Vanilla strategy with complex512 (using Julia)

[rdprins]

Calculating Fock representations using the "vanilla strategy" is now more numerically stable (i.e. numerical blowups
that result from repeatedly applying the recurrence relation are now postponed to higher cutoff values).
This is done by representing Fock amplitudes with precision complex512 rather than complex128
(which counters the accumulation of floating-point errors).
We run Julia code via PyJulia (where Numba was used before) to keep the code fast.

Before submitting

Please complete the following checklist when submitting a PR:

• All new features must include a unit test.
  If you've fixed a bug or added code that should be tested, add a test to the
  test directory!

• All new functions and code must be clearly commented and documented.
  If you do make documentation changes, make sure that the docs build and
  render correctly by running make docs.

• Ensure that the test suite passes, by running make test.

• Ensure that code and tests are properly formatted, by running make format or black -l 100 <filename> on any relevant files. You will need to have the Black code format installed:
  pip install black.

• Add a new entry to the .github/CHANGELOG.md file, summarizing the
  change, and including a link back to the PR.

• The Mr Mustard source code conforms to
  PEP8 standards except line length.
  We check all of our code against Pylint.
  To lint modified files, simply pip install pylint, and then
  run pylint mrmustard/path/to/file.py.

When all the above are checked, delete everything above the dashed
line and fill in the pull request template.

---

Context: Vanilla strategy for calculating Fock representations

Description of the Change: code is now run in Julia via PyJulia + we represent Fock amplitudes with 512 bits of precision

Benefits: numerical stability

Possible Drawbacks: slows down code

Related GitHub Issues:

[ziofil]

oh sorry, I accidentally hit the "ready for review" button

[rdprins]

The line from julia import Main as Main_julia pops up in CodeFactor as it's run outside of toplevel (both in settings.py as in tensorflow_wrapper.py), but I think it can't be moved, because it has to be run after running jl = Julia(compiled_modules=False), which is done in settings.py.