Cosmology

The Open Journal of Astrophysics Unified Astronomy Thesaurus | Astronomy Glossary | Glossary of Astronomical and Cosmological Terms, Ned Wright | Glossary of Astronomy, wikipedia |

Planck 2013 results. XVI. Cosmological parameters | Nice wp article on measuring SNe distances |

Discovery of the hot Big Bang: What Happened in 1948 Past, Present and Future of Cosmic Microwave Background Observations: Implications for Cosmology

Astro2020 Science White Paper: A proposal to exploit galaxy-21cm synergies to shed light on the Epoch of Reionization https://arxiv.org/abs/1903.03628

3 cosmology lectures by Celine Boehm at Sept. 2017 European School of High Energy Physics (slides) https://t.co/bbl9reJMU3 https://t.co/dtn0oy08gi https://t.co/XcEIqpkksQ All ESHEP 2017 lectures: https://t.co/dHsZMwuOn5

Sound Waves from the Beginning of Time, PBS SpaceTime video on Baryon Acoustic Oscillation (BAO) Secrets of the Cosmic Microwave Background, PBS SpaceTime video | reddit post |

The Distance Scale of the Universe; excellent! [astro-ph/0310571] A Map of the Universe This explains the “future visability limit”, which is also refered to in this Ethan Siegel article

[1812.06841] Inflation in Loop Quantum Cosmology, Ed Copeland et al

Megamaser Cosmology Project

Las Cumbres Observatory: Measuring the Age of the Universe | Magnitudes and Distance Measurement | Star in a Box: interactive app on lifecycle of stars |

Latest cosmology results page

Amplitude of Matter Fluctuations, σ8. The σ8 parameter is a measure of matter clumping in the LCDM model The amplitude of the primordial matter power spectrum is parameterized by σ8. This provides an important constraint on clustering of matter (CDM dominated) and the formation of structure.
Determining the cosmological parameters Ωm and σ8 from peculiar velocity and density-contrast data Another, albeit somewhat weaker, tension (compared to H0) exists between the values of the amplitude of galaxy clustering S8 σ8 and the matter fraction Ωm (S₈ − Ωm tension) in the Planck best fit model and those inferred from the latest surveys of large scale structure. [2004.09487] Adam Riess interview with Sean Carroll: this is not a quest to measure a number, this is a quest to do an end-to-end test of the universe and understand why it’s failing or we’re failing...there is this problem with the lumpiness of the universe as well...there’s another parameter, which often goes by the catchy name of Sigma 8 and it measures the clumpiness of matter. And so likewise in the early universe, because we know the state of the universe shortly after the Big Bang, and then we know how it dilutes due to expansion, we should be able to predict how clumpy it should be today. And then we have techniques which are also hard but are powerful in measuring how clumpy is, either by measuring this phenomenon called loop lensing, where we measure how clumps of matter distort the shapes, the apparent shapes of galaxies, or by measuring the motions of galaxies, extra motions due to not the expansion of space but matter, the clumpiness of matter, and those two at this point disagree with each other at… I guess the most recent number that I’ve seen is sort of 3 sigma from each of those, the lensing method and the peculiar velocity method. And in the same direction, that the late universe measurements are in a different direction in terms of size to the sigma 8 number as multiple early universe measurement.

IPython notebook tutorials covering NumPy, Matplotlib, SciPy. etc. and overview of the Python language itself. Matplotlib plotting | Precision data plotting in Python with Matplotlib | Do you often find a figure you made and have no idea what script you used to generate it? I just discovered the metadata keyword in matplotlib (plt.savefig). You can pass a dictionary including the “Creator” and the name of the script! [tweet]

ICRAR cosmology calculator | iCosmos | Ned Wright cosmology calculator |

Computing the Expansion History of the Universe, pdf |

CosmoloPy | nbinderkit |

Colossus html exported from ipynb notebooks | Colossus cosmology python astrophysics toolkit | Overview docs | LSS and DM Halo modules | Diemer 1712.04512 paper | -The easiest way to learn how to use Colossus is by following the tutorial notebooks. -You can learn more about Jupyter notebooks on the Jupyter website. * Cosmology <static/tutorialcosmology.html> * LSS: peaks in Gaussian random fields <static/tutoriallss_peaks.html> -The editable notebooks are located in the colossus/tutorials directory, the links below point to their html output: https://bitbucket.org/bdiemer/colossus/commits/f73536addcb083173bbbe3adb9021da45cac1bbe https://pypi.org/project/colossus/ from the WinPython command interpreter: pip install colossus

>python 
>>>from colossus.tests run import run_tests
Ran 87 tests in 17.344s

Astropy | Astrophysics source code library | astropy tutorials, Jupyter notebooks on github |

Cosmology Collaboration Wikis: https://cmb-s4.org/wiki/index.php/UChicago-2020:_Cosmology_with_CMB-S4 (MediaWiki) Planck Legacy Archive: https://wiki.cosmos.esa.int/planck-legacy-archive/index.php/Planck_Collaboration https://wiki.cosmos.esa.int/planck-legacy-archive/index.php/Main_Page (MediaWiki) NRAO: https://safe.nrao.edu/wiki/bin/view/Main/WebHome (public wiki, separate staff wiki) MCP: https://safe.nrao.edu/wiki/bin/view/Main/MegamaserCosmologyProject TASI: https://sites.google.com/a/colorado.edu/tasi-2018-wiki/home

Hashtags: #cosmology #physics