Enable vectorized 3D/4D kinematics operations on Awkward arrays.
npx skills add https://github.com/gordonwatts/skill-test --skill vector-awkward
Please help me install this Agent Skill. Skill: vector-awkward Source: https://github.com/gordonwatts/skill-test/tree/main/.codex/skills/vector-awkward Command: npx skills add https://github.com/gordonwatts/skill-test --skill vector-awkward
This Skill helps Python users build and operate vector-like records using Awkward arrays, removing boilerplate when working with Momentum3D/Momentum4D data.
Register vector Awkward support with vector.register_awkward() and create a Momentum4D record using ak.zip, then perform common operations such as deltaR or invariant mass.
High-intent search queries and answers about installing and using this skill.
You can compute deltaR and invariant mass by registering Awkward support with vector.register_awkward(), then building Momentum4D records via ak.zip with standard fields like pt, eta, phi, and mass to enable vectorized kinematic operations.
Vectorized kinematics operations on Awkward arrays use the vector library to register Momentum3D or Momentum4D record types, enabling direct computation of boosts, invariant masses, and deltaR across large high-energy physics datasets without Python loops.
Yes, calling vector.register_awkward() before using ak.zip to create Momentum4D records is required to activate vector-aware methods on Awkward arrays, enabling operations like deltaR, invariant mass, and boosts.
Yes, Awkward arrays support high-energy physics momentum boosts and kinematic calculations by constructing Momentum3D or Momentum4D records with standard fields like pt, eta, phi, and mass, then applying vectorized boost operations across large datasets.
Standard field names for Momentum3D or Momentum4D records in Awkward include pt, eta, phi, and mass, assembled using ak.zip with with_name set to Momentum3D or Momentum4D to enable vectorized kinematic operations.
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