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| author | Shivesh Mandalia <shivesh.mandalia@outlook.com> | 2020-03-02 03:16:16 +0000 |
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| committer | Shivesh Mandalia <shivesh.mandalia@outlook.com> | 2020-03-02 03:16:16 +0000 |
| commit | 28557d293cf2b5ec7f17c5d3b684204b9ef4c1f8 (patch) | |
| tree | 687cd4fdaf7c9b43a5a9532d7d987aabbcba21e7 /README.md | |
| parent | c244f9e7d6161af0e3cc48c9f83a8312aa65001a (diff) | |
| download | GolemFlavor-28557d293cf2b5ec7f17c5d3b684204b9ef4c1f8.tar.gz GolemFlavor-28557d293cf2b5ec7f17c5d3b684204b9ef4c1f8.zip | |
minor README edit
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| -rw-r--r-- | README.md | 8 |
1 files changed, 4 insertions, 4 deletions
@@ -18,9 +18,9 @@ This is data of the *flavor* of a neutrino observatory](https://icecube.wisc.edu/), which is a cubic kilometer array of optical sensors embedded in the glacial ice at the South Pole. In particular, *astrophysical* neutrinos are ones that are very-high-energy and -come from astrophysical origins such as [black -holes](https://doi.org/10.1126/science.aat2890). -<!-- For more on the physics behind neutrinos see TODO. --> +come from astrophysical origins such as [active galactic +nuclei](https://doi.org/10.1126/science.aat2890). +<!-- For more on the physics behind neutrinos see [here](https://shivesh.org/research/). --> ### What does the GolemFlavor package do? This package provides utilities for astrophysical neutrino propagation and @@ -29,7 +29,7 @@ Bayesian statistical modeling focused on advanced Markov Chain Monte Carlo in the Astrophysical Flavor, as motivated by the paper [*New Physics in Astrophysical Neutrino Flavor*](https://doi.org/10.1103/PhysRevLett.115.161303). -<!-- For more information on the statistical modeling see TODO. --> +<!-- For more information on the statistical modeling see [here](https://shivesh.org/research/#bayesian-inference). --> ## Features * **Portable Flavor Functions**: A set of useful functions for calculating |