Implement Feedforward modules

[masa10-f]

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Description of the change:

Added feedforward.py and focus_flow.py modules.

The former provides type aliases of feedforward mapping and some utility functions. The latter offers gflow focusing algorithm.

Related issue:

[Copilot]

Pull Request Overview

This PR introduces two new modules to support feedforward corrections and a focusing algorithm while adding a new utility function to compute odd neighbors in a graph state.

• Added odd_neighbors in graphstate.py to compute the symmetric difference of neighboring nodes.
• Implemented focus_flow.py with functions is_focused and focus_gflow to process flowlike objects.
• Added feedforward.py which provides type aliases and helper functions for feedforward correction and causality checking.

Reviewed Changes

Copilot reviewed 3 out of 7 changed files in this pull request and generated no comments.

File	Description
graphix_zx/graphstate.py	Added the odd_neighbors function to compute odd neighboring nodes.
graphix_zx/focus_flow.py	Implemented focus flow algorithm using graph state information.
graphix_zx/feedforward.py	Provided feedforward correction functions and related type aliases.

Files not reviewed (4)

• docs/source/feedforward.rst: Language not supported
• docs/source/focus_flow.rst: Language not supported
• docs/source/graphstate.rst: Language not supported
• docs/source/references.rst: Language not supported

Comments suppressed due to low confidence (3)

graphix_zx/graphstate.py:848

• [nitpick] The local variable name 'odd_neighbors' in the odd_neighbors function shadows the function name and might be unclear. Consider renaming it (e.g., 'result') or adding a clarifying comment.

        odd_neighbors ^= graphstate.neighbors(node)

graphix_zx/focus_flow.py:200

• [nitpick] The use of the symmetric difference assignment (^=) on gflow[target] may be non-intuitive. Adding a comment to explain the intended operation could improve readability.

    gflow[target] ^= gflow[minimal_in_s_k]

graphix_zx/focus_flow.py:1

• The focus flow algorithm is a key new component; ensure that comprehensive tests are added to cover both typical and edge-case scenarios.

'''Focus flow algorithm.