bradkav Goto Github PK
Name: Bradley J. Kavanagh
Type: User
Bio: Particle astrophysicist at IFCA. Living in Santander in Northern Spain, working as a research scientist for the Spanish National Research Council (CSIC).
Blog: bradkav.net
Name: Bradley J. Kavanagh
Type: User
Bio: Particle astrophysicist at IFCA. Living in Santander in Northern Spain, working as a research scientist for the Spanish National Research Council (CSIC).
Blog: bradkav.net
Prospects for discriminating between Majorana and Dirac Dark Matter using future direct detection data.
Light version of AntiparticleDM, without the data files
Code and results for the disruption of axion miniclusters (AMCs) in the Milky Way, as well as radio signals from encounters between AMCs and neutrons stars.
Code for studying primordial black hole (PBH) binaries, clothed in dark matter (DM) halos, associated with the paper "Black Holes' Dark Dress: On the merger rate of a subdominant population of primordial black holes".
My personal physics website, covering Dark Matter, Particle Physics, Statistics and Open Science. The site includes my publication list, CV, research interests and current projects.
Code for calculating Coherent Elastic Neutrino-Nucleus Scattering (CEvNS) cross sections and recoil spectra. Also includes code for obtaining New Physics constraints from the COHERENT-2017 results.
Some example code, illustrating how to use WIMpy (with the end-goal being to perform projections/reconstructions for future CCD Dark Matter detectors)
Curated list of Dark Matter Codes
Code for studying the cosmology and detection of the Dark Axion Portal Model
Code for initialising (and running) Gadget2 with Dark Dress IMRI systems
A place to gather resources for simulating Dark Matter around black holes.
[**Work in Progress**] Detection Codes for Dark Matter experiments. Code for calculating direct detection and neutrino telescope likelihoods. Continually updated as I develop the code and add functionality.
DiphotonFits is a collection of python code (and a couple of data files) which allows you to perform fits to the (binned, digitised) ATLAS diphoton invariant mass spectrum, from the initial Run-II results (Dec 2015). Essentially a worked example in statistics.
Repo and wiki for coming up with a set of standard inputs and outputs for dark matter direct detection codes
[**Work in Progress**] Code for reconstructing velocity distribution from directional direct detection data
[**Work in Progress**] Python code for calculating, plotting and fitting Dark Matter direct detection event rates
Tools for calculating the Radon Transform, for use in the analysis of Directional Dark Matter Direct Detection
Code for calculating event rates and likelihoods for Dark Matter direct detection experiments in the presence of Earth-Scattering
A tool for calculating the impact of Earth-scattering on the distribution of Dark Matter (DM) particles. Includes (Mathematica) code, numerical results, plots and animations.
GRAPPA Student Seminar 2018 - Overview
GRAPPA Student Seminar 2018 - Candidates (Group 2)
GRAPPA Student Seminar 2018 - Cosmology (Group 1)
GRAPPA Student Seminar 2018 - Direct Detection (Group 4)
GRAPPA Student Seminar 2018 - Indirect Detection (Group 3)
Gravitational Wave Sensitivity Curve Plotter
Code for evolving a Dark Matter minispike under the influence of a perturbing body, injecting energy through dynamical friction.
A python code able to simulate Intermediate Mass Ratio Inspirals (IMRI)
London Code Of Conduct
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.