Merge branch 'doc-fix' of https://github.com/qiboteam/qibotn into doc…

…-fix
qiboteam · Mar 4, 2024 · 7c7d860 · 7c7d860
2 parents e6a3060 + 014a39c
commit 7c7d860
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Showing 2 changed files with 20 additions and 20 deletions.
diff --git a/src/qibotn/circuit_convertor.py b/src/qibotn/circuit_convertor.py
@@ -28,10 +28,10 @@ def __init__(self, circuit, dtype="complex128"):
     def state_vector_operands(self):
         """Create the operands for dense vector computation in the interleave
         format.
-        
+
         Parameters:
             None
-            
+
         Returns:
             Operands for the contraction in the interleave format.
         """
@@ -88,11 +88,11 @@ def _parse_gates_to_mode_labels_operands(
         return mode_labels, operands
 
     def op_shape_from_qubits(self, nqubits):
-        """Modify tensor to cuQuantum shape 
-        
+        """Modify tensor to cuQuantum shape.
+
         Parameters:
             nqubits (int): The number of qubits in quantum circuit.
-        
+
         Returns:
             (qubit_states,input_output) * nqubits
         """

diff --git a/src/qibotn/eval.py b/src/qibotn/eval.py
@@ -10,7 +10,7 @@
 def dense_vector_tn(qibo_circ, datatype):
     """Convert qibo circuit to tensornet (TN) format and perform contraction to
     dense vector.
-    
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
@@ -25,12 +25,12 @@ def dense_vector_tn(qibo_circ, datatype):
 def expectation_pauli_tn(qibo_circ, datatype, pauli_string_pattern):
     """Convert qibo circuit to tensornet (TN) format and perform contraction to
     expectation of given Pauli string.
-                 
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
         pauli_string_pattern(str): pauli string pattern.
-        
+
     Returns:
         Expectation of quantum circuit due to pauli string.
     """
@@ -52,12 +52,12 @@ def dense_vector_tn_MPI(qibo_circ, datatype, n_samples=8):
     the least costly contraction path. This is sped up with multi
     thread. After pathfinding the optimal path is used in the actual
     contraction to give a dense vector representation of the TN.
-    
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
         n_samples(int): Number of samples for pathfinding.
-        
+
     Returns:
         Dense vector of quantum circuit.
     """
@@ -127,12 +127,12 @@ def dense_vector_tn_nccl(qibo_circ, datatype, n_samples=8):
     the least costly contraction path. This is sped up with multi
     thread. After pathfinding the optimal path is used in the actual
     contraction to give a dense vector representation of the TN.
-         
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
         n_samples(int): Number of samples for pathfinding.
-        
+
     Returns:
         Dense vector of quantum circuit.
     """
@@ -216,13 +216,13 @@ def expectation_pauli_tn_nccl(qibo_circ, datatype, pauli_string_pattern, n_sampl
     select the least costly contraction path. This is sped up with multi
     thread. After pathfinding the optimal path is used in the actual
     contraction to give an expectation value.
-             
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
         pauli_string_pattern(str): pauli string pattern.
         n_samples(int): Number of samples for pathfinding.
-        
+
     Returns:
         Expectation of quantum circuit due to pauli string.
     """
@@ -308,13 +308,13 @@ def expectation_pauli_tn_MPI(qibo_circ, datatype, pauli_string_pattern, n_sample
     select the least costly contraction path. This is sped up with multi
     thread. After pathfinding the optimal path is used in the actual
     contraction to give an expectation value.
-                 
+
     Parameters:
         qibo_circ: The quantum circuit object.
         datatype (str): Either single ("complex64") or double (complex128) precision.
         pauli_string_pattern(str): pauli string pattern.
         n_samples(int): Number of samples for pathfinding.
-        
+
     Returns:
         Expectation of quantum circuit due to pauli string.
     """
@@ -378,12 +378,12 @@ def expectation_pauli_tn_MPI(qibo_circ, datatype, pauli_string_pattern, n_sample
 def dense_vector_mps(qibo_circ, gate_algo, datatype):
     """Convert qibo circuit to matrix product state (MPS) format and perform
     contraction to dense vector.
-                 
+
     Parameters:
         qibo_circ: The quantum circuit object.
         gate_algo(dict): Dictionary for SVD and QR settings.
         datatype (str): Either single ("complex64") or double (complex128) precision.
-        
+
     Returns:
         Dense vector of quantum circuit.
     """
@@ -402,10 +402,10 @@ def pauli_string_gen(nqubits, pauli_string_pattern):
     Parameters:
         nqubits(int): Number of qubits of Quantum Circuit
         pauli_string_pattern(str): Strings representing sequence of pauli gates.
-        
+
     Returns:
         String representation of the actual pauli string from the pattern.
-        
+
     Example: pattern: "XZ", number of qubit: 7, output = XZXZXZX
     """
     if nqubits <= 0: