feat: option to disable legend #20
Open
Conversation
This file contains 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
|
|
BryceFuller
pushed a commit
to BryceFuller/qiskit-addon-obp
that referenced
this pull request
Oct 2, 2024
* refactor: replace max_gates with max_layers * poc: error budgeting for observable truncation * Cache previous iteration to avoid exceeding error budget (Qiskit#20) * Cache previous iteration to avoid exceeding error budget * Update comment * Update comment * Update comment * Remove no-op * perf: partitioning implementation idea This simply adds a note for a higher performance implementation based on iteratively partitioning the array of coefficients during truncation. Originally I had thought that an implementation based on sorting followed by a `numpy.cumsum` might be better than the while loop. However, a binary search as implemented currently is likely to be faster for the array sizes that we will be dealing with here (since it does not have the initial overhead of sorting; thanks to Minh for pointing this out, too). If this does ever become a bottleneck, we could gain some performance with the suggestion of this commit. Here are some additional resources: - https://numpy.org/doc/stable/reference/generated/numpy.partition.html - https://stackoverflow.com/a/46043964/21957877 * refactor: merge all gates in a layer before back-propagating Since our observable `SparsePauliOp` is the object which will grow fast, we should avoid as many `compose` operations with it as possible. Thus, this commit refactors the back-propagating implementation to: 1. First compose all gates in a layer which intersect with our current observable. Since all gates inside any layer are disjoint, these compositions should be fairly fast since they can be combined trivially. 2. Only now perform the possibly expensive composition with our current observable. This is mathematically equivalent to back-propagating each gate one-by-one but should be more performant. * refactor: minor clean-up * refactor: rename truncate_legacy to truncate_binary_search * refactor: start from correct upper truncation bounds * refactor: updates the entire error thresholding logic * Apply suggestions from code review * Fix inputs to funcs in tests ---------
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.
Issue
#19
Description
True.tox -e style.@BryceFuller