IPAC2019 - List of Authors (Coello de Portugal, J.M.)

Paper	Title	Page
MOPMP027	Second Order Dispersion Measurements in LHC	496
	J. Keintzel, M. Hofer TU Vienna, Wien, Austria J.M. Coello de Portugal, J. Dilly, E. Fol, A. Garcia-Tabares, M. Hofer, J. Keintzel, E.H. Maclean, L. Malina, T.H.B. Persson, R. Tomás, A. Wegscheider CERN, Geneva, Switzerland
	The quadratic dependence of the orbit on the relative momentum offset, also known as second order dispersion, is analysed for the first time for the LHC. In this paper, the measurement and analysis procedure are described. Results and implications on future optics are discussed.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-MOPMP027
About •	paper received ※ 02 May 2019 paper accepted ※ 17 May 2019 issue date ※ 21 June 2019
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MOPMP033	LHC Run 2 Optics Commissioning Experience in View of HL-LHC	508
	R. Tomás, F.S. Carlier, J.M. Coello de Portugal, J. Dilly, S.D. Fartoukh, E. Fol, D. Gamba, A. Garcia-Tabares, M. Giovannozzi, M. Hofer, E.H. Maclean, L. Malina, T.H.B. Persson, P.K. Skowroński, M. Solfaroli, M.L. Spitznagel, A. Wegscheider, J. Wenninger, D.W. Wolf CERN, Geneva, Switzerland
	LHC Run 2 has achieved a beta lower than a factor 2 below design. This has significantly challenged optics measurement and correction techniques in the linear and non-linear regimes, leading to the development of new approaches. Furthermore, experimenting with a large variety of optics has allowed facing the difficulties of future optics and gaining understanding of the machine imperfections. A summary of these aspects is given in view of their implications for the HL-LHC Project.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-MOPMP033
About •	paper received ※ 07 May 2019 paper accepted ※ 20 May 2019 issue date ※ 21 June 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEYYPLM2	The 2018 Heavy-Ion Run of the LHC	2258
	J.M. Jowett, C. Bahamonde Castro, W. Bartmann, C. Bracco, R. Bruce, J.M. Coello de Portugal, J. Dilly, S.D. Fartoukh, E. Fol, N. Fuster-Martínez, A. Garcia-Tabares, M. Hofer, E.B. Holzer, M.A. Jebramcik, J. Keintzel, A. Lechner, E.H. Maclean, L. Malina, T. Medvedeva, A. Mereghetti, T.H.B. Persson, B.Aa. Petersen, S. Redaelli, B. Salvachua, M. Schaumann, C. Schwick, M. Solfaroli, M.L. Spitznagel, H. Timko, R. Tomás, A. Wegscheider, J. Wenninger, D. Wollmann CERN, Meyrin, Switzerland D. Mirarchi The University of Manchester, The Photon Science Institute, Manchester, United Kingdom
	The fourth one-month Pb-Pb collision run brought LHC Run 2 to an end in December 2018. Following the tendency to reduce dependence on the configuration of the preceding proton run, a completely new optics cycle with the strongest ever focussing at the ALICE and LHCb experiments was designed and rapidly implemented, demonstrating the maturity of the collider’s operating modes. Beam-loss monitor thresholds were carefully adjusted to provide optimal protection from the multiple loss mechanisms in heavy-ion operation. A switch from a basic bunch-spacing of 100 ns to 75 ns was made as the beam became available from the injector chain. A new record luminosity, 6 times the original design and close to the operating value proposed for HL-LHC, provided validation of the strategy for mitigating quenches due to bound-free pair production (BFPP) at the interaction points of the ATLAS and CMS experiments. Most of the beam parameters of the HL-LHC Pb-Pb upgrade were attained during this run and the integrated luminosity goals for the first 10 years of LHC operation were substantially exceeded.
	Slides WEYYPLM2 [10.884 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEYYPLM2
About •	paper received ※ 08 May 2019 paper accepted ※ 22 May 2019 issue date ※ 21 June 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPGW081	Unsupervised Machine Learning for Detection of Faulty Beam Position Monitors	2668
SUSPFO097	use link to see paper's listing under its alternate paper code
	E. Fol, J.M. Coello de Portugal, R. Tomás CERN, Geneva, Switzerland
	Unsupervised learning includes anomaly detection techniques that are suitable for the detection of unusual events such as instrumentation faults in particle accelerators. In this work we present the application of decision trees-based algorithm to faulty BPMs detection at the LHC. This method achieves significant improvements in quality of optics measurements and allows to identify relevant signal properties that contribute to fault detection.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEPGW081
About •	paper received ※ 14 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPGW116	LHC Optics Measurement and Correction Software Progress and Plans	2773
	R. Tomás, F.S. Carlier, J.M. Coello de Portugal, J. Dilly, E. Fol, A. Garcia-Tabares, M. Hofer, E.H. Maclean, L. Malina, T.H.B. Persson, P.K. Skowroński, M.L. Spitznagel, A. Wegscheider, J. Wenninger CERN, Meyrin, Switzerland J.F. Cardona, Y. Rodriguez UNAL, Bogota D.C, Colombia F.S. Carlier NIKHEF, Amsterdam, The Netherlands D. Esperante Pereira, J. Fuster, D. Gonzalez-Iglesias IFIC, Valencia, Spain R. Hoekstra KVI, Groningen, The Netherlands
	LHC Optics Measurements and Corrections (OMC) require efficient on-line software applications to acquire and analyze data and to compute the necessary corrections. During Run 2 various measurement and correction techniques have been merged to yield unprecedented optics quality, increasing the required number of steps to finalize the optics commissioning and the size of the software project. In turn, this calls for a higher level of automation, where machine learning techniques are being implemented. During the Long Shutdown 2 a large refactoring of the codes will be in place to improve performance, maintainability and extensibility. A description of the current status of the software and future plans is given.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEPGW116
About •	paper received ※ 07 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPRB077	Optics Corrections Using Machine Learning in the LHC	3990
	E. Fol, J.M. Coello de Portugal, R. Tomás CERN, Geneva, Switzerland G. Franchetti GSI, Darmstadt, Germany
	Optics corrections in the LHC are based on a response matrix approach between available correctors and observables. Supervised learning has been applied to quadrupole error prediction at the LHC giving promising results in simulations and surpassing the performance of the traditional approach. A comparison of different algorithms is given and it is followed by the presentation of further possible concepts to obtain optics corrections using machine learning.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-THPRB077
About •	paper received ※ 14 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Second Order Dispersion Measurements in LHC

496

J. Keintzel, M. Hofer
TU Vienna, Wien, Austria
J.M. Coello de Portugal, J. Dilly, E. Fol, A. Garcia-Tabares, M. Hofer, J. Keintzel, E.H. Maclean, L. Malina, T.H.B. Persson, R. Tomás, A. Wegscheider
CERN, Geneva, Switzerland

The quadratic dependence of the orbit on the relative momentum offset, also known as second order dispersion, is analysed for the first time for the LHC. In this paper, the measurement and analysis procedure are described. Results and implications on future optics are discussed.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-MOPMP027

About •

paper received ※ 02 May 2019 paper accepted ※ 17 May 2019 issue date ※ 21 June 2019

Export •

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

MOPMP033

LHC Run 2 Optics Commissioning Experience in View of HL-LHC

508

R. Tomás, F.S. Carlier, J.M. Coello de Portugal, J. Dilly, S.D. Fartoukh, E. Fol, D. Gamba, A. Garcia-Tabares, M. Giovannozzi, M. Hofer, E.H. Maclean, L. Malina, T.H.B. Persson, P.K. Skowroński, M. Solfaroli, M.L. Spitznagel, A. Wegscheider, J. Wenninger, D.W. Wolf
CERN, Geneva, Switzerland

LHC Run 2 has achieved a beta lower than a factor 2 below design. This has significantly challenged optics measurement and correction techniques in the linear and non-linear regimes, leading to the development of new approaches. Furthermore, experimenting with a large variety of optics has allowed facing the difficulties of future optics and gaining understanding of the machine imperfections. A summary of these aspects is given in view of their implications for the HL-LHC Project.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-MOPMP033

About •

paper received ※ 07 May 2019 paper accepted ※ 20 May 2019 issue date ※ 21 June 2019

Export •

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

WEYYPLM2

The 2018 Heavy-Ion Run of the LHC

2258

J.M. Jowett, C. Bahamonde Castro, W. Bartmann, C. Bracco, R. Bruce, J.M. Coello de Portugal, J. Dilly, S.D. Fartoukh, E. Fol, N. Fuster-Martínez, A. Garcia-Tabares, M. Hofer, E.B. Holzer, M.A. Jebramcik, J. Keintzel, A. Lechner, E.H. Maclean, L. Malina, T. Medvedeva, A. Mereghetti, T.H.B. Persson, B.Aa. Petersen, S. Redaelli, B. Salvachua, M. Schaumann, C. Schwick, M. Solfaroli, M.L. Spitznagel, H. Timko, R. Tomás, A. Wegscheider, J. Wenninger, D. Wollmann
CERN, Meyrin, Switzerland
D. Mirarchi
The University of Manchester, The Photon Science Institute, Manchester, United Kingdom

The fourth one-month Pb-Pb collision run brought LHC Run 2 to an end in December 2018. Following the tendency to reduce dependence on the configuration of the preceding proton run, a completely new optics cycle with the strongest ever focussing at the ALICE and LHCb experiments was designed and rapidly implemented, demonstrating the maturity of the collider’s operating modes. Beam-loss monitor thresholds were carefully adjusted to provide optimal protection from the multiple loss mechanisms in heavy-ion operation. A switch from a basic bunch-spacing of 100 ns to 75 ns was made as the beam became available from the injector chain. A new record luminosity, 6 times the original design and close to the operating value proposed for HL-LHC, provided validation of the strategy for mitigating quenches due to bound-free pair production (BFPP) at the interaction points of the ATLAS and CMS experiments. Most of the beam parameters of the HL-LHC Pb-Pb upgrade were attained during this run and the integrated luminosity goals for the first 10 years of LHC operation were substantially exceeded.

Slides WEYYPLM2 [10.884 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEYYPLM2

About •

paper received ※ 08 May 2019 paper accepted ※ 22 May 2019 issue date ※ 21 June 2019

Export •

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

WEPGW081

Unsupervised Machine Learning for Detection of Faulty Beam Position Monitors

2668

SUSPFO097

use link to see paper's listing under its alternate paper code

E. Fol, J.M. Coello de Portugal, R. Tomás
CERN, Geneva, Switzerland

Unsupervised learning includes anomaly detection techniques that are suitable for the detection of unusual events such as instrumentation faults in particle accelerators. In this work we present the application of decision trees-based algorithm to faulty BPMs detection at the LHC. This method achieves significant improvements in quality of optics measurements and allows to identify relevant signal properties that contribute to fault detection.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEPGW081

About •

paper received ※ 14 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019

Export •

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

WEPGW116

LHC Optics Measurement and Correction Software Progress and Plans

2773

R. Tomás, F.S. Carlier, J.M. Coello de Portugal, J. Dilly, E. Fol, A. Garcia-Tabares, M. Hofer, E.H. Maclean, L. Malina, T.H.B. Persson, P.K. Skowroński, M.L. Spitznagel, A. Wegscheider, J. Wenninger
CERN, Meyrin, Switzerland
J.F. Cardona, Y. Rodriguez
UNAL, Bogota D.C, Colombia
F.S. Carlier
NIKHEF, Amsterdam, The Netherlands
D. Esperante Pereira, J. Fuster, D. Gonzalez-Iglesias
IFIC, Valencia, Spain
R. Hoekstra
KVI, Groningen, The Netherlands

LHC Optics Measurements and Corrections (OMC) require efficient on-line software applications to acquire and analyze data and to compute the necessary corrections. During Run 2 various measurement and correction techniques have been merged to yield unprecedented optics quality, increasing the required number of steps to finalize the optics commissioning and the size of the software project. In turn, this calls for a higher level of automation, where machine learning techniques are being implemented. During the Long Shutdown 2 a large refactoring of the codes will be in place to improve performance, maintainability and extensibility. A description of the current status of the software and future plans is given.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-WEPGW116

About •

paper received ※ 07 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019

Export •

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

THPRB077

Optics Corrections Using Machine Learning in the LHC

3990

E. Fol, J.M. Coello de Portugal, R. Tomás
CERN, Geneva, Switzerland
G. Franchetti
GSI, Darmstadt, Germany

Optics corrections in the LHC are based on a response matrix approach between available correctors and observables. Supervised learning has been applied to quadrupole error prediction at the LHC giving promising results in simulations and surpassing the performance of the traditional approach. A comparison of different algorithms is given and it is followed by the presentation of further possible concepts to obtain optics corrections using machine learning.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2019-THPRB077

About •

paper received ※ 14 May 2019 paper accepted ※ 21 May 2019 issue date ※ 21 June 2019

Export •

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