[open-systems] Testing Measurement-Based Uncomputation notebook #1698
+419
−14
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
dstrain115
approved these changes
Aug 29, 2025
| "source": [ | ||
| "# Verifying Measurement-Based Uncomputation\n", | ||
| "\n", | ||
| "Quantum information cannot be destroyed, but during a computation we may produce intermediate values that we wish to discard. We can \"uncompute\" these values by running the computation in reverse. The ordinary uncomputation strategy requires paying the cost of the computation twice, but [*Halving the cost of quantum addition.* Gidney 2017](https://arxiv.org/abs/1709.06648) shows how measurement in the X basis can effectively discard a bit without expensive uncomputation. The consequence is that the remaining states of the system will pick up phases depending on the random measurement result. [*Verifying Measurement Based Uncomputation.* Gidney 2019](https://algassert.com/post/1903) provides more detail about these phases. It also describes a proceedure for using a phased-classical simulator to \"fuzz test\" measurement-based uncomputation circuits.\n", |
There was a problem hiding this comment.
nit: I think there should be a comma after "during a computation"
| "\n", | ||
| "and_dag = And(uncompute=True)\n", | ||
| "for q1, q2 in itertools.product(range(2), repeat=2):\n", | ||
| " trg = int(q1==1 and q2 == 1)\n", |
There was a problem hiding this comment.
what is 'trg'? I would probably use a better name.
It took me a while to realize this means "target". I would use that name here and below.
Avoid abbreviations: https://google.github.io/styleguide/pyguide.html#316-naming
| " trg = int(q1==1 and q2 == 1)\n", | ||
| " print(f'{q1=}, {q2=}, {trg=}', end=' ')\n", | ||
| " (q1o, q2o), = and_dag.call_classically(ctrl=[q1,q2], target=trg)\n", | ||
| " assert q1o == q1\n", |
There was a problem hiding this comment.
Avoid abbreviations: https://google.github.io/styleguide/pyguide.html#316-naming
I would use q1_output.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Quantum information cannot be destroyed, but during a computation we may produce intermediate values that we wish to discard. We can "uncompute" these values by running the computation in reverse. The ordinary uncomputation strategy requires paying the cost of the computation twice, but Halving the cost of quantum addition. Gidney 2017 shows how measurement in the X basis can effectively discard a bit without expensive uncomputation. The consequence is that the remaining states of the system will pick up phases depending on the random measurement result. Verifying Measurement Based Uncomputation. Gidney 2019 provides more detail about these phases. It also describes a proceedure for using a phased-classical simulator to "fuzz test" measurement-based uncomputation circuits.
Here, we show how Qualtran can be used to verify measurement based uncomputation circuits following Gidney's proposal.