initial commit

pennylane/ftqc/cluster_state.py

@@ -0,0 +1,123 @@
+# Copyright 2025 Xanadu Quantum Technologies Inc.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""This module contains the classes and functions for creating and diagonalizing
+midcircuit measurements with a parameterized measurement axis."""
+
+
+import networkx as nx
+import math
+import matplotlib.pyplot as plt
+from networkx import Graph
+
+
+class ClusterState:
+    """Class of stabilizer-formalism cluster state for measurement-based quantum computing(MBQC).
+
+    Cluster states is a specific instance of a graph state as illustated in [Entanglement in Graph States and its Applications, arXiv:quant-ph/0602096].
+    With cluster states, univeral computation can be realized without the need of making use of any controlled two-system quantum gates. 
+
+    Vertex connectivity:
+    A cluster state can be defined in 1,2 and 3 dimensions, correponding to 1-D chain lattice, 2-D rectangular lattice and 3-D cubic lattices. 
+    
+    Stabilizer:
+    Each vertex is a cluster state represents a qubit and there is one stabilizer generator S_j per graph vertex j of the form
+    S_j = X_{j} \prod_{k\in N(j)} Z_k
+    where the neighborhood N(j) is the set of vertices which share an edge with j [Cluster-state code, https://errorcorrectionzoo.org/c/cluster_state].
+
+    #TODO: do we need 
+
+    
+
+    Args:
+
+    graph: nx.Graph
+
+    """
+    _short_name = "cluster_state"
+
+    def __init__(self, dims: list = None, graph: Graph = None):
+        assert len(dims) <= 3, f"{len(dims)}-dimensional cluster state is not supported."
+        self._graph = len(dims)
+
+
+    def _create_1d_chain(dims):
+        labels = list(range(dims[0]))
+        G = nx.Graph()
+        for label in labels:
+            G.add_node(label)
+
+        for label in labels[1:]:
+            G.add_edge(label - 1, label, label='CNOT')
+
+        return G
+
+    def _create_2d_rectangle(dims):
+        assert len(dims) == 2, f"Rectangle lattice requires a 2 dims input, but {len(dims)} dim is provided"
+        num_labels = math.prod(dims)
+        labels = list(range(num_labels))
+        G = nx.Graph()
+        # Add nodes to the graph
+        for label in labels:
+            G.add_node(label)
+
+        # Add row edges to the graph
+        for j in range(dims[1]):
+            for i in range(dims[0] - 1):
+                start = j*dims[0] + i
+                end = start + 1
+                G.add_edge(start, end, lable='CNOT')
+
+        for j in range(dims[1] - 1):
+            for i in range(dims[0]):
+                start = j*dims[0] + i
+                end = start + dims[0]
+                G.add_edge(start, end, label='CNOT')
+
+        return G
+
+    def _create_3d_cubic(dims):
+        assert len(dims) == 3, f"cubic lattice requires a 3 dims input, but {len(dims)} dim is provided"
+        num_labels = math.prod(dims)
+        labels = list(range(num_labels))
+        G = nx.Graph()
+        # Add nodes to the graph
+        for label in labels:
+            G.add_node(label)
+
+        # Add row edges to the graph
+        for k in range(dims[2]):
+            for j in range(dims[1]):
+                for i in range(dims[0] - 1):
+                    start = k*dims[1]*dims[0]+ j*dims[0] + i
+                    end = start + 1
+                    G.add_edge(start, end, label='CNOT')
+
+        for k in range(dims[2]):
+            for j in range(dims[1] - 1):
+                for i in range(dims[0]):
+                    start = k*dims[1]*dims[0]+ j*dims[0] + i
+                    end = start + dims[0]
+                    G.add_edge(start, end, label='CNOT')
+
+        for k in range(dims[2]-1):
+            for j in range(dims[1]):
+                for i in range(dims[0]):
+                    start = k*dims[1]*dims[0]+ j*dims[0] + i
+                    end = start + dims[1]*dims[0]
+                    G.add_edge(start, end, label='CNOT')
+
+        return G
+
+
+

requirements-dev.txt

@@ -14,3 +14,4 @@ isort==5.13.2
 pylint==2.7.4
 rich>=13.7.1
 tach==0.13.1
+graphviz