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README.md

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@@ -32,9 +32,9 @@ The following table associates each implementation to the examples and figures i
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| 11 | [eikonal/ex40.cpp](./examples/eikonal/ex40.cpp) | MFEM | [Eikonal](#eikonal) |
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| 12 | [monge_ampere/cg_cg_dg.py](./examples/monge_ampere/cg_cg_dg.py) | Firedrake/FEniCS | [Monge-Ampere](#monge) |
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## Installation
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# Instructions
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We encourage using following Docker containers to run the codes listed in the table above:
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We encourage using following Docker containers to run the codes listed in the table above and described below:
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- DOLFINx: [ghcr.io/methods-group/proximalgalerkin-dolfinx:main](https://github.com/METHODS-Group/ProximalGalerkin/pkgs/container/proximalgalerkin-dolfinx)
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- MFEM: [ghcr.io/methods-group/proximalgalerkin-mfem:main](https://github.com/METHODS-Group/ProximalGalerkin/pkgs/container/proximalgalerkin-mfem)
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<a name="obstacle"></a>
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# Example 1(Figure 2): The Obstacle Problem
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## Example 1 (Figure 2): The Obstacle Problem
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Figures 2 (a) and (b) are generated with `DOLFINx`.
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<a name="signorini"></a>
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# Example 2(Figure 3): The Signorini Problem
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## Example 2 (Figure 3): The Signorini Problem
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Deploy the `DOLFINx` Docker container to reproduce the results in this example.
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Then call
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<a name="fracture"></a>
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# Example 3(Figure 4): Variational Fracture
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## Example 3 (Figure 4): Variational Fracture
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This example can be run from within `examples/fracture` using both the `DOLFINx` and the `Firedrake` Docker containers.
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The `DOLFINx` code can be executed with
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<a name="ch"></a>
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# Example 4(Figure 5): Four-Phase Cahn–Hilliard Gradient Flow
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## Example 4 (Figure 5): Four-Phase Cahn–Hilliard Gradient Flow
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To reproduce the results in this example, first deploy the `DOLFINx` Docker container.
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Then run
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<a name="qvi"></a>
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# Example 5(Figure 6): Thermoforming Quasi-Variational Inequality
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## Example 5 (Figure 6): Thermoforming Quasi-Variational Inequality
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Reproducing the results in this example requires the `julia:1.10.8` Docker container.
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Once this container is deployed, the code can be executed by running
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<a name="gradient"></a>
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# Example 6(Figure 7): Gradient Norm Constraints.
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## Example 6 (Figure 7): Gradient Norm Constraints.
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Deploy the `DOLFINx` Docker container to reproduce the results in this example.
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Then run `script.py` within `examples/gradient_constraint` with the following input parameters:
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<a name="harmonic"></a>
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# Example 7(Figure 8): Eigenvalue Constraints
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## Example 7 (Figure 8): Eigenvalue Constraints
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Deploy the `Firedrake` Docker container to reproduce the results in this example.
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Then run the following command within `examples/[TODO]`:
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> [!WARNING]
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> Add instructions
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# Example 8(Figure 9): Intersections of Constraints
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## Example 8 (Figure 9): Intersections of Constraints
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Deploy the `Firedrake` Docker container to reproduce the results in this example.
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Then run the following command within `examples/[TODO]`:
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> [!WARNING]
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> Add instructions
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# Example 9(Figure 10): Harmonic Maps to the Sphere
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## Example 9 (Figure 10): Harmonic Maps to the Sphere
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Deploy the `DOLFINx` Docker container to reproduce the results in this example.
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Then run the following command within `examples/harmonic_maps`:
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python3 harmonic_1D.py
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```
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# Example 10: Linear Equality Constraints
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## Example 10: Linear Equality Constraints
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Note that there is no numerical example for this setting because the derived variational formulation is equivalent to the standard Lagrange multiplier formulation for this class of problems.
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# Example 11(Figure 11): The Eikonal Equation
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## Example 11 (Figure 11): The Eikonal Equation
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We have provided code for this example for both the `MFEM` and `DOLFINx` Docker containers.
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<a name="monge"></a>
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# Example 12(Figure 12): The Monge–Ampere Equation
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## Example 12 (Figure 12): The Monge–Ampere Equation
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This example can be run from within `examples/monge_ampere` using both the `DOLFINx` and the `Firedrake` Docker containers.
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