feat: add gradient descent information to thermoelastic2d problem

[gapaza]

Description

Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.

This pull request adds gradient information to the Thermoelastic2D problem. It also modifies the OptiStep data class to include additional optional fields for gradient information. These fields include:

• x: npt.NDArray (the current design before the gradient update)
• x_update: npt.NDArray (the update step taken by the optimizer)
• obj_values_update: npt.NDArray (how the objective values changed after the update step)

Type of change

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• New feature (non-breaking change which adds functionality)

Screenshots

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Checklist:

• I have run the pre-commit checks with pre-commit run --all-files
• I have run ruff check . and ruff format
• I have run mypy .
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

Reviewer Checklist:

• The content of this PR brings value to the community. It is not too specific to a particular use case.
• The tests and checks pass (linting, formatting, type checking). For a new problem, double check the github actions workflow to ensure the problem is being tested.
• The documentation is updated.
• The code is understandable and commented. No large code blocks are left unexplained, no huge file. Can I read and understand the code easily?
• There is no merge conflict.
• The changes are not breaking the existing results (datasets, training curves, etc.). If they do, is there a good reason for it? And is the associated problem version bumped?
• For a new problem, has the dataset been generated with our slurm script so we can re-generate it if needed? (This also ensures that the problem is running on the HPC.)
• For bugfixes, it is a robust fix and not a hacky workaround.

[g-braeunlich]

Suggested change

	x: npt.NDArray | None = None # the current design before the gradient update
	x_update: npt.NDArray | None = None # the gradient update step taken by the optimizer
	obj_values_update: npt.NDArray | None = None # how the objective values change after the update step
	x: npt.NDArray | None = None
	"""the current design before the gradient update"""
	x_update: npt.NDArray | None = None
	"""the gradient update step taken by the optimizer"""
	obj_values_update: npt.NDArray | None = None
	"""how the objective values change after the update step"""

[g-braeunlich]

PLR0913 starts getting annoying.
I would say: lets remove that check.
Could you do

--- a/pyproject.toml
+++ b/pyproject.toml
@@ -132,6 +132,7 @@ ignore = [
   "EM102",    # f-string-in-exception
   "E741",     # ambiguous-variable-name
   "FIX002",   # flake8-fixme (flake8-todos is enough)
+  "PLR0913",  # too-many-arguments
   "PTH",      # flake8-use-pathlib

and remove the corresponding noqa throughout the codebase?