| Paper | Title | Page |
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| MOPAB001 | Power Deposition in Superconducting Dispersion Suppressor Magnets Downstream of the Betatron Cleaning Insertion for HL-LHC | 37 |
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Funding: Research supported by the HL-LHC project The power deposited in dispersion suppressor magnets downstream of the Large Hadron Collider (LHC) betatron cleaning insertion is governed by off-momentum particles scattered out of the primary collimators. In order to mitigate the risk of magnet quenches during periods of short beam lifetime in future High-Luminosity (HL-LHC) operation, new dispersion suppressor (DS) collimators are considered for installation (one per beam). In this paper, we present FLUKA simulations for both protons and Pb ions at 7 TeV, predicting the power deposition in the DS magnets, including the new higher-field dipoles 11T which are needed to integrate the collimator in the cold region next to the cleaning insertion. The simulated power deposition levels for the adopted HL-LHC collimator configuration and settings are used to assess the quench margin by comparison with the present estimated quench levels. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB001 | |
| About • | paper received ※ 19 May 2021 paper accepted ※ 07 July 2021 issue date ※ 16 August 2021 | |
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| TUPAB216 | Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling | 1923 |
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Funding: This work is partially funded by the Swiss Data Science Center (SDSC), project C18-07. One key aspect of accelerator optimization is to maximize the dynamic aperture (DA) of a ring. Given the number of adjustable parameters and the compute-intensity of DA simulations, this task can benefit significantly from efficient search algorithms of the available parameter space. We propose to gradually train and improve a surrogate model of the DA from SixTrack simulations while exploring the parameter space with adaptive sampling methods. Here we report on a first model of the particle stability plots using convolutional generative adversarial networks (GAN) trained on a subset of SixTrack numerical simulations for different ring configurations of the Large Hadron Collider at CERN. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB216 | |
| About • | paper received ※ 19 May 2021 paper accepted ※ 17 June 2021 issue date ※ 22 August 2021 | |
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| WEPAB024 | Release of Crystal Routine for Multi-Turn Proton Simulations within SixTrack v5 | 2648 |
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| Crystal collimation is studied as a possible scheme to further improve the efficiency of ion collimation at the High Luminosity Large Hadron Collider (HL-LHC), as well as for possible applications in the CERN program of Physics Beyond Colliders. This concept relies on the use of bent crystals that can deflect high-energy halo particles at large angles, of the order of tens of urad. In order to reproduce key experimental results of crystal collimation tests and predict the performance of this system when applied to present and future machines, a dedicated simulation routine was developed. This routine is capable of modeling both coherent and incoherent interactions of beam particles with crystal collimators, and is fully integrated into the magnetic tracking and collimator modeling provided by the single-particle tracking code SixTrack. This paper describes the implementation of the routine in the latest version of SixTrack and its most recent improvements, in particular regarding the treatment of the crystal miscut angle. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB024 | |
| About • | paper received ※ 19 May 2021 paper accepted ※ 23 June 2021 issue date ※ 14 August 2021 | |
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| THPAB011 | Monte Carlo Driven MDI Optimization at a Muon Collider | 3769 |
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| A Muon Collider represents a very interesting possibility for a future machine to explore the energy frontier in particle physics. However, to reach the needed luminosity, beam intensities of the order of 109–1012 muons per bunch are needed. In this context, the Beam-Induced Background must be taken into account for its effects on magnets and detector. Several mitigation strategies can however be conceived. In this view, it is of crucial importance to develop a flexible tool that allows to easily reconstruct the machine geometry in a Monte Carlo code, allowing to simulate in detail the interaction of muon decay products in the machine, while being able to change the machine optics itself to find the best configuration. In this contribution, a possible approach to such a purpose is presented, based on FLUKA for the Monte Carlo simulation and on LineBuilder for the geometry reconstruction. Results based on the 1.5 TeV machine optics developed by the MAP collaboration are discussed, as well as a first approach to possible mitigation strategies. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB011 | |
| About • | paper received ※ 19 May 2021 paper accepted ※ 13 July 2021 issue date ※ 01 September 2021 | |
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