By HEP application¶
These sections are organized by the physics problem being solved, within the scope of the Guide: particle physics, not nuclear or heavy-ion physics, astroparticle physics, cosmology, or accelerator applications. If you have a methodology in mind rather than an application, browse by ML method instead.
Sections¶
- Triggering — real-time event selection, hardware-aware ML, low-latency inference
- Reconstruction — tracking, calorimetry, particle flow, jet tagging
- Simulation & fast emulation — the whole simulation chain: amplitudes, phase-space sampling, event generation, and detector response
- Unfolding & simulation-based inference — detector unfolding, parameter estimation, limit setting from simulators without a tractable likelihood
- Anomaly detection — model-agnostic searches for new physics
- Phenomenology — parton distributions, global fits, BSM scans, reinterpretation, symbolic methods
- Formal theory — ML for formal theoretical problems, like for example string theory
- Lattice QCD — ML for lattice configurations, observables, and flow-based sampling
Some sections may be empty for now
The Guide is community-written. A section appears here once a contributor has written it. If a section you care about is missing or only a stub, please consider contributing.