Support Sparse Matrix representation for Observables and Arithmetic Ops (1/3)

[Jaybsoni]

Context:
We want to support sparse matrix representation for Symbolic operators, these depend on the sparse matrix attributes of their factors/summands/base operators. We must then also support sparse matrix representations for a few other operators; we choose to support observables as these have useful applications (eg. Quantum Chemistry).

Description of the Change:
Implement the sparse_matrix() property for some well known PL observables. Add a sparse expand method to handle varying wire labels.

Benefits:
Performance boost when computing expectation values / other measurements using operator arithmetic or observables.

Closes #2882

[github-actions]

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[codecov]

Codecov Report

Merging #2964 (ab92ae2) into master (754f2c9) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master    #2964   +/-   ##
=======================================
  Coverage   99.65%   99.65%           
=======================================
  Files         266      266           
  Lines       22318    22335   +17     
=======================================
+ Hits        22241    22258   +17     
  Misses         77       77           

Impacted Files	Coverage Δ
pennylane/ops/identity.py	100.00% <100.00%> (ø)
pennylane/ops/qubit/non_parametric_ops.py	100.00% <100.00%> (ø)

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[albi3ro]

This will be a good starting point for further development and feature coverage of sparse matrices!

[Jaybsoni]

[sc-24922]