Benchmarking electron-cloud simulations and pressure measurements at the LHC

TL;DR

This paper presents a benchmarking method that compares electron-cloud simulations with pressure measurements at the LHC to monitor surface conditioning and optimize machine operation strategies.

Contribution

It introduces a novel approach to infer beam-pipe surface parameters by benchmarking simulations against pressure data during LHC operations.

Findings

Successfully applied the method to LHC data

Enabled monitoring of scrubbing progress

Provided insights into electron-cloud effects

Abstract

During the beam commissioning of the Large Hadron Collider (LHC) with 150, 75, 50 and 25-ns bunch spacing, important electron-cloud effects, like pressure rise, cryogenic heat load, beam instabilities or emittance growth, were observed. A method has been developed to infer different key beam-pipe surface parameters by benchmarking simulations and pressure rise observed in the machine. This method allows us to monitor the scrubbing process (i.e. the reduction of the secondary emission yield as a function of time) in the regions where the vacuum-pressure gauges are located, in order to decide on the most appropriate strategies for machine operation. In this paper we present the methodology and first results from applying this technique to the LHC.