Fixing errors in documentation

documentation/source/general/tutorial/CD.ipynb

@@ -84,7 +84,7 @@
     "\n",
     "A QUBO probelem is a combinatorical optimization problem that can be formulated as\n",
     "\n",
-    "$$ \\mathrm{min} \\ y = x^T Q x, $$\n",
+    "$$ \\min_x\\left(x^T Q x\\right), $$\n",
     "\n",
     "where $Q$ is a symmetric matrix and $x$ are binary vectors $x_i \\in \\{0, 1\\}$.\n",
     "\n",
@@ -370,7 +370,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "ca0fce92",
    "metadata": {},
    "outputs": [
@@ -384,6 +384,7 @@
    ],
    "source": [
     "from qrisp.algorithms.cold import solve_QUBO\n",
+    "import numpy as np\n",
     "\n",
     "Q = np.array([[-1.1, 0.6, 0.4, 0.0, 0.0, 0.0],\n",
     "              [0.6, -0.9,  0.5, 0.0, 0.0, 0.0],\n",
@@ -464,7 +465,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "qrisp_08",
+   "display_name": ".venv (3.11.16.final.0)",
    "language": "python",
    "name": "python3"
   },
@@ -478,7 +479,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.11"
+   "version": "3.11.16"
   }
  },
  "nbformat": 4,

documentation/source/general/tutorial/tutorial.ipynb

@@ -515,7 +515,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "0791ce5a",
    "metadata": {},
    "outputs": [
@@ -529,7 +529,7 @@
    ],
    "source": [
     "from math import pi\n",
-    "from qrisp.grover import diffuser\n",
+    "from qrisp.algorithms.grover import diffuser\n",
     "\n",
     "qf = QuantumFloat(3, -1, signed=True)\n",
     "\n",

src/qrisp/algorithms/cold/dcqo_problem.py

@@ -610,7 +610,7 @@ def run(  # noqa: PLR0913, PLR0917 -- public, keyword-callable API shape
         CRAB=False,
         optimizer="COBYQA",
         objective="agp_coeff_magnitude",
-        bounds=(),
+        bounds=(-2, 2),
         options={},
         mes_kwargs={},
         precision=0.01,
@@ -632,9 +632,9 @@ def run(  # noqa: PLR0913, PLR0917 -- public, keyword-callable API shape
             Evolution time for the simulation.
         method : str
             Method to solve the QUBO with. Either ``LCD`` or ``COLD``.
-        N_opt : int
+        N_opt : int, optional
             Number of optimization parameters in ``H_control``.
-        CRAB : bool
+        CRAB : bool, optional
             If ``True``, the CRAB optimization method is being used. The default is ``False``.
         optimizer : str, optional
             Specifies the `SciPy optimization routine
@@ -647,8 +647,8 @@ def run(  # noqa: PLR0913, PLR0917 -- public, keyword-callable API shape
             ``agp_coeff_magnitude``.
         bounds : tuple
             The parameter bounds for the optimizer. Default is (-2, 2).
-        options : dict
-            Additional options for the Scipy solver.
+        options : dict, optional
+            A dictionary of additional options for the Scipy solver.
         mes_kwargs : dict, optional
             The keyword arguments for the measurement function. Default is an empty dictionary.
         precision : float, optional

src/qrisp/core/quantum_session.py

@@ -537,7 +537,7 @@ def clear_data(self):
         self.data.clear()
 
     def statevector(self, return_type="sympy", plot=False, decimals=None):
-        r"""Returns a representation of the statevector. Three options are available:
+        r"""Returns a representation of the statevector. Four options are available:
 
         * ``sympy`` returns a `Sympy quantum state
           <https://docs.sympy.org/latest/modules/physics/quantum/state.html>`_,
@@ -551,15 +551,16 @@ def statevector(self, return_type="sympy", plot=False, decimals=None):
           investigated by calling this function on a dictionary of this QuantumSession's
           QuantumVariables.
 
-        If you need to retrieve the statevector as a numpy array, please use the
-        corresponding
+        * ``array`` returns an array, just like the corresponding
         :meth:`QuantumCircuit method <qrisp.QuantumCircuit.statevector_array>`.
+        If you don't need the options ``plot`` and ``decimals`` then please use
+        that function instead.
 
         Parameters
         ----------
         return_type : str, optional
             String indicating how the statevector should be returned. Available are
-            ``sympy``, ``array`` and ``function``. The default is ``sympy``.
+            ``sympy``, ``latex``, ``function`` and ``array``. The default is ``sympy``.
         plot : bool, optional
             If the return type is set to ``array``, this boolean will trigger a plot of
             the statevector. The default is ``False``.

src/qrisp/environments/quantum_conditionals.py

@@ -152,7 +152,7 @@ def quantum_eq(qv_0, qv_1):
     state $\ket{0}$. After this, we apply regular X gates onto ``temp_qv`` such that
     the qubits where the inputs agree, are in state $\ket{1}$. Finally,
     we apply a multi-controlled X gate onto the result to flip the result, if
-    all of qubits of the qubits in ``temp_qv`` are in the $\ket{0}$ state.
+    all of qubits of the qubits in ``temp_qv`` are in the $\ket{1}$ state.
 
     We inspect the resulting QuantumCircuit