Merge pull request #853 from Shivansh20128/847-function-equivalency

Replacing "pure_to_mixed" with "vector_to_density_matrix" and then renaming to "to_density_matrix"

toqito/matrix_ops/__init__.py

@@ -8,4 +8,4 @@
 from toqito.matrix_ops.vectors_from_gram_matrix import vectors_from_gram_matrix
 from toqito.matrix_ops.vectors_to_gram_matrix import vectors_to_gram_matrix
 from toqito.matrix_ops.calculate_vector_matrix_dimension import calculate_vector_matrix_dimension
-from toqito.matrix_ops.vector_to_density_matrix import vector_to_density_matrix
+from toqito.matrix_ops.to_density_matrix import to_density_matrix

toqito/matrix_ops/tests/test_vector_to_density_matrix.py → toqito/matrix_ops/tests/test_to_density_matrix.py

@@ -1,9 +1,9 @@
-"""Test vector_to_density_matrix."""
+"""Test to_density_matrix."""
 
 import numpy as np
 import pytest
 
-from toqito.matrix_ops import vector_to_density_matrix
+from toqito.matrix_ops import to_density_matrix
 
 
 @pytest.mark.parametrize(
@@ -23,11 +23,11 @@
         (np.array([[[1, 0], [0, 1]]]), None, ValueError),
     ],
 )
-def test_vector_to_density_matrix(input_vector, expected_output, exception):
+def test_to_density_matrix(input_vector, expected_output, exception):
     """Test vector to density matrix functionality."""
     if exception:
         with pytest.raises(exception):
-            vector_to_density_matrix(input_vector)
+            to_density_matrix(input_vector)
     else:
-        computed_density_matrix = vector_to_density_matrix(input_vector)
+        computed_density_matrix = to_density_matrix(input_vector)
         assert (np.abs(computed_density_matrix - expected_output) <= 1e-3).all()

toqito/matrix_ops/vector_to_density_matrix.py → toqito/matrix_ops/to_density_matrix.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 
-def vector_to_density_matrix(input_array: np.ndarray) -> np.ndarray:
+def to_density_matrix(input_array: np.ndarray) -> np.ndarray:
     """Convert a given vector to a density matrix or return the density matrix if already given.
 
     If the input is a vector, this function computes the outer product to form a density matrix.
@@ -15,9 +15,9 @@ def vector_to_density_matrix(input_array: np.ndarray) -> np.ndarray:
     As an example, consider one of the Bell states.
 
     >>> from toqito.states import bell
-    >>> from toqito.matrix_ops import vector_to_density_matrix
+    >>> from toqito.matrix_ops import to_density_matrix
     >>>
-    >>> vector_to_density_matrix(bell(0))
+    >>> to_density_matrix(bell(0))
     array([[0.5, 0. , 0. , 0.5],
            [0. , 0. , 0. , 0. ],
            [0. , 0. , 0. , 0. ],

toqito/measurements/pretty_good_measurement.py

@@ -3,7 +3,7 @@
 import numpy as np
 import scipy
 
-from toqito.matrix_ops import vector_to_density_matrix
+from toqito.matrix_ops import to_density_matrix
 
 
 def pretty_good_measurement(states: list[np.ndarray], probs: list[float] | None = None) -> list[np.ndarray]:
@@ -69,7 +69,7 @@ def pretty_good_measurement(states: list[np.ndarray], probs: list[float] | None
     if not np.isclose(sum(probs), 1):
         raise ValueError("Probability vector should sum to 1.")
 
-    states = [vector_to_density_matrix(state) for state in states]
+    states = [to_density_matrix(state) for state in states]
     p_var = sum(probs[i] * states[i] for i in range(n))
 
     p_var_sqrt = scipy.linalg.fractional_matrix_power(p_var, -1 / 2)

toqito/state_ops/__init__.py

@@ -1,4 +1,3 @@
 """Operations on quantum states."""
 
-from toqito.state_ops.pure_to_mixed import pure_to_mixed
 from toqito.state_ops.schmidt_decomposition import schmidt_decomposition

toqito/state_opt/ppt_distinguishability.py

@@ -3,7 +3,7 @@
 import numpy as np
 import picos
 
-from toqito.matrix_ops import calculate_vector_matrix_dimension, vector_to_density_matrix
+from toqito.matrix_ops import calculate_vector_matrix_dimension, to_density_matrix
 from toqito.matrix_props import has_same_dimension
 
 
@@ -156,7 +156,7 @@ def _min_error_primal(
         ]
     )
 
-    dms = [vector_to_density_matrix(vector) for vector in vectors]
+    dms = [to_density_matrix(vector) for vector in vectors]
     if strategy == "unambig":
         for i in range(n):
             for j in range(n):
@@ -189,7 +189,7 @@ def _min_error_dual(
     y_var = picos.HermitianVariable("Y", (d, d))
     problem.add_list_of_constraints(
         [
-            y_var - probs[i] * vector_to_density_matrix(vectors[i])
+            y_var - probs[i] * to_density_matrix(vectors[i])
             >> picos.partial_transpose(
                 q_var,
                 subsystems=subsystems,

toqito/state_opt/state_distinguishability.py

@@ -3,7 +3,7 @@
 import numpy as np
 import picos
 
-from toqito.matrix_ops import calculate_vector_matrix_dimension, vector_to_density_matrix, vectors_to_gram_matrix
+from toqito.matrix_ops import calculate_vector_matrix_dimension, to_density_matrix, vectors_to_gram_matrix
 from toqito.matrix_props import has_same_dimension
 
 
@@ -167,7 +167,7 @@ def _min_error_primal(
     problem.add_list_of_constraints([meas >> 0 for meas in measurements])
     problem.add_constraint(picos.sum(measurements) == picos.I(dim))
 
-    dms = [vector_to_density_matrix(vector) for vector in vectors]
+    dms = [to_density_matrix(vector) for vector in vectors]
 
     problem.set_objective("max", np.real(picos.sum([(probs[i] * dms[i] | measurements[i]) for i in range(n)])))
     solution = problem.solve(solver=solver, **kwargs)
@@ -188,7 +188,7 @@ def _min_error_dual(
     # Set up variables and constraints for SDP:
     y_var = picos.HermitianVariable("Y", (dim, dim))
     problem.add_list_of_constraints(
-        [y_var >> probs[i] * vector_to_density_matrix(vector) for i, vector in enumerate(vectors)]
+        [y_var >> probs[i] * to_density_matrix(vector) for i, vector in enumerate(vectors)]
     )
 
     # Objective function:

toqito/state_opt/state_exclusion.py

@@ -3,7 +3,7 @@
 import numpy as np
 import picos
 
-from toqito.matrix_ops import calculate_vector_matrix_dimension, vector_to_density_matrix, vectors_to_gram_matrix
+from toqito.matrix_ops import calculate_vector_matrix_dimension, to_density_matrix, vectors_to_gram_matrix
 from toqito.matrix_props import has_same_dimension
 
 
@@ -185,7 +185,7 @@ def _min_error_primal(
     problem.add_list_of_constraints([meas >> 0 for meas in measurements])
     problem.add_constraint(picos.sum(measurements) == picos.I(dim))
 
-    dms = [vector_to_density_matrix(vector) for vector in vectors]
+    dms = [to_density_matrix(vector) for vector in vectors]
     # # Numerical inaccuracies can make it so the trace of the density matrices aren't unital, which messes up with
     # # cvxopt
     # dms = [state / np.trace(state) for state in dms]
@@ -209,7 +209,7 @@ def _min_error_dual(
     # Set up variables and constraints for SDP:
     y_var = picos.HermitianVariable("Y", (dim, dim))
     problem.add_list_of_constraints(
-        [y_var << probs[i] * vector_to_density_matrix(vector) for i, vector in enumerate(vectors)]
+        [y_var << probs[i] * to_density_matrix(vector) for i, vector in enumerate(vectors)]
     )
 
     # Objective function:
@@ -239,7 +239,7 @@ def _unambiguous_primal(
     problem.add_list_of_constraints([meas >> 0 for meas in measurements])
     problem.add_constraint(inconclusive_measurement >> 0)
 
-    unnormalized_dms = [p * vector_to_density_matrix(vector) for (p, vector) in zip(probs, vectors)]
+    unnormalized_dms = [p * to_density_matrix(vector) for (p, vector) in zip(probs, vectors)]
     sums_of_unnormalized_dms = picos.sum(unnormalized_dms)
 
     problem.add_list_of_constraints(m | rho == 0 for (m, rho) in zip(measurements, unnormalized_dms))
@@ -268,7 +268,7 @@ def _unambiguous_dual(
 
     problem.add_constraint(lagrangian_variable_big_n >> 0)
 
-    dms = [vector_to_density_matrix(vector) for (p, vector) in zip(probs, vectors)]
+    dms = [to_density_matrix(vector) for (p, vector) in zip(probs, vectors)]
     unnormalized_dms = [proba * rho for (proba, rho) in zip(probs, dms)]
     sum_of_unnormalized_dms = picos.sum(unnormalized_dms)
 

toqito/state_opt/tests/test_state_distinguishability.py

@@ -4,7 +4,7 @@
 import pytest
 
 from toqito.matrices import standard_basis
-from toqito.matrix_ops import vector_to_density_matrix
+from toqito.matrix_ops import to_density_matrix
 from toqito.state_opt import state_distinguishability
 from toqito.states import bb84, bell
 
@@ -14,7 +14,7 @@
     # Bell states (should be perfectly distinguishable)
     ([bell(0), bell(1), bell(2), bell(3)], 1),
     # Bell states as density matrices
-    ([vector_to_density_matrix(bell(i)) for i in range(4)], 1),
+    ([to_density_matrix(bell(i)) for i in range(4)], 1),
     # BB84 states
     (bb84()[0] + bb84()[1], .5),
 ]

toqito/state_opt/tests/test_state_exclusion.py

@@ -4,7 +4,7 @@
 import pytest
 
 from toqito.matrices import standard_basis
-from toqito.state_ops import pure_to_mixed
+from toqito.matrix_ops import to_density_matrix
 from toqito.state_opt import state_exclusion
 from toqito.states import bell
 
@@ -14,8 +14,8 @@
     # Bell states are perfectly distinguishable, so the probability of error should be nil
     ([bell(0), bell(1), bell(2), bell(3)], None, 0, {}),
     ([bell(0), bell(1), bell(2), bell(3)], [1 / 4, 1 / 4, 1 / 4, 1 / 4], 0, {}),
-    ([pure_to_mixed(bell(0)), pure_to_mixed(bell(1))], None, 0, {"cvxopt_kktsolver": "ldl"}),
-    ([pure_to_mixed(bell(0)), pure_to_mixed(bell(1))], [1 / 2, 1 / 2], 0, {"cvxopt_kktsolver": "ldl"}),
+    ([to_density_matrix(bell(0)), to_density_matrix(bell(1))], None, 0, {"cvxopt_kktsolver": "ldl"}),
+    ([to_density_matrix(bell(0)), to_density_matrix(bell(1))], [1 / 2, 1 / 2], 0, {"cvxopt_kktsolver": "ldl"}),
     # For |0> and |+>, this probability is 1/2 - 1/(2*sqrt(2))
     (
         [np.array([[1.], [0.]]), np.array([[1.], [1.]]) / np.sqrt(2)],
@@ -35,8 +35,8 @@
     # Bell states are perfectly distinguishable, so the probability of error should be nil
     ([bell(0), bell(1), bell(2), bell(3)], None, 0, {}),
     ([bell(0), bell(1), bell(2), bell(3)], [1 / 4, 1 / 4, 1 / 4, 1 / 4], 0, {}),
-    ([pure_to_mixed(bell(0)), pure_to_mixed(bell(1))], None, 0, {}),
-    ([pure_to_mixed(bell(0)), pure_to_mixed(bell(1))], [1 / 2, 1 / 2], 0, {}),
+    ([to_density_matrix(bell(0)), to_density_matrix(bell(1))], None, 0, {}),
+    ([to_density_matrix(bell(0)), to_density_matrix(bell(1))], [1 / 2, 1 / 2], 0, {}),
     # For |0> and |+>, this probability is 1/sqrt(2)
     (
         [np.array([[1.], [0.]]), np.array([[1.], [1.]]) / np.sqrt(2)],

toqito/state_props/l1_norm_coherence.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from toqito.state_ops import pure_to_mixed
+from toqito.matrix_ops import to_density_matrix
 
 
 def l1_norm_coherence(rho: np.ndarray) -> float:
@@ -49,5 +49,5 @@ def l1_norm_coherence(rho: np.ndarray) -> float:
     :return: The l1-norm coherence of :code:`rho`.
 
     """
-    rho = pure_to_mixed(rho)
+    rho = to_density_matrix(rho)
     return np.sum(np.sum(np.abs(rho))) - np.trace(rho)

toqito/state_props/log_negativity.py

@@ -3,7 +3,7 @@
 import numpy as np
 from picos import partial_transpose
 
-from toqito.state_ops import pure_to_mixed
+from toqito.matrix_ops import to_density_matrix
 
 
 def log_negativity(rho: np.ndarray, dim: list[int] | int = None) -> float:
@@ -46,7 +46,7 @@ def log_negativity(rho: np.ndarray, dim: list[int] | int = None) -> float:
 
     """
     # Allow the user to input either a pure state vector or a density matrix.
-    rho = pure_to_mixed(rho)
+    rho = to_density_matrix(rho)
     rho_dims = rho.shape
     round_dim = np.round(np.sqrt(rho_dims))
 

toqito/state_props/negativity.py

@@ -3,7 +3,7 @@
 import numpy as np
 from picos import partial_transpose
 
-from toqito.state_ops import pure_to_mixed
+from toqito.matrix_ops import to_density_matrix
 
 
 def negativity(rho: np.ndarray, dim: list[int] | int = None) -> float:
@@ -47,7 +47,7 @@ def negativity(rho: np.ndarray, dim: list[int] | int = None) -> float:
 
     """
     # Allow the user to input either a pure state vector or a density matrix.
-    rho = pure_to_mixed(rho)
+    rho = to_density_matrix(rho)
     rho_dims = rho.shape
     round_dim = np.round(np.sqrt(rho_dims))