Speaker
Description
The numerical solution of the Vlasov–Fokker–Planck (VFP) equation is a well-established method to simulate the dynamics of electron bunches in storage rings, including their self-interaction through wake fields. Inovesa is an efficient VFP solver architecture that enables accurate simulations of phase space evolution, capturing phenomena such as coherent synchrotron radiation (CSR) and the micro-bunching instability on standard desktop hardware.
Building on this foundation, we introduce Inovesalib, a redesigned and extensible library version of Inovesa that exposes the core VFP solver as a modular C++ API and provides a Python wrapper for seamless integration into user workflows. Inovesalib decouples the solver core from application logic and offers a plugin architecture that allows users to implement custom algorithms without modifying the underlying solver. The redesigned structure turns Inovesa from a standalone application into a flexible simulation framework, suitable for integration into optimization pipelines, machine-learning workflows, and custom tools. We present the library architecture and demonstrate its use in both C++ and Python.
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