This week's assignments will guide you through the following topics:
- Computing workflow of CMS
- Issues related to real data
Please read the following:
- Read about the CMS event data model (EDM): https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookCMSSWFramework
- Learn about the CMS software stack (CMSSW): https://cms-sw.github.io/index.html
- Browse an example pull request to CMSSW: cms-sw/cmssw#30072
- Skim some papers on the framework and multithreading: https://indico.cern.ch/event/408139/contributions/979800/attachments/815724/1117731/FrameworkPaper.pdf, {cite:p}
Jones:2014uza
Propose a project for Quarter 2. Possible extensions include:
- Explore other model architectures for the same H(bb) identification task, like transformers, tensor networks, equivariant neural networks.
- Expand the model to do multiclass classification (classifying all flavors of QCD quarks, gluons, H(bb) present in the dataset).
- Try an unsupervised learning approach like (variational) autoencoders for anomaly detection.
- Explore model compression, knowledge distillation, quantization or other techniques to reduce the model size or complexity; Can it be made more efficient?
- Perform a regression task, like correcting the energy or mass of the particle jet based on generator-level "truth" information.
- Apply concepts you learned to a new dataset like the TrackML Particle Tracking Challenge: https://www.kaggle.com/c/trackml-particle-identification/overview.
- Apply your algorithm to real data.
- Apply concepts you learned to a slightly different jet tagging problem for VBS production of 2H(bb) 2H(WW), which may be used in a real CMS analysis!
- Explainable AI for GNNs using layerwise relevance propagation (LRP) or GNNExplainer {cite:p}
gnnexplainer.
Answer the following questions
- What are some differences between the CMS event data model and other processing frameworks