I Workshop de Computing y Software de la Red Española de LHC

Contribution List

11. Welcome

Carmen Garcia (Univ. of Valencia and CSIC (ES))

28/04/2021, 09:00

COMCHA

27. Information

Andreu Pacheco Pages (Institut de Física d'Altes Energies - Barcelona (ES)), Jose Hernandez (CIEMAT), Jose Salt (Univ. of Valencia and CSIC (ES)), Luca Fiorini (Univ. of Valencia and CSIC (ES))

28/04/2021, 09:09

COMCHA

1. Hardware for Machine Learning and ML as a service

Miguel Ángel Martínez del Amor (University of Seville)

28/04/2021, 09:10

COMCHA

2. Anomalies detection with Machine Learning at the LHC

Judita Mamuzic (IFIC Valencia)

28/04/2021, 10:00

COMCHA

3. Application of Machine Learning for LHC experiment operations

Pablo Martinez Ruiz Del Arbol (Universidad de Cantabria and CSIC (ES))

28/04/2021, 11:30

COMCHA

4. Topical presentations

28/04/2021, 12:20

COMCHA

5. Future of COMCHA

Arantza De Oyanguren Campos (Univ. of Valencia and CSIC (ES))

28/04/2021, 13:35

COMCHA

12. Welcome and Introduction

Jose Salt (Univ. of Valencia and CSIC (ES))

29/04/2021, 09:00

LHC Computing

18. Lightweight site federation for CMS support

Antonio Delgado Peris (Centro de Investigaciones Energéti cas Medioambientales y Tecno)

29/04/2021, 09:10

LHC Computing

LHC Computing Short Presentation

LHC Computing

19. Exploitation of network-segregated CPU resources at BSC for CMS

Jose Hernandez (CIEMAT)

29/04/2021, 09:25

LHC Computing

LHC Computing Short Presentation

LHC Computing

21. ATLAS EventIndex: A Catalogue of all ATLAS Events

Carlos Garcia Montoro (Univ. of Valencia and CSIC (ES))

29/04/2021, 09:40

LHC Computing

LHC Computing Short Presentation

LHC Computing

25. A Spanish data cache service for the CMS experiment

Jose Flix Molina (Centro de Investigaciones Energéti cas Medioambientales y Tecno)

29/04/2021, 09:55

LHC Computing

LHC Computing Short Presentation

LHC Computing

8. Resources and exploitation

Santiago Gonzalez De La Hoz (Univ. of Valencia and CSIC (ES))

29/04/2021, 10:10

LHC Computing

9. Data Management

Jose Flix Molina (Centro de Investigaciones Energéti cas Medioambientales y Tecno), Jose Hernandez (CIEMAT)

29/04/2021, 11:30

LHC Computing

10. Analysis Facilities

Andreu Pacheco Pages (Institut de Física d'Altes Energies - Barcelona (ES)), Antonio Perez-Calero Yzquierdo (Centro de Investigaciones Energéti cas Medioambientales y Tecno)

29/04/2021, 12:15

LHC Computing

6. Strategy and perspectives

Andreu Pacheco Pages (Institut de Física d'Altes Energies - Barcelona (ES)), Jose Hernandez (CIEMAT), Jose Salt (Univ. of Valencia and CSIC (ES))

29/04/2021, 13:00

LHC Computing

LHC Computing

20. A Deep Learning approach to LHCb Calorimeter reconstruction using a Cellular Automaton

Nuria Valls Canudas (La Salle, Ramon Llull University (ES))

COMCHA

COMCHA Short Presentation

COMCHA

The optimization of reconstruction algorithms has become a key aspect in LHCb as it is currently undergoing a major upgrade that will considerably increase the data processing rate. Aiming to accelerate the second most time consuming reconstruction process of the trigger, we propose an alternative reconstruction algorithm for the Electromagnetic Calorimeter of LHCb. Together with the use of...

26. DNN used in the search for scalar top quark pair production in the top corridor region

Andrea Trapote Fernandez (Universidad de Oviedo (ES))

COMCHA

COMCHA Short Presentation

COMCHA

A parametric DNN algorithm is used to separate signal from background in the search for scalar top quark pair production at the LHC. This search targets a region of parameter space where the kinematics of top squark pair production and top quark pair production are very similar, because of the mass difference between the top squark and the neutralino being close to the top quark mass. The...

23. High-dimensional sampling algorithms comparison for particle and astrophysics applications

Judita Mamuzic (IFIC Valencia)

COMCHA

COMCHA Short Presentation

COMCHA

High energy physics analyses often encounter optimization problems in high-dimensional parameter space, and finding an optimal algorithm represents an important initial step in each analysis, where typically an optimum of a very complicated function needs to be found. We performed an optimization algorithm comparison using a number of test functions, for increasing dimensionality, and compared...

22. Hunting dark matter signals with deep learning at the LHC

Dr Andres Daniel Perez (IFLP - UNLP/CONICET)

COMCHA

COMCHA Short Presentation

COMCHA

We study several simplified dark matter models and their signatures at the LHC using Neural Networks. We focus on the usual monojet plus missing transverse energy channel, but to train the algorithms we organize the data in 2D histograms instead of event-by-event arrays. This results in a huge performance boost to distinguish between standard model (SM) only and SM plus new physics signals. We...

24. Jet classification in t-tbar decays of heavy BSM resonances in ATLAS using ML techniques

Jorge Juan Martinez De Lejarza Samper (Univ. of Valencia and CSIC (ES))

COMCHA

COMCHA Short Presentation

COMCHA

The search for heavy resonances with diverse mass and width values is the ultimate goal of the ATLAS physics group where we are developing this
study. The analysis selects events where one of the top quarks decays hadronically and the other one semileptonically. The reconstruction of the
different components of the decay allows us to build an invariant mass distribution which would show...

7. Short presentations

LHC Computing

LHC Computing

14. Test

LHC Computing

LHC Computing Short Presentation

LHC Computing

This is a test