pysm
22 posts
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GNILC dust templates: impact of the zero-level offset fix
The PySM 3 GNILC dust templates were regenerated after fixing the NumPy indexing bug of issue #281 that left the zero-level offset in the intensity input. This notebook compares the released 2023 templates with the regenerated ones: intensity zero level, polarization fraction, TT/EE/BB spectra, and the mean intensity check of issue #226. A dedicated section answers why the polarization fraction distribution differs from fig. 5 of Planck 2018 XII: the fix places the templates at the low-offset convention of that figure, and the residual is sky region and resolution.
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GNILC dust zero-level offset with the Lenz et al. 2017 low-velocity HI map
The original zero-level measurement used the full HI4PI column density, which includes high-velocity clouds that carry no dust. Redoing it with the Lenz et al. 2017 low-velocity map proposed in the feedback on PySM issue #281 shifts the intercept by only +0.001 MJy/sr: the offset is confirmed at about 0.126 MJy/sr. Includes the residual map requested in the discussion: the low-valued bump is a southern, high-column population that does not track the >90 km/s gas, with hemispheres differing in FIR per unit column but agreeing on the intercept.
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Measuring the zero-level offset of the GNILC dust intensity map with HI4PI
The CIB monopole was never subtracted from the GNILC dust input of the PySM d9/d10/d11 templates because of a NumPy indexing bug; this notebook measures the real zero-level offset of that map from the HI4PI HI correlation.
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PySM: produce CAR output at the smoothing stage
PySM 3 only builds HEALPix skies. Here is how to produce CAR pixelization output at the smoothing stage with a single spherical harmonic transform, and a validation against the smooth-then-reproject route.
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PySM 3.4.6 released: FLAMINGO kSZ models and c1 documentation
A practical introduction to the new FLAMINGO kinetic SZ presets and documented c1 cosmology in PySM 3.4.6.
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PySM 3.4.5: HalfDome TSZ model, scipy pin removed, Python 3.9 dropped
PySM 3.4.5 is now available on PyPI and GitHub. Changes in this release:
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PySM 3.4.4 released with new SZ models and NumPy 2 support
PySM 3.4.4 is now available both on PyPI and on conda-forge. This release is mostly about extending the Sunyaev-Zeldovich model suite and making sure PySM works cleanly with NumPy 2.
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PySM 3.4.3 Released
PySM version 3.4.3 is now live. Install it from PyPI or upgrade existing environments with pip install --upgrade pysm3. Full details are available in the GitHub release notes.
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PySM methods paper published in ApJ
The Astrophysical Journal formally published our paper, Full-sky Models of Galactic Microwave Emission and Polarization at Sub-arcminute Scales for the Python Sky Model, on September 12, 2025. I wanted to capture the news here now that the issue is out, following up on my March note about the ArXiv submission.
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BK18 added to Panexp model suite and new WebSky radio source models in PySM 3.4.1
Following up on my previous post about Panexp model suite simulations, there have been several important updates: BK18 Simulation Now Available
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PySM 3.4.1 Released
PySM version 3.4.1 is now available. It can be downloaded from PyPI. The release notes detail new features and improvements.
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New simulations of the Panexp model suite for Planck and WMAP
Following up on my recent post about PySM models for Galactic emission, I have recently executed three new simulations of the Panexp model suite:
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New paper on arXiv about models of Galactic emission in the microwaves for CMB experiments
A new paper has been published on Arxiv discussing models of Galactic emission in the microwaves for Cosmic Microwave Background (CMB) experiments:
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Generate sample Cosmology data for Cheap and FAIR data portal with PySM
This notebook generates some figures of Galactic and Extra-Galactic emissions using PySM. Mostly for displaying purposes.
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2024-07-29-pysm-point-source-pixell-healpix
Testing the pixell simobjects functionality to create maps of point sources pre-smoothed with a gaussian beam. The purpose is to include this functionality in PySM to be able to generate on the fly maps of source starting from a catalog.