Add nu_star (collisionality) to post-processed outputs#2103
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AndrewTKent wants to merge 1 commit intogoogle-deepmind:mainfrom
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Add nu_star (collisionality) to post-processed outputs#2103AndrewTKent wants to merge 1 commit intogoogle-deepmind:mainfrom
AndrewTKent wants to merge 1 commit intogoogle-deepmind:mainfrom
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Exposes the electron-ion collisionality (nu_star) already computed by collisions.calc_nu_star() as a post-processed output on the face grid. Uses collisionality_multiplier=1.0 for the physical value (the non-unity multiplier in QLKNN is a model-specific calibration factor, not physics). Useful for particle transport predictions and analysis. Closes google-deepmind#2094
Nush395
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Apr 14, 2026
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Thanks for the contribution! Can you also regenerate the references? This should be straightforward to do following https://torax.readthedocs.io/en/v1.3.0/contribution_tips.html#regenerating-unit-test-references
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Summary
nu_star) as a post-processed output on the face gridcollisions.calc_nu_star()withcollisionality_multiplier=1.0(physical value, not the QLKNN model-specific calibration factor)torax/_src/output_tools/post_processing.py(import, dataclass field + docstring,zeros(),make_post_processed_outputs())Closes #2094
Notes for reviewers
PostProcessedOutputsmeans the.ncreference files need regeneration (same pattern as theP_LH_delabieaddition in 83197e3).test_full_output_matches_referenceandtest_simulation_with_restartwill fail until then.collisionality_multiplier=1.0: The QLKNN multiplier is a model-calibration factor (e.g., 0.25 for qlknn_10d to compensate for a legacy collision operator mismatch). The output exposes the true physical collisionality — comment in code explains this choice.Test plan
.ncreference filespytest torax/_src/output_tools/tests/post_processing_test.pypytest torax/_src/output_tools/tests/output_test.pypytest torax/tests/sim_test.py