IPAC2022 - List of Authors (Malina, L.)

Paper	Title	Page
WEPOST008	Optics Correction Strategy for Run 3 of the LHC	1687
	T.H.B. Persson, F.S. Carlier, A. Costa Ojeda, J. Dilly, V. Ferrentino, E. Fol, H. García Morales, M. Hofer, E.J. Høydalsvik, J. Keintzel, M. Le Garrec, E.H. Maclean, L. Malina, F. Soubelet, R. Tomás García, A. Wegscheider, L. van Riesen-Haupt CERN, Meyrin, Switzerland J.F. Cardona UNAL, Bogota D.C, Colombia
	After almost 4 years of shutdown the LHC is again operational in 2022. Experience from the previous Long Shutdown (LS) has shown that the local errors around the triplet magnets changed significantly and it is likely we will again see different errors in 2022. In the LHC there is an interplay between the linear and the nonlinear correction which can make the corrections difficult and time-consuming to find. In this article, we describe the measurements and corrections performed during the commissioning in 2022 in order to control both the linear and the nonlinear optics to high precision.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST008
About •	Received ※ 08 June 2022 — Revised ※ 25 June 2022 — Accepted ※ 04 July 2022 — Issue date ※ 10 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPOMS016	A Pipeline for Orchestrating Machine Learning and Controls Applications	1439
	I.V. Agapov, M. Böse, L. Malina DESY, Hamburg, Germany
	Machine learning and artificial intelligence are becoming widespread paradigms in control of complex processes. Operation of accelerator facilities is not an exception, with a number of advances having happened over the last years. In the domain of intelligent control of accelerator facilities, the research has mostly been focused on feasibility demonstration of ML-based agents, or application of ML-based agents to a well-defined problem such as parameter tuning. The main challenge on the way to a more holistic AI-based operation, in our opinion, is of engineering nature and is related to the need of significant reduction of the amount of human intervention. The areas where such intervention is still significant are: training and tuning of ML models; scheduling and orchestrating of multiple intelligent agents; data stream handling; configuration management; and software testing and verification requiring advanced simulation environment. We have developed a software framework which attempts to address all these issues. The design and implementation of this system will be presented, together with application examples for the PETRA III storage ring.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS016
About •	Received ※ 09 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 25 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPOMS035	Harpy: A Fast, Simple and Accurate Harmonic Analysis with Error Propagation	2326
	L. Malina DESY, Hamburg, Germany
	Traditionally, in the accelerator physics field, accurate harmonic analysis has been performed by iteratively interpolating the result of Fast Fourier Transform (FFT) in the frequency domain. Such an approach becomes computationally demanding when relatively small effects are being studied, which is especially evident in the typical example of harmonic analysis of turn-by-turn beam position monitor data, i.e. many correlated but noisy signals. A new harmonic analysis algorithm, called Harpy, is about an order of magnitude faster than other methods, while often being also more accurate. Harpy combines standard techniques such as zero-padded FFT and noise-cleaning based on singular value decomposition. This combination also allows estimating errors of phases and amplitudes of beam-related harmonics calculated from cleaned data.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOMS035
About •	Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 20 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Optics Correction Strategy for Run 3 of the LHC

1687

T.H.B. Persson, F.S. Carlier, A. Costa Ojeda, J. Dilly, V. Ferrentino, E. Fol, H. García Morales, M. Hofer, E.J. Høydalsvik, J. Keintzel, M. Le Garrec, E.H. Maclean, L. Malina, F. Soubelet, R. Tomás García, A. Wegscheider, L. van Riesen-Haupt
CERN, Meyrin, Switzerland
J.F. Cardona
UNAL, Bogota D.C, Colombia

After almost 4 years of shutdown the LHC is again operational in 2022. Experience from the previous Long Shutdown (LS) has shown that the local errors around the triplet magnets changed significantly and it is likely we will again see different errors in 2022. In the LHC there is an interplay between the linear and the nonlinear correction which can make the corrections difficult and time-consuming to find. In this article, we describe the measurements and corrections performed during the commissioning in 2022 in order to control both the linear and the nonlinear optics to high precision.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST008

About •

Received ※ 08 June 2022 — Revised ※ 25 June 2022 — Accepted ※ 04 July 2022 — Issue date ※ 10 July 2022

Cite •

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

TUPOMS016

A Pipeline for Orchestrating Machine Learning and Controls Applications

1439

I.V. Agapov, M. Böse, L. Malina
DESY, Hamburg, Germany

Machine learning and artificial intelligence are becoming widespread paradigms in control of complex processes. Operation of accelerator facilities is not an exception, with a number of advances having happened over the last years. In the domain of intelligent control of accelerator facilities, the research has mostly been focused on feasibility demonstration of ML-based agents, or application of ML-based agents to a well-defined problem such as parameter tuning. The main challenge on the way to a more holistic AI-based operation, in our opinion, is of engineering nature and is related to the need of significant reduction of the amount of human intervention. The areas where such intervention is still significant are: training and tuning of ML models; scheduling and orchestrating of multiple intelligent agents; data stream handling; configuration management; and software testing and verification requiring advanced simulation environment. We have developed a software framework which attempts to address all these issues. The design and implementation of this system will be presented, together with application examples for the PETRA III storage ring.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS016

About •

Received ※ 09 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 25 June 2022

Cite •

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

WEPOMS035

Harpy: A Fast, Simple and Accurate Harmonic Analysis with Error Propagation

2326

L. Malina
DESY, Hamburg, Germany

Traditionally, in the accelerator physics field, accurate harmonic analysis has been performed by iteratively interpolating the result of Fast Fourier Transform (FFT) in the frequency domain. Such an approach becomes computationally demanding when relatively small effects are being studied, which is especially evident in the typical example of harmonic analysis of turn-by-turn beam position monitor data, i.e. many correlated but noisy signals. A new harmonic analysis algorithm, called Harpy, is about an order of magnitude faster than other methods, while often being also more accurate. Harpy combines standard techniques such as zero-padded FFT and noise-cleaning based on singular value decomposition. This combination also allows estimating errors of phases and amplitudes of beam-related harmonics calculated from cleaned data.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOMS035

About •

Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 20 June 2022

Cite •

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