Graph States
A graph state is a multipartite qubit state specified by a simple undirected graph. Vertices are qubits, edges prescribe entangling controlled- operations, and the resulting state is characterized by a set of commuting Pauli products supported on vertices and their neighbors.
Graph states are important because they turn complicated multipartite entanglement into combinatorial data. They include cluster states used in measurement-based quantum computing, give compact examples of stabilizer states, and provide useful test cases for entanglement witnesses and quantum error correction.
Helpful background. Composite operators makes the omitted identity factors precise; Pauli matrices supplies the commutation rules used in the stabilizers.
Graphs and Qubits
Section titled “Graphs and Qubits”Let
be a simple undirected graph with vertex set
Each vertex labels one qubit, so the Hilbert space is
The neighborhood of a vertex is
Thus the graph records which qubits are directly connected in the state-preparation circuit. It is not, by itself, a physical lattice unless a particular implementation supplies one.
Controlled-Z Construction
Section titled “Controlled-Z Construction”Start with every qubit in
For each edge , apply the controlled- gate
on qubits and in the computational basis. The graph state is
All controlled- gates are diagonal in the computational basis, so they commute. The product therefore does not depend on the order of the edges.
Equivalently,
The exponent is interpreted modulo : every edge whose two endpoint bits are both contributes a minus sign.
First Examples
Section titled “First Examples”If is empty, then
so the state is fully product.
For a graph with two vertices and one edge,
This is an entangled two-qubit state. It is locally unitarily equivalent to a Bell state. For example, applying a Hadamard gate to the second qubit gives
For a three-qubit path graph
the graph state is a linear three-qubit cluster state. For a star graph with one center connected to all other vertices, the graph state is locally Clifford equivalent to a GHZ state: apply a Hadamard to every leaf, leaving the center unchanged. The center generator becomes and each leaf generator becomes .
These equivalences are useful, but they do not mean the graph is irrelevant. Different graphs organize correlations, measurements, and code constructions in different ways.
Stabilizer Description Preview
Section titled “Stabilizer Description Preview”Graph states have a compact Pauli-eigenvalue description. For each vertex , define
where acts as the Pauli on qubit , and acts as the Pauli on qubit .
The graph state is the unique simultaneous eigenstate of all these operators:
The reason is simple. The product state is stabilized by every :
Conjugating by the controlled- gates incident on gives
Thus the simple stabilizers of become the graph-state stabilizers .
The operators commute with each other. If two vertices are not adjacent, the corresponding Pauli factors do not conflict. If two vertices are adjacent, each stabilizer has one where the other has one , giving two anticommutations in the product and hence an overall commutation.
Linear Cluster Example
Section titled “Linear Cluster Example”For the path graph , the neighborhoods are
The stabilizer generators are
These three commuting observables specify the three-qubit graph state as their common eigenstate. Notice that each stabilizer is local in the graph-theoretic sense: it acts on a vertex and its neighbors.
For a longer one-dimensional chain, the interior generators have the form
This pattern is the algebraic signature of a one-dimensional cluster state.
Entanglement from Graph Connectivity
Section titled “Entanglement from Graph Connectivity”Disconnected graphs give product states across connected components. If
with no edge connecting the two components, then
up to the ordering convention for tensor factors.
Connected graph states are entangled across every nontrivial bipartition of the vertices. More quantitatively, for a bipartition , the Schmidt rank of a graph state is determined by the adjacency matrix connecting the two sides:
Here is the submatrix of the graph adjacency matrix with rows in and columns in , and the rank is over the two-element field . This formula is one reason graph states are analytically tractable: some entanglement data can be read from binary linear algebra.
The formula should not be mistaken for a full multipartite classification. Graph states are a structured family, not the space of all multipartite states.
The nonzero reduced-state eigenvalues are all , so the entropy in bits is also . This is a binary matrix rank, not a count of crossing edges and not generally the rank over the real numbers (Hein, Eisert, and Briegel).
For example, let and . Two separate edges and give , rank two, and two bits of entropy. Connecting every vertex of to every vertex of gives , rank one, and only one bit. More crossing edges need not mean more entanglement across a specified cut.
Two independent crossing edges give two bits of entanglement across . Four crossing edges with identical adjacency rows give only one bit. The dashed line marks the chosen partition; the edge count alone does not determine the Schmidt rank.
Cluster states and measurements
Section titled “Cluster states and measurements”A cluster state is a graph state on a lattice such as a line or square grid. In measurement-based quantum computation, the graph is combined with designated input/output qubits, adaptive single-qubit measurement bases, and outcome-dependent corrections. A graph state alone is not yet a computational protocol; for example, a one-dimensional chain is not a universal resource for arbitrary quantum computation under single-qubit measurements.
A simple state-level rule illustrates the role of outcomes. Measuring vertex in with outcome bit removes that vertex and its incident edges. The state on the remaining vertices is
with probability for either outcome. Thus the remaining graph is known up to local corrections. Forgetting the outcome instead produces a mixture of the two branches. Photonic qubits discusses how destructive measurements and photon loss affect such preparations.
Reading an edge correctly
Section titled “Reading an edge correctly”An edge specifies a controlled- in this preparation, not necessarily an interaction that remains switched on. Nor does it promise entanglement in the two-qubit marginal of its endpoints: in the three-vertex path, all pair marginals are separable because the state is locally equivalent to GHZ. The graph describes a global state, and local Clifford changes can give different graphs for equivalent entanglement patterns.
References
Section titled “References”- M. Hein, J. Eisert, and H. J. Briegel, “Multiparty entanglement in graph states”, Physical Review A 69, 062311 (2004).
- M. Hein, W. Dür, J. Eisert, R. Raussendorf, M. Van den Nest, and H.-J. Briegel, “Entanglement in graph states and its applications”, in Quantum Computers, Algorithms and Chaos, IOS Press (2006), pp. 115–218.
- R. Raussendorf and H. J. Briegel, “A one-way quantum computer”, Physical Review Letters 86, 5188–5191 (2001).
- M. Van den Nest, J. Dehaene, and B. De Moor, “Graphical description of the action of local Clifford transformations on graph states”, Physical Review A 69, 022316 (2004).
Exercises
Section titled “Exercises”- Show that all controlled- gates in the graph-state construction commute.
Solution
Each controlled- gate is diagonal in the computational basis. Diagonal matrices commute with each other, even when they act on overlapping qubits. Therefore the product
is independent of the order chosen for the edges.
- Compute the two-qubit graph state for one edge and verify that applying gives .
Solution
Starting from
the controlled- gate flips the sign only on :
Using
one finds
- For the path graph , verify that and commute.
Solution
The only qubits where nonidentity Pauli operators from both products meet are qubits and . On qubit , anticommutes with . On qubit , anticommutes with . These two minus signs cancel, so
- If a graph has two disconnected components and , show that the graph state factors across those components.
Solution
The initial state factors:
Because there are no edges between components, the controlled- gates split into a product of gates internal to and gates internal to . Hence
up to tensor-factor ordering.
- For a six-vertex graph cut into and , let the cross-adjacency matrix be
Compute the Schmidt rank and entropy. Why would real matrix rank give the wrong answer?
Solution
Over , the third row is the sum of the first two, while the first two are independent. Thus , Schmidt rank is , and entropy is two bits. Over the reals the determinant is , so the real rank is three. Graph-state phase addition is modulo two, which is why that real rank is irrelevant here.