Work

Latent diffusion can map beam loss to two-dimensional phase-space projections

Year: 2025

Type: article

Abstract: Beam loss monitors (BLMs) and beam current monitors (BCMs) are ubiquitous at particle accelerators around the world. These simple devices provide noninvasive high-level beam measurements but give no insight into the detailed 6D ( x , y , z , p x , p y , p z ) beam phase-space distributions or dynamics. We show that generative conditional latent diffusion models can learn intricate patterns to solve the extreme inverse problem of mapping waveforms of tens of BLMs or BCMs along an accelerator to detailed 2D projections of a charged particle beam’s 6D phase-space density. This transformational method can be used at any particle accelerator to transform simple noninvasive devices into detailed beam phase-space diagnostics. We demonstrate this concept via multiparticle simulations of the high-intensity beam in the kilometer-long Los Alamos Neutron Science Center linear proton accelerator.

Source: Physical Review Accelerators and Beams

DOI: 10.1103/rqg9-g3dp

Authors: Alexander Scheinker, Alan Williams

Institution: Los Alamos National Laboratory

Language: English

Topic: Particle accelerators and beam dynamics

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

Funders: U.S. Department of Energy, Laboratory Directed Research and Development, Los Alamos National Laboratory

Award: G2480931584