Bug fix in html docsing

examples/time_evolution_comparison.py

@@ -27,7 +27,11 @@ def create_heisenberg_hamiltonian(n, sparse=True):
 
 
 def create_initial_state(n):
-    """Create initial Neel state |↑↓↑↓↑↓↑↓> for n sites."""
+    r"""
+    Create initial Neel state
+    :math:`\vert \uparrow\downarrow\uparrow\downarrow\uparrow\downarrow\uparrow\downarrow\rangle`
+    for n sites.
+    """
     c = tc.Circuit(n)
     # Apply X gates to odd sites to create Neel state
     c.x([i for i in range(1, n, 2)])

examples/vqe_qudit_example.py

@@ -4,7 +4,7 @@
 This example shows how to run a simple VQE on a qudit system using
 `tensorcircuit.QuditCircuit`. We build a compact ansatz using single-qudit
 rotations in selected two-level subspaces and RXX-type entanglers, then
-optimize the energy of a Hermitian "clock–shift" Hamiltonian:
+optimize the energy of a Hermitian "clock-shift" Hamiltonian:
 
     H(d) = - J * (X_c \otimes X_c)  -  h * (Z_c \otimes I + I \otimes Z_c)
 
@@ -31,20 +31,20 @@
 
 
 def vqe_forward(param, *, nqudits: int, d: int, nlayers: int, J: float, h: float):
-    """Build a QuditCircuit ansatz and compute ⟨H⟩.
+    r"""Build a QuditCircuit ansatz and compute :math:`\langle H\rangle`.
 
     Ansatz:
       [ for L in 1...nlayers ]
         - On each site q:
-            RX(q; θ_Lq^(01)) ∘ RY(q; θ_Lq^(12)) ∘ RZ(q; φ_Lq^(0))
+            :math:`RX(q; \theta_L q^{(01)}) RY(q; \theta_L q^{(12)}) RZ(q; \phi_L q^{(0)})`
           (subspace indices shown as superscripts)
         - Entangle neighboring pairs with RXX on subspaces (0,1)
     """
     if d < 3:
         raise ValueError("This example assumes d >= 3 (qutrit or higher).")
 
-    S = tc.quditgates._x_matrix_func(d)
-    Z = tc.quditgates._z_matrix_func(d)
+    S = tc.quditgates.x_matrix_func(d)
+    Z = tc.quditgates.z_matrix_func(d)
     Sdag = tc.backend.adjoint(S)
     Zdag = tc.backend.adjoint(Z)
 
@@ -76,8 +76,8 @@ def vqe_forward(param, *, nqudits: int, d: int, nlayers: int, J: float, h: float
     return tc.backend.real(energy)
 
 
-def build_param_shape(nqudits: int, d: int, nlayers: int):
-    # Per layer per qudit: RX^(01), RY^(12) (or dummy), RZ^(0) = 3 params
+def build_param_shape(nqudits: int, nlayers: int):
+    # Per layer per qudit: RX^{(01)}, RY^{(12)} (or dummy), RZ^{(0)} = 3 params
     # Per layer entanglers: len(pairs) parameters
     pairs = nqudits - 1
     per_layer = 3 * nqudits + pairs
@@ -86,7 +86,7 @@ def build_param_shape(nqudits: int, d: int, nlayers: int):
 
 def main():
     parser = argparse.ArgumentParser(
-        description="VQE on QuditCircuit (clock–shift model)"
+        description="VQE on QuditCircuit (clock-shift model)"
     )
     parser.add_argument(
         "--d", type=int, default=3, help="Local dimension per site (>=3)"

tensorcircuit/applications/layers.py

@@ -35,7 +35,7 @@
 
 def _resolve(symbol: Union[Symbol, Tensor], i: int = 0) -> Tensor:
     """
-    Make sure the layer is compatible with both multi-param and single param requirements。
+    Make sure the layer is compatible with both multi-param and single param requirements
 
     What could be the input: list/tuple of sympy.symbol, tf.tensor with 1D or 0D shape
     """

tensorcircuit/backends/abstract_backend.py

@@ -1039,8 +1039,8 @@ def searchsorted(self: Any, a: Tensor, v: Tensor, side: str = "left") -> Tensor:
         :type a: Tensor
         :param v: value to inserted
         :type v: Tensor
-        :param side:  If ‘left’, the index of the first suitable location found is given.
-            If ‘right’, return the last such index.
+        :param side:  If `left`, the index of the first suitable location found is given.
+            If `right`, return the last such index.
             If there is no suitable index, return either 0 or N (where N is the length of a),
             defaults to "left"
         :type side: str, optional

tensorcircuit/basecircuit.py

@@ -3,7 +3,7 @@
 
 Note:
   - Supports qubit (d = 2) and qudit (d >= 2) systems.
-  - For string-encoded samples/counts when d <= 36, digits use base-d characters 0–9A–Z (A = 10, …, Z = 35).
+  - For string-encoded samples/counts when d <= 36, digits use base-d characters 0-9A-Z (A = 10, ..., Z = 35).
 """
 
 # pylint: disable=invalid-name
@@ -362,7 +362,7 @@ def to_qir(self) -> List[Dict[str, Any]]:
 
     def perfect_sampling(self, status: Optional[Tensor] = None) -> Tuple[str, float]:
         """
-        Sampling base-d strings (0–9A–Z when d <= 36) from the circuit output based on quantum amplitudes.
+        Sampling base-d strings (0-9A-Z when d <= 36) from the circuit output based on quantum amplitudes.
         Reference: arXiv:1201.3974.
 
         :param status: external randomness, with shape [nqubits], defaults to None
@@ -604,7 +604,7 @@ def sample(
                 "count_tuple": # (np.array([0]), np.array([2]))
 
                 "count_dict_bin": # {"00": 2, "01": 0, "10": 0, "11": 0}
-                    for cases d\in [11, 36], use 0–9A–Z digits (e.g., 'A' -> 10, …, 'Z' -> 35);
+                    for cases d\in [11, 36], use 0-9A-Z digits (e.g., 'A' -> 10, ..., 'Z' -> 35);
 
                 "count_dict_int": # {0: 2, 1: 0, 2: 0, 3: 0}
 

tensorcircuit/circuit.py

@@ -1,7 +1,7 @@
 """
 Quantum circuit: the state simulator.
 Supports qubit (dim=2) and qudit (3 <= dim <= 36) systems.
-For string-encoded samples/counts, digits use 0–9A–Z where A=10, …, Z=35.
+For string-encoded samples/counts, digits use 0-9A-Z where A=10, ..., Z=35.
 """
 
 # pylint: disable=invalid-name
@@ -768,7 +768,7 @@ def measure_reference(
         Take measurement on the given quantum lines by ``index``.
 
         Return format:
-        - For d <= 36, the sample is a base-d string using 0–9A–Z (A=10,…).
+        - For d <= 36, the sample is a base-d string using 0-9A-Z (A=10,...).
 
         :Example:
 
@@ -874,7 +874,7 @@ def expectation(
         :param nmc: repetition time for Monte Carlo sampling for noisfy calculation, defaults to 1000
         :type nmc: int, optional
         :param status: external randomness given by tensor uniformly from [0, 1], defaults to None,
-            used for noisfy circuit sampling
+            used for noisy circuit sampling
         :type status: Optional[Tensor], optional
         :raises ValueError: "Cannot measure two operators in one index"
         :return: Tensor with one element

tensorcircuit/densitymatrix.py

@@ -179,9 +179,9 @@ def _contract(self) -> None:
 
     @staticmethod
     def check_kraus(kraus: Sequence[Gate]) -> bool:
-        """
+        r"""
         Check if Kraus operators satisfy the completeness relation:
-        sum_i K_i^† K_i = I
+        :math:`\sum_i K_i^\dagger K_i = I`
 
         :param kraus: Sequence of Kraus operators
         :type kraus: Sequence[Gate]

tensorcircuit/quantum.py

@@ -79,7 +79,7 @@ def _decode_basis_label(label: str, n: int, dim: int) -> List[int]:
     """
     Decode a string basis label into a list of integer digits.
 
-    The label is interpreted in base-``dim`` using characters ``0–9A–Z``.
+    The label is interpreted in base-``dim`` using characters ``0-9A-Z``.
     Only dimensions up to 36 are supported.
 
     :param label: basis label string, e.g. "010" or "A9F"
@@ -97,7 +97,7 @@ def _decode_basis_label(label: str, n: int, dim: int) -> List[int]:
     """
     if dim > 36:
         raise NotImplementedError(
-            f"String basis label supports d<=36 (0–9A–Z). Got dim={dim}. "
+            f"String basis label supports d<=36 (0-9A-Z). Got dim={dim}. "
             "Use an integer array/tensor of length n instead."
         )
     s = label.upper()
@@ -107,7 +107,7 @@ def _decode_basis_label(label: str, n: int, dim: int) -> List[int]:
     for ch in s:
         if ch not in _ALPHABET:
             raise ValueError(
-                f"Invalid character '{ch}' in basis label (allowed 0–9A–Z)."
+                f"Invalid character '{ch}' in basis label (allowed 0-9A-Z)."
             )
         v = _ALPHABET.index(ch)
         if v >= dim:
@@ -751,7 +751,7 @@ def tensor_product(self, other: "QuOperator") -> "QuOperator":
         """
         Tensor product with another operator.
         Given two operators `A` and `B`, produces a new operator `AB` representing
-        :math:`A ⊗ B`. The `out_edges` (`in_edges`) of `AB` is simply the
+        :math:`A \otimes B`. The `out_edges` (`in_edges`) of `AB` is simply the
         concatenation of the `out_edges` (`in_edges`) of `A.copy()` with that of
         `B.copy()`:
         `new_out_edges = [*out_edges_A_copy, *out_edges_B_copy]`
@@ -2403,13 +2403,13 @@ def free_energy(
 
 def renyi_entropy(rho: Union[Tensor, QuOperator], k: int = 2) -> Tensor:
     """
-    Compute the Rényi entropy of order :math:`k` by given density matrix.
+    Compute the Renyi entropy of order :math:`k` by given density matrix.
 
     :param rho: The density matrix in form of Tensor or QuOperator.
     :type rho: Union[Tensor, QuOperator]
-    :param k: The order of Rényi entropy, default is 2.
+    :param k: The order of Renyi entropy, default is 2.
     :type k: int, optional
-    :return: The :math:`k` th order of Rényi entropy.
+    :return: The :math:`k` th order of Renyi entropy.
     :rtype: Tensor
     """
     s = 1 / (1 - k) * backend.real(backend.log(trace_product(*[rho for _ in range(k)])))
@@ -2423,7 +2423,7 @@ def renyi_free_energy(
     k: int = 2,
 ) -> Tensor:
     """
-    Compute the Rényi free energy of the corresponding density matrix and Hamiltonian.
+    Compute the Renyi free energy of the corresponding density matrix and Hamiltonian.
 
     :Example:
 
@@ -2440,9 +2440,9 @@ def renyi_free_energy(
     :type h: Union[Tensor, QuOperator]
     :param beta: Constant for the optimization, default is 1.
     :type beta: float, optional
-    :param k: The order of Rényi entropy, default is 2.
+    :param k: The order of Renyi entropy, default is 2.
     :type k: int, optional
-    :return: The :math:`k` th order of Rényi entropy.
+    :return: The :math:`k` th order of Renyi entropy.
     :rtype: Tensor
     """
     energy = backend.real(trace_product(rho, h))