Use Resource Estimation Module to build call graphs for QT-PL integration

[austingmhuang]

Context:
Previously we had custom written call graphs in order to support workflows in a reasonable time frame and produce resource estimates. Now that we have the resource estimation module in Pennylane core, we can leverage that to produce the call graphs instead, rather than using the custom call graphs we had written at the inception of the integration.

Description of the Change:
Delete all the previous existing call graphs and simply get estimates from the pennylane.estimator module and convert those to Qualtran-understandable values.

Benefits:
Makes sure that any ToBloq'd pennylane operator/circuit's call graph is equivalent to the qre.estimate of the same pennylane operator/circuit.

Possible Drawbacks:
There might be some differences between the results arising from the original custom written call graphs and that from the pennylane.estimator module

Related GitHub Issues:
[sc-100485]

[github-actions]

Hello. You may have forgotten to update the changelog!
Please edit doc/releases/changelog-dev.md with:

• A one-to-two sentence description of the change. You may include a small working example for new features.
• A link back to this PR.
• Your name (or GitHub username) in the contributors section.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 99.42%. Comparing base (d38fa4e) to head (60a8f5c).
⚠️ Report is 33 commits behind head on master.

Additional details and impacted files

@@           Coverage Diff           @@
##           master    #8390   +/-   ##
=======================================
  Coverage   99.42%   99.42%           
=======================================
  Files         587      587           
  Lines       62168    62235   +67     
=======================================
+ Hits        61812    61879   +67     
  Misses        356      356           

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[obliviateandsurrender]

Thanks @austingmhuang! Leaving some initial comments.

[soranjh]

Suggested change

	computed using the `pennylane.estimator` module, which may lead to different results.
	computed using the `pennylane.estimator` module.

[soranjh]

Instead, you might provide a reason on why this is a good change.

[DSGuala]

Suggestion: it enables scaling up to larger circuits. For example this now takes 5 seconds. It used to take 5 minutes.

import pennylane as qml
import numpy as np

shape = qml.StronglyEntanglingLayers.shape(n_layers=200, n_wires=400)
rng = np.random.default_rng(12345)
weights = rng.random(size=shape)

op = qml.StronglyEntanglingLayers(weights=weights, wires=range(400))
bloq = qml.io.ToBloq(op)

bloq.call_graph()

[Jaybsoni]

Changes look good to me. Are there any integration tests that show how this feature works in the general context 👍🏼.

[DSGuala]

Approved from my side as soon as the changelog is updated and tests pass 👍

[Jaybsoni]

Looks good to me, happy to approve once we add an integration test for how this feature would work more generally. Also do we have a PR open for the wire mapping bug?

[austingmhuang]

Looks good to me, happy to approve once we add an integration test for how this feature would work more generally. Also do we have a PR open for the wire mapping bug?

Implement the integration test and fixed the wire mapping bug here and made the appropriate changes to the test cases.

[austingmhuang]

Approved from my side as soon as the changelog is updated and tests pass 👍

I will update the changelog.

[Jaybsoni]

Looks good to me,