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2023:topics [2023/03/08 17:21] stephen.jones [Session 1] |
2023:topics [2023/06/22 16:06] (current) gregor.kasieczka [Session 2] |
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===== List of topics for 2023 ====== | ===== List of topics for 2023 ====== | ||
//(accessible to everyone, editing rights to conveners and organizers)// | //(accessible to everyone, editing rights to conveners and organizers)// | ||
+ | --------------------------- | ||
==== Session 1 ==== | ==== Session 1 ==== | ||
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* Miscellaneous | * Miscellaneous | ||
* forward physics -> FASER. Anything needed from SM point of view? | * forward physics -> FASER. Anything needed from SM point of view? | ||
+ | |||
+ | * Machine Learning | ||
+ | * Matrix Element calculation using ML | ||
+ | * Interpretable models | ||
+ | * Fast surrogate models for physics simulations | ||
+ | * Workflows and interoperability with experimental software | ||
+ | * Incorporating uncertainties in the training of ML models | ||
+ | * ML-based unfolding techniques | ||
+ | * Enforcing properties to ML models: Lorentz invariance/equivariance, permutation invariance, IRC safety | ||
+ | |||
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* starting from state-of-the-art ML-taggers, estimate how much they are correlated to the physics in the measurements of substructure we already have. Discuss good procedures to best tune MC to describe ML-taggers. Discuss good procedures to estimate uncertainties on ML-taggers, given the physics understanding of various effects (an example is scale-variations, where our constraints from data are certainly stronger than the factor 2 variations in many cases, but sometimes the opposite). | * starting from state-of-the-art ML-taggers, estimate how much they are correlated to the physics in the measurements of substructure we already have. Discuss good procedures to best tune MC to describe ML-taggers. Discuss good procedures to estimate uncertainties on ML-taggers, given the physics understanding of various effects (an example is scale-variations, where our constraints from data are certainly stronger than the factor 2 variations in many cases, but sometimes the opposite). | ||
* take stock of how well most recent generator developments have improved description of multiple new measurements of substructure. (Followup from a previous Les Houches 2015 on q/g-tagging) | * take stock of how well most recent generator developments have improved description of multiple new measurements of substructure. (Followup from a previous Les Houches 2015 on q/g-tagging) | ||
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+ | |||
+ | **__Tools, Event Generators and Machine Learning:__** | ||
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==== Session 2 ==== | ==== Session 2 ==== | ||
- | .... | + | **__Higgs:__** |
+ | * "Precision": | ||
+ | * Trilinear and quadrilinear Higgs couplings | ||
+ | * Lepton flavour violation in the Higgs sector | ||
+ | * Constraining the CP structure of the Higgs couplings | ||
+ | * Higgs and EFT | ||
+ | * Characterizing Higgs boson production and decay | ||
+ | * "Novelties": | ||
+ | * Exotic decays of the 125 GeV Higgs boson | ||
+ | * Additional Higgs bosons (low/high mass) - uncovered parameter space | ||
+ | * Naturalness | ||
+ | * Gaps in searches for traditional models (SUSY, compositness) | ||
+ | * Searches for cosmological triggers (new Higgs bosons and v-like leptons) | ||
+ | * Unexpected signatures of naturalness | ||
- | ---- | ||
- | ---- | + | **__Machine Learning and Tools:__** |
+ | * **Reinterpretation**: Tools like Rivet, Gambit, .., ML for reinterpretation, reinterpretation of model agnostic searches | ||
+ | * **EFTs**: Fits, PDF inclusion, SMEFT progress ... | ||
+ | * **Physics & ML**: Injection of physics priors into classification and generative models; interpretable ML techniques; ML for optimal sensitivity for BSM searches and optimal observables and likelihood learning, opening the black box | ||
+ | * **Anomalies**: A unified view of different anomaly detection techniques,.pushing the boundaries of anomaly detection | ||
- | ==== Session 1 (from 2021) ==== | ||
- | Here for convenience | ||
- | **__Jet substructure techniques:__** | ||
- | * Interplay of jet substructure with other groups (e.g. jet substructure for EW measurements like VBF, semileptonic VV, etc.) | + | **__Low-energy precision probes of BSM:__** |
- | * Snowmass jet substructure report (JSS at future colliders) [work + discussion] | + | * New Electric Dipole Moment searches? |
- | * What can we do with previous colliders, in light of the LHC [discussion] | + | * Parity violation in new systems? |
- | * Comparing new unfolding methods | + | * Exotic atoms/ions to test exotic forces |
- | * Accord on unbinned results (?) | + | * muonic atoms |
- | * Probing the latest MC generators (PB algorithm, PANScales, Deductor...) with jet substructure | + | * antiprotonic atoms |
- | * Finite N_C, beyond LL, ... | + | * highly charged ions |
- | + | * Rydberg states | |
- | + | ||
- | + | ||
- | **__Monte Carlo:__** | + | |
- | + | ||
- | * Non-perturbative uncertainties | + | |
- | * common hadronisation interface and variations | + | |
- | * theoretical understanding | + | |
- | * differences in tuned comparisons | + | |
- | * pheno impact for certain classes of processes (e.g. VBF/VBS) | + | |
- | * Shower accuracy studies | + | |
- | * comparing different schemes on higher orders, evaluate phenomenological impact | + | |
- | * Subleading colour and interplay with colour reconnection | + | |
- | * New sampling methods and algorithms versus machine learning techniques | + | |
- | * Accuracy of merging resummed calculation versus ME+PS paradigms | + | |
- | * Photon physics, modelling of fragmentation | + | |
- | * Heavy flavour matching | + | |
- | * review of existing measurements | + | |
- | * Connecting precision calculation, fragmentation and decays | + | |
- | * partons at 100 TeV | + | |
- | * Common LHC event bazaar | + | |
- | * Status and needs for electroweak corrections and radiation in shower algorithms | + | |
- | * Machine learning and adaptive Monte Carlo methods | + | |
- | + | ||
- | ==== Session 2 ==== | + | |