Comments (3)
Very good point - but unfortunately very hard to do within s4cmb without sacrificing its efficiency (atmosphere simulations are very costly!). I opened a project, but we might need the help of TOAST here indeed. Happy to discuss this!
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TODO:
- step0: Implement simple correlated noise model. step1: calibration using TOAST simulations.
- step2: Try to import TOAST within s4cmb, and scan atmosphere realisations to generate TOD.
- step4: ??
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step 0 done. See here for a demonstration!
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Related Issues (20)
- Observed Pixels HOT 1
- Index error in detector_pointing.py HOT 3
- Link s4cmb Apps to a power-spectrum estimator HOT 1
- Implement deprojection of spurious signals HOT 1
- Assertion Error in tod.py HOT 5
- no origin/dichroic branch HOT 5
- Tests fail with numpy version. 1.14 HOT 1
- Pixels outside obspix with deep_patch HOT 4
- Doctests are failing because dependencies got updated (severly) HOT 2
- Add perturbed polarization angle option in second channel for dichroic sims.
- Move the CI to GitHub Actions
- Fix compilation issue with pyslalib HOT 1
- Boresight pointing is bugged
- Add a linter
- Run continuous integration on pull requests
- JOSS paper HOT 4
- Badge for JOSS
- Main figure not visible with GitHub Dark mode HOT 2
- Test failure in recent numpy / python 3.9 versions HOT 1
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