MAD-NG, a standalone multiplatform tool for linear and non-linear optics design and optimisation

TL;DR

MAD-NG is a versatile, multi-platform tool that integrates fast computational methods and scripting capabilities for advanced linear and nonlinear optics design and optimization, demonstrated on large-scale accelerator projects.

Contribution

The paper introduces MAD-NG, a new standalone software combining LuaJIT and GTPSA for efficient optics design and optimization, with applications to major accelerator studies.

Findings

Successfully applied to large-scale accelerator projects like HiLumi-LHC and FCC-ee.

Provides high-performance, flexible analysis and optimization features for complex optical systems.

Demonstrates effective use of fast parametric nonlinear normal forms and Lie map operators.

Abstract

The paper will provide an overview of the capabilities of the Methodical Accelerator Design Next Generation (MAD-NG) tool. MAD-NG is a standalone, all-in-one, multi-platform tool well-suited for linear and nonlinear optics design and optimization, and has already been used in large-scale studies such as HiLumi-LHC or FCC-ee. It embeds LuaJIT, an extremely fast tracing just-in-time compiler for the Lua programming language, delivering exceptional versatility and performance for the forefront of computational physics. The core of MAD-NG relies on the fast Generalized Truncated Power Series Algebra (GTPSA) library, which has been specially developed to handle many parameters and high-order differential algebra, including Lie map operators. This ecosystem offers powerful features for the analysis and optimization of linear and nonlinear optics, thanks to the fast parametric nonlinear normal forms and the polyvalent matching command. A few examples and results will complete this overview of the MAD-NG application.