Refactor sqrt_inv_sqrt

[JoeyT1994]

This PR removes the sqrt_inv_sqrt function in apply.jl in favor of a map_itensor(f::Function, t::ITensors, args...) added in the file itensorsextensions.jl in the new internal module ITensorsExtensions (where src/ITensorsExt/utils.jl is also now moved).

map_itensor(f::Function, A::ITensor, ...) uses the SVD to take a decomposition U, S, V of A and applies f over the diagonal elements of S. This uses the sqrt_decomp function from ITensors.jl (introduced in the PR https://github.com/ITensor/ITensors.jl/pull/1197/files) which correctly handles quantum numbers. The indices of the returned ITensor match those of the input A.

The symmetric_factorize function has been removed entirely from apply.jl as we can just call factorize_svd(A::ITensor; ortho = "none") from ITensors.jl` to do the same thing (again this was introduced in PR https://github.com/ITensor/ITensors.jl/pull/1197/files).

Tests are included. @mtfishman these appear to show the square root / inverse being correctly taken by the SVD backend and I don't see any phase issues cropping up?

A few other changes in this PR:
src/tensornetworkoperators.jl and test/test_tnos.jl have been removed and archived as they will be significantly refactored down the line.

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 65.51724% with 10 lines in your changes are missing coverage. Please review.

Project coverage is 82.66%. Comparing base (ae4ad2c) to head (0dc6016).
Report is 4 commits behind head on main.

Files	Patch %	Lines
src/apply.jl	52.38%	10 Missing ⚠️

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Additional details and impacted files

@@            Coverage Diff             @@
##             main     #158      +/-   ##
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+ Coverage   81.89%   82.66%   +0.77%     
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  Files          72       72              
  Lines        3744     3635     -109     
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- Hits         3066     3005      -61     
+ Misses        678      630      -48     

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[mtfishman]

I have to say that it doesn't sit well with me to use an SVD to perform square roots and inverses of positive semi-definite Hermitian matrices, I think it is safer and more direct (not to mention faster) to use a Hermitian eigendecomposition to ensure the gauge is fixed in the correct way.

[mtfishman]

Looks good, thanks! Good to go back and start cleaning up some of this code.