Demo: How to use PennyLane for Resource Estimation #1592

AntonNI8 · 2025-10-31T21:45:41Z

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github-actions · 2025-10-31T21:45:49Z

👋 Hey, looks like you've updated some demos!

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demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

After the update to Sphinx, Sphinx Gallery now outputs a different format for generated code blocks, where the code block is now part of an entirely separate element and no longer nested in `rst-class` directive. This PR adds a fix to be able to handle both the new and old `sphx-glr-script-out` formats. It has been tested on #1592 .

github-actions · 2025-11-17T16:12:08Z

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Deployed at: 2025-12-16 21:06:00 UTC

josh146

Thanks @AntonNI8 @Jaybsoni, the story is very well done now! I have left mostly stylistic and minor structuring comments below, once taken into account I think the demo is good to go 🙌

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

josh146 · 2025-12-08T10:04:08Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+def circuit(hamiltonian, num_steps, order):
+    qre.UniformStatePrep(num_states=2**n_q)  # uniform superposition over all basis states
+    qre.TrotterPauli(hamiltonian, num_steps, order)


Something I think is worth emphasizing to the reader is that this circuit is not executable (e.g., you could show them what happens when they execute this function --- I assume nothing, and compare it to what happens when you execute executable_circuit).

I agree with your suggestion Josh! However the system size we have selected are already non-executable. Even the executable circuit has 1250 wires which we cannot hope to execute on simulator.

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

josh146 · 2025-12-08T10:08:56Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+######################################################################
+# Your turn!
+# ~~~~~~~~~~
+#
+# Now that you’ve seen how powerful PennyLane’s
+# quantum resource :mod:`estimator <pennylane.estimator>` is,
+# go try it out yourself!
+#
+# Use PennyLane to reason about the costs of your quantum algorithm
+# without any of the headaches.


I wonder if there is something more explicit to put here in the concluding call-to-action. As it is currently worded, it isn't really saying much that hasn't already been said earlier on in the demo.

Perhaps this is the place to mention some of the other features of the estimation module, point to specs, etc?

daniela-angulo · 2025-12-16T18:59:06Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+# without any of the headaches.
+#
+# References
+# ----------


Suggested change

# ----------

# ~~~~~~~~~~

daniela-angulo · 2025-12-16T19:00:03Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+r"""How to use PennyLane for Resource Estimation
+============================================
+
+Fault tolerant quantum computers are on their way. But how do we ensure that useful algorithms can


Suggested change

Fault tolerant quantum computers are on their way. But how do we ensure that useful algorithms can

Fault-tolerant quantum computers are on their way. However, how do we ensure that useful algorithms can

daniela-angulo · 2025-12-16T19:10:05Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+============================================
+
+Fault tolerant quantum computers are on their way. But how do we ensure that useful algorithms can
+actually run on them? An algorithm is hardly helpful when it cannot be executed; but only truly


Suggested change

actually run on them? An algorithm is hardly helpful when it cannot be executed; but only truly

actually run on them? An algorithm is hardly helpful when it cannot be executed, but only truly

josh146

thanks @Jaybsoni @AntonNI8, this is fantastic 💪

Clear, concise, and tells a compelling story.

Is the plan to merge it into dev, and have it go live for the next PL release?

josh146 · 2025-12-18T03:00:19Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+to execute on a given quantum hardware architecture, or if it will even fit in memory to begin with.
+
+PennyLane is here to make that process easy, with our new resource estimation module
+:mod:`estimator <pennylane.estimator>`. `estimator` leverages the latest resource estimates,


Suggested change

:mod:`estimator <pennylane.estimator>`. `estimator` leverages the latest resource estimates,

:mod:`estimator <pennylane.estimator>`. ``estimator`` leverages the latest resource estimates,

josh146 · 2025-12-18T03:00:36Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+quickly as possible.
+
+In this demo, we will estimate the quantum resources necessary for a simple Hamiltonian workflow:
+evolve the quantum state of a honeycomb lattice of spins under the


Suggested change

evolve the quantum state of a honeycomb lattice of spins under the

evolving the quantum state of a honeycomb lattice of spins under the

josh146 · 2025-12-18T03:02:00Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+# **Thats 20,000 spins!**
+#
+# Generating such Hamiltonians quickly becomes a bottleneck.
+# However, :mod:`estimator <pennylane.estimator>`,


Suggested change

# However, :mod:`estimator <pennylane.estimator>`,

# However, :mod:`estimator <pennylane.estimator>`

josh146 · 2025-12-18T03:02:19Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+# from the :mod:`estimator <pennylane.estimator>` module to express our circuit.
+# These
+# :class:`ResourceOperator <pennylane.estimator.resource_operator.ResourceOperator>`
+# classes, like the `PauliHamiltonian` above, are designed to require minimal information


Suggested change

# classes, like the `PauliHamiltonian` above, are designed to require minimal information

# classes, like the ``PauliHamiltonian`` above, are designed to require minimal information

josh146 · 2025-12-18T03:02:46Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+print(res)
+
+######################################################################
+# Our resource estimate was generated in the blink of an eye.


Suggested change

# Our resource estimate was generated in the blink of an eye.

# Our resource estimate was generated in the blink of an eye 👁️

optional!

josh146 · 2025-12-18T03:03:08Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+)
+
+######################################################################
+# Let’s see how the cost of ``qre.TrotterPauli`` differs in these two cases!


Suggested change

# Let’s see how the cost of ``qre.TrotterPauli`` differs in these two cases!

# Let’s see how the cost of ``qre.TrotterPauli`` differs in these two cases:

josh146 · 2025-12-18T03:05:17Z

demonstrations_v2/re_how_to_use_pennylane_for_resource_estimation/demo.py

+# References
+# ----------


Suggested change

# References

# ----------

# References

# ~~~~~~~~~~

init

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AntonNI8 and others added 7 commits November 12, 2025 16:24

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Handle new sphx-gallery format #1599

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v0.4 wrote intro

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Merge branch 'master' into re_howto

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	Fault tolerant quantum computers are on their way. But how do we ensure that useful algorithms can
	Fault-tolerant quantum computers are on their way. However, how do we ensure that useful algorithms can

	actually run on them? An algorithm is hardly helpful when it cannot be executed; but only truly
	actually run on them? An algorithm is hardly helpful when it cannot be executed, but only truly

	:mod:`estimator <pennylane.estimator>`. `estimator` leverages the latest resource estimates,
	:mod:`estimator <pennylane.estimator>`. ``estimator`` leverages the latest resource estimates,

	evolve the quantum state of a honeycomb lattice of spins under the
	evolving the quantum state of a honeycomb lattice of spins under the

	# However, :mod:`estimator <pennylane.estimator>`,
	# However, :mod:`estimator <pennylane.estimator>`

	# classes, like the `PauliHamiltonian` above, are designed to require minimal information
	# classes, like the ``PauliHamiltonian`` above, are designed to require minimal information

	# Our resource estimate was generated in the blink of an eye.
	# Our resource estimate was generated in the blink of an eye 👁️

	# Let’s see how the cost of ``qre.TrotterPauli`` differs in these two cases!
	# Let’s see how the cost of ``qre.TrotterPauli`` differs in these two cases:

Demo: How to use PennyLane for Resource Estimation #1592

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