Qiskit / qiskit / 10774677144

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github

Committed by web-flow

Commit Message

Fully port Split2QUnitaries to rust (#13025)

* Fully port Split2QUnitaries to rust

This commit builds off of #13013 and the other data model in Rust
infrastructure and migrates the InverseCancellation pass to
operate fully in Rust. The full path of the transpiler pass now never
leaves Rust until it has finished modifying the DAGCircuit. There is
still some python interaction necessary to handle parts of the data
model that are still in Python, mainly for creating `UnitaryGate`
instances and `ParameterExpression` for global phase. But otherwise
the entirety of the pass operates in rust now.

This is just a first pass at the migration here, it moves the pass to
use loops in rust. The next steps here are to look at operating
the pass in parallel. There is no data dependency between the
optimizations being done for different gates so we should be able to
increase the throughput of the pass by leveraging multithreading to
handle each gate in parallel. This commit does not attempt
this though, because of the Python dependency and also the data
structures around gates and the dag aren't really setup for
multithreading yet and there likely will need to be some work to
support that.

Part of #12208

* Update pass logic with changes from #13095

Some of the logic inside the Split2QUnitaries pass was updated in a
recently merged PR. This commit makes those changes so the rust
implementation matches the current state of the previous python version.

* Use op_nodes() instead of topological_op_nodes()

* Use Fn trait instead of FnMut for callback

We don't need the callback to be mutable currently so relax the trait to
just be `Fn` instead of `FnMut`. If we have a need for a mutable
environment callback in the future we can change this easily enough
without any issues.

* Avoid extra edge operations in replace_on_incoming_qubits

* Rename function

Run Details

98 of 106 new or added lines in 6 files covered. (92.45%)

4 existing lines in 1 file now uncovered.

73032 of 81897 relevant lines covered (89.18%)

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