Remove dead links

Author: JDBetteridge

demos/eigenvalues_QG_basinmodes/qgbasinmodes.py.rst

@@ -18,9 +18,6 @@ dissipative forces. Unlike the other demo that integrated the equations forward
 in time, in this problem it is necessary to compute the eigenvalues and
 eigenfunctions for a particular differential operator.
 
-This demo requires SLEPc and slepc4py to be installed. For instructions on how
-to install them please follow `these instructions <https://www.firedrakeproject.org/install#slepc>`_.
-
 
 Governing PDE
 ~~~~~~~~~~~~~
@@ -138,7 +135,7 @@ We define the Test Function :math:`\phi` and the Trial Function
 To build the weak formulation of our equation we need to build two PETSc
 matrices in the form of a generalized eigenvalue problem,
 :math:`A\psi = \lambda M\psi`. This eigenproblem takes `restrict=True` to help
-users to avoid convergence failures by removing eigenvalues on the 
+users to avoid convergence failures by removing eigenvalues on the
 boundary, while preserving the original function space for the eigenmodes. ::
 
   eigenproblem = LinearEigenproblem(

docs/source/aims_25.rst

@@ -50,7 +50,7 @@ reading is available on the links above.
     - Firedrake practical 2: `Dirichlet boundary conditions <https://colab.research.google.com/github/firedrakeproject/notebooks/blob/aims/02-poisson.ipynb>`__
     - Firedrake practical 4: `mixed Poisson <https://colab.research.google.com/github/firedrakeproject/notebooks/blob/aims/05-mixed-poisson.ipynb>`__
     - Firedrake practical 6: `solvers <https://colab.research.google.com/github/firedrakeproject/notebooks/blob/aims/08-composable-solvers.ipynb>`__
-    - Adjoint practical 1: `Burgers again <https://colab.research.google.com/github/firedrakeproject/notebooks/blob/aims/13_adjoint_calculations.ipynb#scrollTo=e7b5808f-f0ae-4e40-bcca-eff67f251fc9>`__
+    - Adjoint practical 1: `Burgers again <https://colab.research.google.com/github/firedrakeproject/notebooks/blob/aims/13_adjoint_calculations.ipynb>`__
     - `Scientific machine learning <https://github.com/NBoulle/physics-driven-ml/raw/main/tutorials/sciml_intro.pdf>`__, `practical <https://colab.research.google.com/github/NBoulle/physics-driven-ml/blob/main/tutorials/Tutorial_2_ex.ipynb>`__