HB2023 - List of Keywords (framework)

Paper	Title	Other Keywords	Page
TUA2I2	Community Modeling Tools for High Brightness Beam Physics	simulation, space-charge, interface, plasma	81
	C.E. Mitchell, M. Garten, A. Huebl, R. Lehé, J. Qiang, R.T. Sandberg, J.-L. Vay LBNL, Berkeley, California, USA
	Pushing accelerator technology toward operation with higher intensity hadron beams is critical to meet the needs of future colliders, spallation neutron sources, and neutrino sources. To understand the dynamics of such beams requires a community effort with a comprehensive approach to modeling, from the source to the end of the beam lifetime. One needs efficient numerical models with high spatial resolution and particle statistics, insensitivity to numerical noise, and the ability to resolve low-density halo and particle loss. To meet these challenges, LBNL and collaborators have seeded an open ecosystem of codes, the Beam pLasma & Accelerator Simulation Toolkit (BLAST), that can be combined with each other and with machine learning frameworks to enable integrated start-to-end simulation of accelerator beamlines for accelerator design. Examples of BLAST tools include the PIC codes WarpX and ImpactX. These codes feature GPU acceleration and mesh-refinement, and have openPMD standardized data I/O and a Python interface. We describe these tools and the advantages that open community standards provide to inform the modeling and operation of future high-brightness accelerators.
	Slides TUA2I2 [13.597 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-HB2023-TUA2I2
About •	Received ※ 03 October 2023 — Revised ※ 06 October 2023 — Accepted ※ 09 October 2023 — Issued ※ 01 November 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEA3C3	Differential Algebra for Accelerator Optimization with Truncated Green’s Function	space-charge, simulation, multipole, operation	254
	C.S. Park Korea University Sejong Campus, Sejong, Republic of Korea
	Accelerator optimization is a critical problem in the design of high-performance particle accelerators. The truncated Green’s function space charge algorithm is a powerful tool for simulating the effects of space charge in accelerators. However, the truncated Green’s function algorithm can be computationally expensive, especially for large accelerators. In this work, we present a new approach to accelerator optimization using differential algebra with the truncated Green’s function space charge algorithm. Our approach uses differential algebra to symbolically represent the equations of the truncated Green’s function algorithm. This allows us to perform efficient symbolic analysis of the equations, which can be used to identify and optimize the accelerator parameters. We demonstrate the effectiveness of our approach by applying it to the optimization of a linear accelerator. We show that our approach can significantly reduce the computational cost of the truncated Green’s function algorithm, while still achieving high accuracy.
	Slides WEA3C3 [0.772 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-HB2023-WEA3C3
About •	Received ※ 28 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 14 October 2023 — Issued ※ 18 October 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THAFP09	Optimizing Beam Dynamics in LHC with Active Deep Learning	network, simulation, dynamic-aperture, hadron	422
	D. Di Croce, T. Pieloni, M. Seidel EPFL, Lausanne, Switzerland M. Giovannozzi, F.F. Van der Veken CERN, Meyrin, Switzerland E. Krymova SDSC, Lausanne, Switzerland M. Seidel PSI, Villigen PSI, Switzerland
	The Dynamic Aperture (DA) is an important concept for the study of non-linear beam dynamics in a circular accelerator. It refers to the region in phase space where a particle’s motion remains bounded over a given number of turns. Understanding the features of DA is crucial for operating circular accelerators as it provides insights on non-linear beam dynamics and the phenomena affecting beam lifetime. The standard approach to calculate the DA is computationally very intensive. In our study, we aim at determining an optimal set of parameters that affect DA, like betatron tune, chromaticity, and Landau octupole strengths, using a Deep Neural Network (DNN) model. The DNN model predicts the so-called angular DA, based on simulated LHC data. To enhance its performance, we integrated the DNN model into an innovative Active Learning (AL) framework. This framework not only enables retraining and updating of the model, but also facilitates efficient data generation through smart sampling. The results demonstrate that the use of the Active Learning (AL) framework allows faster scanning of LHC ring configuration parameters without compromising the accuracy of the DA calculations.
	Slides THAFP09 [1.028 MB]
	Poster THAFP09 [6.173 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-HB2023-THAFP09
About •	Received ※ 01 October 2023 — Revised ※ 04 October 2023 — Accepted ※ 10 October 2023 — Issued ※ 31 October 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THBP35	Analysis Tools for Numerical Simulations of Dynamic Aperture with Xsuite	simulation, collider, dynamic-aperture, hadron	551
	T. Pugnat, M. Giovannozzi, F.F. Van der Veken CERN, Meyrin, Switzerland D. Di Croce EPFL, Lausanne, Switzerland
	Recently, several efforts have been made at CERN to develop a new tracking tool, Xsuite, which is intended to be the successor to SixTrack. In this framework, analysis tools have also been prepared with the goal of providing advanced post-processing techniques for the interpretation of dynamic aperture simulations. The proposed software suite, named Xdyna, is meant to be a successor to the existing SixDesk environment. It incorporates all recent approaches developed to determine the dynamic aperture for a fixed number of turns. It also enables studying the time evolution of the dynamic aperture and the fitting of rigorous models based on the stability-time estimate provided by the Nekhoroshev theorem. These models make it possible to link the dynamic aperture to beam lifetime, and thus provide very relevant information for the actual performance of particle colliders. These tools have been applied to studies related to the luminosity upgrade of the CERN Large Hadron Collider (HL-LHC), the results of which are presented here.
	Poster THBP35 [0.514 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-HB2023-THBP35
About •	Received ※ 28 September 2023 — Revised ※ 05 October 2023 — Accepted ※ 10 October 2023 — Issued ※ 11 October 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

TUA2I2

Community Modeling Tools for High Brightness Beam Physics

simulation, space-charge, interface, plasma

81

C.E. Mitchell, M. Garten, A. Huebl, R. Lehé, J. Qiang, R.T. Sandberg, J.-L. Vay
LBNL, Berkeley, California, USA

Pushing accelerator technology toward operation with higher intensity hadron beams is critical to meet the needs of future colliders, spallation neutron sources, and neutrino sources. To understand the dynamics of such beams requires a community effort with a comprehensive approach to modeling, from the source to the end of the beam lifetime. One needs efficient numerical models with high spatial resolution and particle statistics, insensitivity to numerical noise, and the ability to resolve low-density halo and particle loss. To meet these challenges, LBNL and collaborators have seeded an open ecosystem of codes, the Beam pLasma & Accelerator Simulation Toolkit (BLAST), that can be combined with each other and with machine learning frameworks to enable integrated start-to-end simulation of accelerator beamlines for accelerator design. Examples of BLAST tools include the PIC codes WarpX and ImpactX. These codes feature GPU acceleration and mesh-refinement, and have openPMD standardized data I/O and a Python interface. We describe these tools and the advantages that open community standards provide to inform the modeling and operation of future high-brightness accelerators.

Slides TUA2I2 [13.597 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-HB2023-TUA2I2

About •

Received ※ 03 October 2023 — Revised ※ 06 October 2023 — Accepted ※ 09 October 2023 — Issued ※ 01 November 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEA3C3

Differential Algebra for Accelerator Optimization with Truncated Green’s Function

space-charge, simulation, multipole, operation

254

C.S. Park
Korea University Sejong Campus, Sejong, Republic of Korea

Accelerator optimization is a critical problem in the design of high-performance particle accelerators. The truncated Green’s function space charge algorithm is a powerful tool for simulating the effects of space charge in accelerators. However, the truncated Green’s function algorithm can be computationally expensive, especially for large accelerators. In this work, we present a new approach to accelerator optimization using differential algebra with the truncated Green’s function space charge algorithm. Our approach uses differential algebra to symbolically represent the equations of the truncated Green’s function algorithm. This allows us to perform efficient symbolic analysis of the equations, which can be used to identify and optimize the accelerator parameters. We demonstrate the effectiveness of our approach by applying it to the optimization of a linear accelerator. We show that our approach can significantly reduce the computational cost of the truncated Green’s function algorithm, while still achieving high accuracy.

Slides WEA3C3 [0.772 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-HB2023-WEA3C3

About •

Received ※ 28 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 14 October 2023 — Issued ※ 18 October 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THAFP09

Optimizing Beam Dynamics in LHC with Active Deep Learning

network, simulation, dynamic-aperture, hadron

422

D. Di Croce, T. Pieloni, M. Seidel
EPFL, Lausanne, Switzerland
M. Giovannozzi, F.F. Van der Veken
CERN, Meyrin, Switzerland
E. Krymova
SDSC, Lausanne, Switzerland
M. Seidel
PSI, Villigen PSI, Switzerland

The Dynamic Aperture (DA) is an important concept for the study of non-linear beam dynamics in a circular accelerator. It refers to the region in phase space where a particle’s motion remains bounded over a given number of turns. Understanding the features of DA is crucial for operating circular accelerators as it provides insights on non-linear beam dynamics and the phenomena affecting beam lifetime. The standard approach to calculate the DA is computationally very intensive. In our study, we aim at determining an optimal set of parameters that affect DA, like betatron tune, chromaticity, and Landau octupole strengths, using a Deep Neural Network (DNN) model. The DNN model predicts the so-called angular DA, based on simulated LHC data. To enhance its performance, we integrated the DNN model into an innovative Active Learning (AL) framework. This framework not only enables retraining and updating of the model, but also facilitates efficient data generation through smart sampling. The results demonstrate that the use of the Active Learning (AL) framework allows faster scanning of LHC ring configuration parameters without compromising the accuracy of the DA calculations.

Slides THAFP09 [1.028 MB]

Poster THAFP09 [6.173 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-HB2023-THAFP09

About •

Received ※ 01 October 2023 — Revised ※ 04 October 2023 — Accepted ※ 10 October 2023 — Issued ※ 31 October 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THBP35

Analysis Tools for Numerical Simulations of Dynamic Aperture with Xsuite

simulation, collider, dynamic-aperture, hadron

551

T. Pugnat, M. Giovannozzi, F.F. Van der Veken
CERN, Meyrin, Switzerland
D. Di Croce
EPFL, Lausanne, Switzerland

Recently, several efforts have been made at CERN to develop a new tracking tool, Xsuite, which is intended to be the successor to SixTrack. In this framework, analysis tools have also been prepared with the goal of providing advanced post-processing techniques for the interpretation of dynamic aperture simulations. The proposed software suite, named Xdyna, is meant to be a successor to the existing SixDesk environment. It incorporates all recent approaches developed to determine the dynamic aperture for a fixed number of turns. It also enables studying the time evolution of the dynamic aperture and the fitting of rigorous models based on the stability-time estimate provided by the Nekhoroshev theorem. These models make it possible to link the dynamic aperture to beam lifetime, and thus provide very relevant information for the actual performance of particle colliders. These tools have been applied to studies related to the luminosity upgrade of the CERN Large Hadron Collider (HL-LHC), the results of which are presented here.

Poster THBP35 [0.514 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-HB2023-THBP35

About •

Received ※ 28 September 2023 — Revised ※ 05 October 2023 — Accepted ※ 10 October 2023 — Issued ※ 11 October 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)