Les Houches
2023 Session
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- Use of wiki pages and slack. Wifi access/set-up.
- Important info about bus, lodging, facilities.
- Bulletins.
Wikis of Previous sessions
Les Houches Themes
(Lyrics and Music)
(Lyrics and Music)
This is an old revision of the document!
Please add your name to the projects you are interested in contributing to:
If you are interested in a session on learning to install and run Contur please sign up here and we will schedule something early in the week.
All welcome to contribute: https://www.overleaf.com/read/jzsrmbqffwtb
….this should actually become a short review of what material is provided by different experimental groups , how it is used in recasting, how it improves things, additional aspects to consider, etc…..cover searches as well as measurements……
Extra angles to include: use of event sharing from/between experiments and pheno? Analysis combinations by experiments on elementary nuisances: provide multi-analysis SL covariance.
=== Library of regression and classification networks Keras/Tensorflow and Scikit-learn to start Library of Training data, maybe connected to hep-data (database)
Train regression on the following: - electroweak cross-section in pMSSM19 (DeepXs, …) - cross sections Wprime, Zprime (how many dimensions?) - Doublet Higgs model (6 dim)
Train likelihoods: - global fits Gambit Xenoda data (train on likehoods on different observables, e.g. only colliderbit) - Higgs model with many nuisance parameters (100?)
Train on observables: - example relic density
Train on reconstruction efficiencies: - LLSps
(want to share code for the networks…)
Output: - git repositories for networks - Xenodo data - talk with hepdata - paper - prototype code for the network library
Other info: - How to sample ? Depends on goal, proposed active learning etc.