pyTRAIN -- a modern TRAIN implementation

TL;DR

pyTRAIN is a modern Python re-implementation of the classic TRAIN code, enhancing usability, extensibility, and supporting advanced beam-beam interaction simulations for accelerator physics.

Contribution

It introduces a Python-based version of TRAIN with new features like support for arbitrary particle types and beam-beam interactions, improving upon the original code.

Findings

Benchmarking shows consistency with the classic TRAIN code.

Simulation results align with LHC physics observations.

Enhanced usability and extensibility demonstrated.

Abstract

The TRAIN code, developed in 1995 as a post-processor for second-order transport maps from MAD, has been used extensively at the LEP and the LHC to study self-consistent closed orbits, tunes and chromaticities of bunch trains under the presence of beam-beam long-range (BBLR) and PACMAN effects.. This paper presents a modern re-implementation of the TRAIN concept in Python using well-known numeric libraries (numpy, scipy) and an optional link to MAD-X via cpymad. This greatly improves the usability, maintainability and extensibility of the code. New functionality includes the support for arbitrary particle types, an arbitrary number and distribution of beam-beam interaction points, and the extrapolation of the beam-beam induced closed-orbit effects to arbitrary points in the machine. The code is benchmarked against the classic TRAIN code, and simulation results are compared to observations from LHC physics operation.