Performance of the ALICE luminosity levelling software architecture in the Pb-Pb physics run

Luminosity leveling is performed in the ALICE experi-ment of the Large Hadron Collider (LHC) in order to limitthe event pile-up probability, and ensure a safe operation forthe detectors. It will be even more important during Run3 when 50 KHz Pb ion-Pb ion (Pb-Pb) collisions will bedelivered in IP2. On the ALICE side, it is handled by theALICE-LHC Interface project, which also ensures an onlinedata exchange between ALICE and the LHC. An automated luminosity leveling algorithm was developed for the proton-proton physics run, and was also deployed for the Pb-Pb run with some minor changes following experience gained. The algorithm is implemented in the SIMATIC WinCC SCADA environment, and determines the leveling step from measured beam parameters received from the LHC, and the luminosity recorded by ALICE. In this paper, the softwarearchitecture of the luminosity leveling software is presented,and the performance achieved during the Pb-Pb run and Vander Meer scans is discussed.peer-reviewe

Software architecture for automatic LHC collimator alignment using machine learning

The Large Hadron Collider at CERN relies on a collimation system to absorb unavoidable beam losses before they reach the superconducting magnets. The collimators are positioned close to the beam in a transverse setting hierarchy achieved by aligning each collimator with a precision of a few tens of micrometres. In previous years, collimator alignments were performed semi-automatically, requiring collimation experts to be present to oversee and control the entire process. In 2018, expert control of the alignment procedure was replaced by dedicated machine learning algorithms, and this new software was used for collimator alignments throughout the year. This paper gives an overview of the software re-design required to achieve fully automatic collimator alignments, describing in detail the software architecture and controls systems involved. Following this successful deployment, this software will be used in the future as the default alignment software for the LHC.peer-reviewe

Feasibility of hardware acceleration in the LHC orbit feedback controller

Orbit correction in accelerators typically make use of a linear model of the machine, called the Response Matrix(RM), that relates local beam deflections to position changes.The RM is used to obtain a Pseudo-Inverse (PI), which is used in a feedback configuration, where positional errors from the reference orbit as measured by Beam Position Monitors (BPMs) are used to calculate the required change in the current flowing through the Closed Orbit Dipoles (CODs).The calculation of the PIs from the RMs is a crucial part in the LHC’s Orbit Feedback Controller (OFC), however in the present implementation of the OFC this calculation is omitted as it takes too much time to calculate and thus is unsuitable in a real-time system. As a temporary solution the LHC operators pre-calculate the new PIs outside the OFC, and then manually upload them to the OFC in advance. In this paper we aim to find a solution to this computational bottleneck through hardware acceleration in order to act automatically and as quickly as possible to COD and/or BPM failures by re-calculating the PIs within the OFC. These results will eventually be used in the renovation of the OFCfor the LHC’s Run 3.peer-reviewe

An off-momentum beam loss feedback controller and graphical user interface for the LHC

During LHC operation, a campaign to validate the configuration of the LHC collimation system is conducted every few months. This is performed by means of loss maps, where specific beam losses are voluntarily generated with the resulting loss patterns compared to expectations. The LHC collimators have to protect the machine from both betatron and off-momentum losses. In order to validate the off-momentum protection, beam losses are generated by shifting the RF frequency using a low intensity beam. This is a delicate process that, in the past, often led to the beam being dumped due to excessive losses. To avoid this, a feed-back system based on the100 Hz data stream from the LHC Beam Loss system has been implemented. When given a target RF frequency, the feedback system approaches this frequency in steps while monitoring the losses until the selected loss pattern conditions are reached, so avoiding the excessive losses that lead to a beam dump. This paper will describe the LHC off-momentum beam loss feedback system and the results achieved.peer-reviewe