: Any | None = None) → Tensor#: Convert inputs to torch.Tensor.

forward(x: GraphState) → GraphState#: Perform a forward pass by measuring the GraphState.

init_para(angle: Any | None = None) → None#: Initialize the parameters.

class deepquantum.mbqc.command.Correction(nodes: int | List[int], basis: str = 'x', domain: int | Iterable[int] | None = None)#

基类：Command

Correction command.

参数:

nodes (int or List[int]) – The indices of the nodes to correct.
basis (str, optional) – The type of correction ('x' or 'z'). Default: 'x'
domain (Union[int, Iterable[int], None], optional) – The indices of the nodes that contribute to signal domain s. Default: None

forward(x: GraphState) → GraphState#: Perform a forward pass by correcting the GraphState.

deepquantum.mbqc.operation module#

Base classes

class deepquantum.mbqc.operation.Operation(name: str | None = None, nodes: int | List[int] | None = None)#

基类：Module

A base class for quantum operations.

参数:

name (str or None, optional) – The name of the quantum operation. Default: None
nodes (int, List[int] or None, optional) – The indices of the nodes that the quantum operation acts on. Default: None

class deepquantum.mbqc.operation.Command(name: str, nodes: int | List[int])#

基类：Operation

A base class for MBQC commands.

参数:

name (str) – The name of the command.
nodes (int or List[int]) – The indices of the nodes that the command acts on.

forward(x: GraphState) → GraphState#: Perform a forward pass.

deepquantum.mbqc.pattern module#

Measurement pattern

基类：Operation

Measurement-based quantum computing (MBQC) pattern.

A Pattern represents a measurement-based quantum computation, which consists of a sequence of commands (node preparation, entanglement, measurement, and correction) applied to qubits arranged in a graph structure.

参数:

nodes_state (int, List[int] or None) – The nodes of the input state in the subgraph. It can be an integer representing the number of nodes or a list of node indices. Default: None.
state (Any, optional) – The initial state of the subgraph. Default: 'plus'.
edges (List or None, optional) – Additional edges connecting the nodes in the subgraph. Default: None.
nodes (int, List[int] or None, optional) – Additional nodes to include in the subgraph. Default: None.
name (str or None, optional) – The name of the pattern. Default: None

Ref: V. Danos, E. Kashefi and P. Panangaden. J. ACM 54.2 8 (2007)

forward(data: Tensor | None = None, state: GraphState | None = None) → Tensor#

Perform a forward pass of the MBQC pattern and return the final graph state.

参数:

data (torch.Tensor or None, optional) – The input angle data for the encoders. Default: None
state (GraphState or None, optional) – The initial state for the pattern. Default: None

返回:

The final graph state of the pattern after applying the commands.

返回类型:

GraphState

Add a subgraph to the graph state.

参数:

nodes_state (int, List[int] or None) – The nodes of the input state in the subgraph. It can be an integer representing the number of nodes or a list of node indices. Default: None.
state (Any, optional) – The initial state of the subgraph. Default: 'plus'.
edges (List or None, optional) – Additional edges connecting the nodes in the subgraph. Default: None.
nodes (int, List[int] or None, optional) – Additional nodes to include in the subgraph. Default: None.
measure_dict (Dict, optional) – A dictionary to record measurement results. Default: None.
index (int or None, optional) – The index where to insert the subgraph. Default: None.

get_graph()#

add(op: Operation, encode: bool = False) → None#

A method that adds an operation to the MBQC pattern.

参数:

op (Operation) – The operation to add. It is an instance of Operation class or its subclasses, such as Node, or Measurement.
encode (bool) – Whether the command encodes data. Default: False

encode(data: Tensor | None) → None#

Encode the input data into measurement angle as parameters.

This method iterates over the encoders of the pattern(encode=True measurements) and initializes their parameters with the input data. The input data must be at least as long as the number of parameters in the encoders.

参数:: data (torch.Tensor or None) – The input data for the encoders, must be a 1D tensor.
抛出:: AssertionError – If input data is shorter than the number of parameters in the encoders.

n(node: int | List[int])#

Add a new node to the pattern.

参数:: node (int or List[int]) – Index or list of indices for the new node.

e(node: List[int])#

Add an entanglement operators on two nodes in the pattern.

参数:: node (List[int]) – A list of two integers specifying the nodes to entangle. Must reference existing nodes in the pattern.

Add a measurement operation to the pattern.

参数:

node (int) – The node to measure.
plane (str, optional) – Measurement plane (‘xy’, ‘yz’, or ‘xz’). Defaults to ‘xy’.
angle (float) – Measurement angle in radians. Defaults to 0.
t_domain (int, Iterable[int] or None], optional) – List of nodes that contribute to the Z correction. Default: None
s_domain (int, Iterable[int] or None], optional) – List of nodes that contribute to the X correction. Default: None
encode (bool) – Whether to encode angle. Default: False.

c_x(node: int, domain: int | Iterable[int] | None = None)#

Add an X correction operation to the pattern.

参数:

node (int) – The node to apply the X correction.
domain (int, Iterable[int] or None], optional) – List of nodes on which the signal depends. Default: None

c_z(node: int, domain: int | Iterable[int] | None = None)#

Add a Z correction operation to the pattern.

参数:

node (int) – The node to apply the Z correction.
domain (int, Iterable[int] or None], optional) – List of nodes on which the signal depends. Default: None

draw(width: int = 4)#: Draw the MBQC pattern.

is_standard() → bool#

Determine whether the command sequence is standard.

返回:: A bool value, True if the pattern follows NEMC standardization, False otherwise

standardize()#

Standardize the command sequence into NEMC form.

This function reorders operations into the standard form: - Node preparations (N) - Entanglement operations (E) - Measurement operations (M) - Correction operations (C)

It handles the propagation of correction operations by: 1. Moving X-corrections through entanglements (generating Z-corrections) 2. Moving corrections through measurements (modifying measurement signal domains) 3. Collecting remaining corrections at the end

See https://arxiv.org/pdf/0704.1263 Ch.(5.4)

shift_signals() → Dict#

Perform signal shifting procedure. This allows one to dispose of dependencies induced by the Z-action, and obtain sometimes standard patterns with smaller computational depth complexity.

It handles the propagation of signal shifting commands by: 1. Extracting signals via t_domain(in XY plane cases) of measurements. 2. Moving signals to the left, through modifying other measurements and corrections.

返回:: A signal dictionary including all the signal shifting commands.

See https://arxiv.org/pdf/0704.1263 Ch.(5.5)

deepquantum.mbqc.state module#

Quantum states

基类：Module

A subgraph state of a quantum state.

参数:

nodes_state (int, List[int] or None, optional) – The nodes of the input state in the subgraph. It can be an integer representing the number of nodes or a list of node indices. Default: None.
state (Any, optional) – The initial state of the subgraph. Default: 'plus'.
edges (List or None, optional) – Additional edges connecting the nodes in the subgraph. Default: None.
nodes (int, List[int] or None, optional) – Additional nodes to include in the subgraph. Default: None.

property nodes#: Nodes of the graph.

property edges#: Edges of the graph.

property full_state: Tensor#: Compute and return the full quantum state of the subgraph.

set_graph(nodes_state: int | List[int] | None = None, edges: List | None = None, nodes: int | List[int] | None = None) → None#: Set the graph structure for the subgraph state.

set_state(state: Any = 'plus') → None#: Set the quantum state of the subgraph.

add_nodes(nodes: int | List[int]) → None#: Add nodes to the subgraph.

add_edges(edges: List) → None#: Add edges to the subgraph.

shift_labels(n: int) → None#: Shift the labels of the nodes in the graph by a given integer.

compose(other: SubGraphState, relabel: bool = True) → SubGraphState#

Compose this subgraph state with another subgraph state.

参数:

other (SubGraphState) – The other subgraph state to compose with.
relabel (bool, optional) – Whether to relabel nodes to avoid conflicts. Default: True.

返回:

A new subgraph state that is the composition of the two.

返回类型:

SubGraphState

update_node2wire_dict() → Dict#

Update the mapping from nodes to wire indices.

返回:: A dictionary mapping nodes to their corresponding wire indices.
返回类型:: Dict

draw(**kwargs)#: Draw the graph using NetworkX.

基类：Module

A graph state composed by several SubGraphStates.

参数:

nodes_state (int, List[int] or None, optional) – The nodes of the input state in the subgraph. It can be an integer representing the number of nodes or a list of node indices. Default: None.
state (Any, optional) – The initial state of the subgraph. Default: 'plus'.
edges (List or None, optional) – Additional edges connecting the nodes in the subgraph. Default: None.
nodes (int, List[int] or None, optional) – Additional nodes to include in the subgraph. Default: None.

Add a subgraph to the graph state.

参数:

nodes_state (int, List[int] or None, optional) – The nodes of the input state in the subgraph. It can be an integer representing the number of nodes or a list of node indices. Default: None.
state (Any, optional) – The initial state of the subgraph. Default: 'plus'.
edges (List or None, optional) – Additional edges connecting the nodes in the subgraph. Default: None.
nodes (int, List[int] or None, optional) – Additional nodes to include in the subgraph. Default: None.
measure_dict (Dict or None, optional) – A dictionary to record measurement results. Default: None.
index (int or None, optional) – The index where to insert the subgraph. Default: None.

property graph: SubGraphState#: The combined graph of all subgraphs.

property measure_dict: Dict#: A dictionary containing all measurement results for the graph state.

Module contents#

MBQC Module