TeamGraphix · thierry-martinez · Jul 18, 2026 · Jul 18, 2026 · Jul 18, 2026 · Jul 18, 2026
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -98,7 +98,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - #468, #511: The `pyzx` module has been moved to a separate plugin: https://github.com/thierry-martinez/graphix-pyzx/
   Consequently, the `pyproject.toml` no longer defines an `extra` dependency group for the `pyzx` package.
 
-- #512: Method `Circuit.simulate_statevector` accepts a `backend: DenseStateBackend[_DenseStateT] | Literal["statevector", "densitymatrix"]` parameter.
+- #512: Method `Circuit.simulate` (formerly `Circuit.simulate_statevector`, see #567)  accepts a `backend: DenseStateBackend[_DenseStateT] | Literal["statevector", "densitymatrix"]` parameter.
+
+- #567:
+  - Method `Circuit.simulate_statevector` has been renamed `Circuit.simulate`.
+  - Method `Pattern.simulate_pattern` has been renamed `Pattern.simulate`.
 
 ## [0.3.5] - 2026-03-26
 

diff --git a/README.md b/README.md
@@ -74,7 +74,7 @@ pattern.draw_graph()
 ### simulating the pattern
 
 ```python
-state_out = pattern.simulate_pattern(backend="statevector")
+state_out = pattern.simulate(backend="statevector")
 ```
 
 ### and more..

diff --git a/benchmarks/statevec.py b/benchmarks/statevec.py
@@ -5,7 +5,7 @@
 Here we benchmark our statevector simulator for MBQC.
 
 The methods and modules we use are the followings:
-    1. :meth:`graphix.pattern.Pattern.simulate_pattern`
+    1. :meth:`graphix.pattern.Pattern.simulate`
         Pattern simulator with statevector backend.
     2. :mod:`paddle_quantum.mbqc`
         Pattern simulation using :mod:`paddle_quantum.mbqc`.
@@ -87,12 +87,12 @@ def simple_random_circuit(nqubit, depth):
     pattern.minimize_space()
     nqubit = len(pattern.extract_nodes())
     start = perf_counter()
-    pattern.simulate_pattern(max_qubit_num=30)
+    pattern.simulate(max_qubit_num=30)
     end = perf_counter()
     print(f"width: {width}, nqubit: {nqubit}, depth: {DEPTH}, time: {end - start}")
     pattern_time.append(end - start)
     start = perf_counter()
-    circuit.simulate_statevector()
+    circuit.simulate()
     end = perf_counter()
     circuit_time.append(end - start)
 

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -35,7 +35,9 @@
 autosectionlabel_prefix_document = True
 
 intersphinx_mapping = {
+    "python": ("https://docs.python.org/3", None),
     "networkx": ("https://networkx.github.io/documentation/stable/", None),
+    "sympy": ("https://docs.sympy.org/latest/", None),
 }
 
 sys.path.insert(0, os.path.abspath("../../"))

diff --git a/docs/source/generator.rst b/docs/source/generator.rst
@@ -9,38 +9,7 @@ Pattern Generation
 .. currentmodule:: graphix.transpiler
 
 .. autoclass:: Circuit
-
-    .. automethod:: __init__
-
-    .. automethod:: transpile
-
-    .. automethod:: simulate_statevector
-
-    .. automethod:: cz
-
-    .. automethod:: cnot
-
-    .. automethod:: h
-
-    .. automethod:: s
-
-    .. automethod:: x
-
-    .. automethod:: y
-
-    .. automethod:: z
-
-    .. automethod:: rx
-
-    .. automethod:: ry
-
-    .. automethod:: rz
-
-    .. automethod:: j
-
-    .. automethod:: ccx
-
-    .. automethod:: m
+    :members:
 
 .. autoclass:: TranspiledPattern
 

diff --git a/docs/source/intro.rst b/docs/source/intro.rst
@@ -132,7 +132,7 @@ Note that the input state has *teleported* to qubits 6 and 7 after the computati
         import networkx as nx
         og = OpenGraph(nx.Graph([0, 1]), output_nodes=[0, 1])
 
-    >>> print(og.to_pattern().simulate_pattern())
+    >>> print(og.to_pattern().simulate())
     Statevec object with statevector [[ 0.5+0.j  0.5+0.j]
     [ 0.5+0.j -0.5+0.j]] and length (2, 2).
 

diff --git a/docs/source/modifier.rst b/docs/source/modifier.rst
@@ -7,84 +7,6 @@ Pattern Manipulation
 .. currentmodule:: graphix.pattern
 
 .. autoclass:: Pattern
-
-    .. automethod:: __init__
-
-    .. automethod:: add
-
-    .. automethod:: extend
-
-    .. automethod:: clear
-
-    .. automethod:: replace
-
-    .. automethod:: reorder_output_nodes
-
-    .. automethod:: reorder_input_nodes
-
-    .. automethod:: simulate_pattern
-
-    .. automethod:: compute_max_degree
-
-    .. automethod:: compose
-
-    .. automethod:: connected_nodes
-
-    .. automethod:: remove_input_nodes
-
-    .. automethod:: perform_pauli_pushing
-
-    .. automethod:: remove_pauli_measurements
-
-    .. automethod:: remove_local_clifford_commands
-
-    .. automethod:: to_ascii
-
-    .. automethod:: to_unicode
-
-    .. automethod:: to_latex
-
-    .. automethod:: standardize
-
-    .. automethod:: shift_signals
-
-    .. automethod:: is_standard
-
-    .. automethod:: extract_graph
-
-    .. automethod:: extract_nodes
-
-    .. automethod:: extract_causal_flow
-
-    .. automethod:: extract_gflow
-
-    .. automethod:: extract_opengraph
-
-    .. automethod:: extract_measurement_commands
-
-    .. automethod:: parallelize_pattern
-
-    .. automethod:: minimize_space
-
-    .. automethod:: draw
-
-    .. automethod:: max_space
-
-    .. automethod:: to_qasm3
-
-    .. automethod:: is_parameterized
-
-    .. automethod:: subs
-
-    .. automethod:: xreplace
-
-    .. automethod:: check_runnability
-
-    .. automethod:: map
-
-    .. automethod:: infer_pauli_measurements
-
-    .. automethod:: to_bloch
-
+    :members:
 
 .. autofunction:: shift_outcomes
diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
@@ -51,9 +51,9 @@ This is the simplest of the `graph state
 <https://en.wikipedia.org/wiki/Graph_state>`_ with nodes = [0, 1] and edge = (0, 1). Any MBQC pattern has a corresponding resource graph state on which the computation occurs only with single-qubit measurements.
 
 We can use the :class:`~graphix.simulator.PatternSimulator` to classically simulate the pattern above and obtain the output state, for default input state of :math:`|+\rangle`.
-Alternatively, we can simply call :meth:`~graphix.pattern.Pattern.simulate_pattern` of :class:`~graphix.pattern.Pattern` object to do it in one line:
+Alternatively, we can simply call :meth:`~graphix.pattern.Pattern.simulate` of :class:`~graphix.pattern.Pattern` object to do it in one line:
 
->>> print(pattern.simulate_pattern(backend='statevector'))
+>>> print(pattern.simulate(backend='statevector'))
 Statevec object with statevector [1.+0.j 0.+0.j] and length (2,).
 
 Note again that we started with :math:`|+\rangle` state so the answer is correct.
@@ -240,7 +240,7 @@ We can simulate the MBQC pattern with various noise models to understand their e
 
 .. code-block:: python
 
-    out_state = pattern.simulate_pattern(backend="statevector")
+    out_state = pattern.simulate(backend="statevector")
 
 The statevector backend simulates the pattern ideally, without any noise.
 

diff --git a/examples/deutsch_jozsa.py b/examples/deutsch_jozsa.py
@@ -90,8 +90,8 @@
 # So the preprocessing has done all the necessary computations, and all nodes are isolated with no further measurements required.
 # Let us make sure the result is correct:
 
-out_state = pattern.simulate_pattern()
-state = circuit.simulate_statevector().statevec
+out_state = pattern.simulate()
+state = circuit.simulate().statevec
 print("overlap of states: ", np.abs(np.dot(state.psi.flatten().conjugate(), out_state.psi.flatten())))
 
 # %%
diff --git a/examples/ghz_with_tn.py b/examples/ghz_with_tn.py
@@ -45,7 +45,7 @@
 # %%
 # Calculate the amplitudes of ``|00...0>`` and ``|11...1>`` states.
 
-tn = pattern.simulate_pattern(backend="tensornetwork")
+tn = pattern.simulate(backend="tensornetwork")
 print(f"The amplitude of |00...0>: {tn.basis_amplitude(0)}")
 print(f"The amplitude of |11...1>: {tn.basis_amplitude(2**n - 1)}")
 

diff --git a/examples/qaoa.py b/examples/qaoa.py
@@ -47,8 +47,8 @@
 # %%
 # finally, simulate the QAOA circuit
 
-out_state = pattern.simulate_pattern()
-state = circuit.simulate_statevector().statevec
+out_state = pattern.simulate()
+state = circuit.simulate().statevec
 print("overlap of states: ", np.abs(np.dot(state.psi.flatten().conjugate(), out_state.psi.flatten())))
 # sphinx_gallery_thumbnail_number = 2
 

diff --git a/examples/qft_with_tn.py b/examples/qft_with_tn.py
@@ -78,7 +78,7 @@ def qft(circuit: Circuit, n: int) -> None:
 import time
 
 t1 = time.time()
-tn = pattern.simulate_pattern(backend="tensornetwork")
+tn = pattern.simulate(backend="tensornetwork")
 value = tn.basis_amplitude(0)
 t2 = time.time()
 print("amplitude of |00...0> is ", value)

diff --git a/examples/rotation.py b/examples/rotation.py
@@ -68,7 +68,7 @@
 # Internally, we are executing the command sequence we inspected above on a statevector simulator.
 # We also have a tensornetwork simulation backend to handle larger MBQC patterns. see other examples for how to use it.
 
-out_state = pattern.simulate_pattern(backend="statevector")
+out_state = pattern.simulate(backend="statevector")
 print(out_state.flatten())
 
 # %%

diff --git a/examples/tn_simulation.py b/examples/tn_simulation.py
@@ -93,7 +93,7 @@ def ansatz(
 # The graph_prep argument is optional,
 # but with 'parallel' the TensorNetworkBackend will prepeare the graph state faster.
 
-mbqc_tn = pattern.simulate_pattern(backend="tensornetwork", graph_prep="parallel")
+mbqc_tn = pattern.simulate(backend="tensornetwork", graph_prep="parallel")
 sv = mbqc_tn.to_statevector().flatten()
 print("Statevector after the simulation:", sv)
 
@@ -206,7 +206,7 @@ def cost(
     pattern.remove_input_nodes()
     pattern = pattern.infer_pauli_measurements()
     pattern.remove_pauli_measurements(standardize=True)
-    mbqc_tn = pattern.simulate_pattern(backend="tensornetwork", graph_prep="parallel")
+    mbqc_tn = pattern.simulate(backend="tensornetwork", graph_prep="parallel")
     exp_val: float = 0
     for op in ham:
         exp_val += np.real(mbqc_tn.expectation_value(op, range(n), optimize=opt))
@@ -248,7 +248,7 @@ def __call__(
 pattern = circuit.transpile().pattern
 pattern.standardize()
 pattern.shift_signals()
-mbqc_tn = pattern.simulate_pattern(backend="tensornetwork", graph_prep="parallel")
+mbqc_tn = pattern.simulate(backend="tensornetwork", graph_prep="parallel")
 
 # %%
 # Let's use the defined optimizer and find the most probable basis states.

diff --git a/graphix/pattern.py b/graphix/pattern.py
@@ -389,7 +389,7 @@ def input_nodes(self) -> list[int]:
 
     @property
     def output_nodes(self) -> list[int]:
-        """List all nodes that are either `input_nodes` or prepared with `N` commands and that have not been measured with an `M` command."""
+        """List all nodes that are either ``input_nodes`` or prepared with ``N`` commands and that have not been measured with an ``M`` command."""
         return list(self.__output_nodes)  # copy for preventing modification
 
     def __len__(self) -> int:
@@ -1118,7 +1118,7 @@ def extract_pauli_flow(self) -> PauliFlow[Measurement]:
         return self.extract_xzcorrections().to_pauli_flow()
 
     def extract_xzcorrections(self) -> XZCorrections[Measurement]:
-        """Extract the XZ-corrections from the current measurement pattern.
+        r"""Extract the XZ-corrections from the current measurement pattern.
 
         Returns
         -------
@@ -1130,7 +1130,7 @@ def extract_xzcorrections(self) -> XZCorrections[Measurement]:
         XZCorrectionsError
             If the extracted correction dictionaries are not well formed.
         ValueError
-            If `N` commands in the pattern do not represent a |+⟩ state or if the pattern corrections form closed loops.
+            If ``N`` commands in the pattern do not represent a :math:`\ket{+}` state or if the pattern corrections form closed loops.
 
         Notes
         -----
@@ -1398,7 +1398,7 @@ def space_list(self) -> list[int]:
         return n_list
 
     @overload
-    def simulate_pattern(
+    def simulate(
         self,
         backend: StatevectorBackend | Literal["statevector"] = "statevector",
         input_state: State
@@ -1412,7 +1412,7 @@ def simulate_pattern(
     ) -> Statevec: ...
 
     @overload
-    def simulate_pattern(
+    def simulate(
         self,
         backend: DensityMatrixBackend | Literal["densitymatrix"],
         input_state: State
@@ -1426,7 +1426,7 @@ def simulate_pattern(
     ) -> DensityMatrix: ...
 
     @overload
-    def simulate_pattern(
+    def simulate(
         self,
         backend: TensorNetworkBackend | Literal["tensornetwork", "mps"],
         input_state: State
@@ -1439,15 +1439,15 @@ def simulate_pattern(
     ) -> MBQCTensorNet: ...
 
     @overload
-    def simulate_pattern(
+    def simulate(
         self,
         backend: Backend[_StateT_co],
         input_state: Data | None = ...,
         rng: Generator | None = ...,
         **kwargs: Any,
     ) -> _StateT_co: ...
 
-    def simulate_pattern(
+    def simulate(
         self,
         backend: Backend[_StateT_co] | _BackendLiteral = "statevector",
         input_state: Data | None = BasicStates.PLUS,

diff --git a/graphix/sim/statevec.py b/graphix/sim/statevec.py
@@ -574,7 +574,7 @@ def draw(
         >>> circuit = Circuit(2)
         >>> circuit.h(0)
         >>> circuit.cz(0, 1)
-        >>> print(circuit.simulate_statevector().statevec.draw())
+        >>> print(circuit.simulate().statevec.draw())
         √2/2(|00⟩ + |01⟩)
         """
         return statevec_to_str(