astrophysics
26 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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healpy 1.20.0b1 beta — harmonic_ud_grade for artifact-safe map downgrading
pip install --pre healpy==1.20.0b1 harmonicudgrade changes map NSIDE through spherical-harmonic transforms with pixel-window and beam transfer corrections following Eq. 1 of Planck 2015 X (arXiv:1502.01588).
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healpy harmonic_ud_grade vs skytools change_resolution: A Comparison
A comparison of healpy.harmonic_ud_grade and skytools.change_resolution for HEALPix map resolution changes, highlighting API differences, beam/pixel-window support, direct alm input, and agreement levels.
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harmonic_ud_grade vs ud_grade: A Focused Comparison
harmonic_ud_grade vs ud_grade A Focused Comparison.
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Why 3 pixels per beam? The mathematics of HEALPix resolution matching
Exploring why the Planck convention uses FWHM = 3 x pixel size for harmonic-space map downgrading, with equations from the literature and simulated demonstrations.
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Healpy blm_gauss breaking change analysis
Analyzing the breaking change in healpy's blm_gauss function (1.18.1 to 1.19.0) and its impact on Gaussian beam coefficients.
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Astrophysics Papers Daily Summaries Notebook with the Jetstream LLM Inference Service
Fetch today's astro-ph papers from arXiv, summarize abstracts with llm, and output a Markdown summary. This is an example of using the Jetstream Inference Service, notice that you need first to configure the llm package to access the Jetstream Inference Service via the API
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Interactive 3D plot of a Planck map with Matplotlib
This is an update of my older tutorial Unfortunately I was not able to make Mayavi properly plot the data, rerunning the same code would give a map that looked like uniform noise.
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CFITSIO file writing with checkpointing
I wrote a prototype implementation of writing FITS files in C checkpointing using the FITS flush function so that if the code segfaults, the file is not corrupted, see:
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Simple WCS with astropy modeling and gwcs
Some notes on how to convert a FITS WCS to a WCS from gwcs (Generalized WCS) to be used within the JWST pipeline python import astropy from astropy.io import fits import numpy as np from astropy import units as u
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Advanced pandas with astrophysics example notebook
Taught a lesson today on advanced python and pandas based on an example application in Astrophysics with simulations of data from the Planck Satellite), features also a Binder button to run it yourself. Jupyter Notebook available at: under CC-BY
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Accelerate groupby operation on pixels with Numba
Download the original IPython notebook Astrophysics background