Contact
Andrea Giammanco
Position
Research scientist
Address
Centre for Cosmology, Particle Physics and Phenomenology - CP3
Université catholique de Louvain
2, Chemin du Cyclotron - Box L7.01.05
B-1348 Louvain-la-Neuve
Belgium
Université catholique de Louvain
2, Chemin du Cyclotron - Box L7.01.05
B-1348 Louvain-la-Neuve
Belgium
Phone
+32 10 47 3221
Office
Personal homepage
UCL member card
People responsibilities
Postdocs
PhD students
Visitors
Interns
Former members
Samuel Bein
(IISN - CMS)
(member since August 2024)
Anna Benecke
(FNRS)
(member since April 2021)
Luigi Favaro
(IISN - MaxLHC)
(member since November 2024)
Zak Lawrence
(IISN - CMS)
(member since September 2024)
Jindrich Lidrych
(IISN)
(member since December 2022)
I am an experimental particle physicist, member of the CMS Collaboration at CERN. I am particularly interested in precision Standard Model measurements and Higgs physics.
I am an experimental particle physicist, member of the CMS Collaboration at CERN. I am particularly interested in precision Standard Model measurements and Higgs physics.
PhD students
Oguz Guzel
(IISN - CMS BSM)
(member since September 2022)
I am interested in the Higgs boson pair production at the LHC and the analysis of CMS data by making use of the data analysis techniques including machine learning.
I am interested in the Higgs boson pair production at the LHC and the analysis of CMS data by making use of the data analysis techniques including machine learning.
Sumaira Ikram
(Other - CAI, Other - CAI)
(member since September 2023)
Simulations and data analysis of a muon radiography experiment at Mt. Vesuvius, Italy.
Simulations and data analysis of a muon radiography experiment at Mt. Vesuvius, Italy.
Maxime Lagrange
(Other - UE - Silentborder)
(member since September 2021)
I am interested in tomographic image reconstruction applied to muography, and how it can benefit from Machine-learning optimization.
I am interested in tomographic image reconstruction applied to muography, and how it can benefit from Machine-learning optimization.
Zahraa Zaher
(Other)
(member since July 2023)
Machine-learning optimization of experiments in fundamental and applied physics.
Machine-learning optimization of experiments in fundamental and applied physics.
Visitors
Abhishek Chauhan
Collaborating with Andrea Giammanco's muography team.
Collaborating with Andrea Giammanco's muography team.
Interns
Giorgio Mauceri
PileUp Per-Particle Identification (PUPPI) developments and studies in the context of CMS and Delphes.
PileUp Per-Particle Identification (PUPPI) developments and studies in the context of CMS and Delphes.
Former members
Research statement
I am a Research Director of FNRS, with 100% focus on research (no teaching).
Broadly speaking, I am interested into:
# Muography, i.e., the application of HEP detectors and techniques for mapping the interior of large structures using atmospheric muons from cosmic ray showers.
* Co-leading, with Eduardo Cortina, the Portable Muoscope project at CP3 (see https://cp3-git.irmp.ucl.ac.be/muographycp3).
* Member of the MUon RAdiography of VESuvius (MURAVES) collaboration.
* Member of the EU-funded SilentBorder consortium, aiming at building practical and cheap muon scanners for border controls.
# Analysis of CMS data at LHC; more specifically:
* Top quark physics: the sixth quark is quite unusual (who ordered that 175 GeV monster?). Could it be the key to unlock the mystery of what's beyond the Standard Model? In the past (Sep.2014-Aug.2016) I coordinated the CMS group devoted to that.
* Higgs boson couplings (with the top quark and with new particles): being the last particle to have been discovered, and by far the most crucial of them all, it is rather natural to check if that famous 125 GeV resonance tells us something that we did not expect. I was one of the coordinators of the work package "Higgs coupling determination and interpretation" of the be.h Belgian HEP consortium (2018-2022).
* Unusual signatures of new physics: our multi-purpose detectors were optimized for as many interesting signatures as possible, but I like when someone proposes original ways to use them, that can actually cover some blind spot of traditional searches. This includes unusual datasets such as heavy ions.
# Parametric detector simulations.
# Some forays into HEP phenomenology, in collaboration with theorists.
# Applied statistics (machine learning, unfolding, etc.)
Broadly speaking, I am interested into:
# Muography, i.e., the application of HEP detectors and techniques for mapping the interior of large structures using atmospheric muons from cosmic ray showers.
* Co-leading, with Eduardo Cortina, the Portable Muoscope project at CP3 (see https://cp3-git.irmp.ucl.ac.be/muographycp3).
* Member of the MUon RAdiography of VESuvius (MURAVES) collaboration.
* Member of the EU-funded SilentBorder consortium, aiming at building practical and cheap muon scanners for border controls.
# Analysis of CMS data at LHC; more specifically:
* Top quark physics: the sixth quark is quite unusual (who ordered that 175 GeV monster?). Could it be the key to unlock the mystery of what's beyond the Standard Model? In the past (Sep.2014-Aug.2016) I coordinated the CMS group devoted to that.
* Higgs boson couplings (with the top quark and with new particles): being the last particle to have been discovered, and by far the most crucial of them all, it is rather natural to check if that famous 125 GeV resonance tells us something that we did not expect. I was one of the coordinators of the work package "Higgs coupling determination and interpretation" of the be.h Belgian HEP consortium (2018-2022).
* Unusual signatures of new physics: our multi-purpose detectors were optimized for as many interesting signatures as possible, but I like when someone proposes original ways to use them, that can actually cover some blind spot of traditional searches. This includes unusual datasets such as heavy ions.
# Parametric detector simulations.
# Some forays into HEP phenomenology, in collaboration with theorists.
# Applied statistics (machine learning, unfolding, etc.)
Projects
Research directions:
Experiments and collaborations:
Active projects
Non-active projects
Data analysis in HEP, astroparticle and GW experiments
Detector commissioning, operation and data processing
Phenomenology of elementary particles
Research and development of new detectors
Theories of the fundamental interactions
Detector commissioning, operation and data processing
Phenomenology of elementary particles
Research and development of new detectors
Theories of the fundamental interactions
Experiments and collaborations:
Active projects
Advanced Multi-Variate Analysis for New Physics Searches at the LHC
Agni Bethani, Christophe Delaere, Andrea Giammanco, Vincent Lemaitre, Fabio Maltoni
With the 2012 discovery of the Higgs boson at the Large Hadron Collider, LHC, the Standard Model of particle physics has been completed, emerging as a most successful description of matter at the smallest distance scales. But as is always the case, the observation of this particle has also heralded the dawn of a new era in the field: particle physics is now turning to the mysteries posed by the presence of dark matter in the universe, as well as the very existence of the Higgs. The upcoming run of the LHC at 13 TeV will probe possible answers to both issues, providing detailed measurements of the properties of the Higgs and extending significantly the sensitivity to new phenomena.
Since the LHC is the only accelerator currently exploring the energy frontier, it is imperative that the analyses of the collected data use the most powerful possible techniques. In recent years several analyses have utilized multi-variate analysis techniques, obtaining higher sensitivity; yet there is ample room for further improvement. With our program we will import and specialize the most powerful advanced statistical learning techniques to data analyses at the LHC, with the objective of maximizing the chance of new physics discoveries.
We have been part of AMVA4NewPhysics, a network of European institutions whose goal is to foster the development and exploitation of Advanced Multi-Variate Analysis for New Physics searches. The network offered between 2015 and 2019 extensive training in both physics and advanced analysis techniques to graduate students, focusing on providing them with the know-how and the experience to boost their career prospects in and outside academia. The network develops ties with non-academic partners for the creation of interdisciplinary software tools, allowing a successful knowledge transfer in both directions. The network studies innovative techniques and identifies their suitability to problems encountered in searches for new physics at the LHC and detailed studies of the Higgs boson sector.
External collaborators: University of Oxford, INFN, University of Padova, Université Blaise Pascal, LIP, IASA, CERN, UCI, EPFL, B12 Consulting, SDG Consulting, Yandex, MathWorks.
With the 2012 discovery of the Higgs boson at the Large Hadron Collider, LHC, the Standard Model of particle physics has been completed, emerging as a most successful description of matter at the smallest distance scales. But as is always the case, the observation of this particle has also heralded the dawn of a new era in the field: particle physics is now turning to the mysteries posed by the presence of dark matter in the universe, as well as the very existence of the Higgs. The upcoming run of the LHC at 13 TeV will probe possible answers to both issues, providing detailed measurements of the properties of the Higgs and extending significantly the sensitivity to new phenomena.
Since the LHC is the only accelerator currently exploring the energy frontier, it is imperative that the analyses of the collected data use the most powerful possible techniques. In recent years several analyses have utilized multi-variate analysis techniques, obtaining higher sensitivity; yet there is ample room for further improvement. With our program we will import and specialize the most powerful advanced statistical learning techniques to data analyses at the LHC, with the objective of maximizing the chance of new physics discoveries.
We have been part of AMVA4NewPhysics, a network of European institutions whose goal is to foster the development and exploitation of Advanced Multi-Variate Analysis for New Physics searches. The network offered between 2015 and 2019 extensive training in both physics and advanced analysis techniques to graduate students, focusing on providing them with the know-how and the experience to boost their career prospects in and outside academia. The network develops ties with non-academic partners for the creation of interdisciplinary software tools, allowing a successful knowledge transfer in both directions. The network studies innovative techniques and identifies their suitability to problems encountered in searches for new physics at the LHC and detailed studies of the Higgs boson sector.
External collaborators: University of Oxford, INFN, University of Padova, Université Blaise Pascal, LIP, IASA, CERN, UCI, EPFL, B12 Consulting, SDG Consulting, Yandex, MathWorks.
Development of a framework for fast simulation of a generic collider experiment: Delphes
Jérôme de Favereau, Christophe Delaere, Pavel Demin, Andrea Giammanco, Vincent Lemaitre
Observability of new phenomenological models in High Energy experiments is delicate to evaluate, due to the complexity of the related detectors, DAQ chain and software. Delphes is a new framework for fast simulation of a general purpose experiment. The simulation includes a tracking system, a magnetic field, calorimetry and a muon system, and possible very forward detectors arranged along the beamline. The framework is interfaced to standard file format from event generators and outputs observable analysis data objects. The simulation takes into account the detector resolutions, usual reconstruction algorithms for complex objects (FastJet) and a simplified trigger emulation. Detection of very forward scattered particles relies on the transport in beamlines with the Hector software.
Observability of new phenomenological models in High Energy experiments is delicate to evaluate, due to the complexity of the related detectors, DAQ chain and software. Delphes is a new framework for fast simulation of a general purpose experiment. The simulation includes a tracking system, a magnetic field, calorimetry and a muon system, and possible very forward detectors arranged along the beamline. The framework is interfaced to standard file format from event generators and outputs observable analysis data objects. The simulation takes into account the detector resolutions, usual reconstruction algorithms for complex objects (FastJet) and a simplified trigger emulation. Detection of very forward scattered particles relies on the transport in beamlines with the Hector software.
Imaging with cosmic-ray muons
Abhishek Chauhan, Eduardo Cortina Gil, Pavel Demin, Khalil El Achi, Andrea Giammanco, Sumaira Ikram, Maxime Lagrange, Nicolas Szilasi, Ayman Youssef, Zahraa Zaher
The general goal of this project is to develop muon-based radiography or tomography (“muography”), an innovative multidisciplinary approach to study large-scale natural or man-made structures, establishing a strong synergy between particle physics and other disciplines, such as geology and archaeology.
Muography is an imaging technique that relies on the measurement of the absorption of muons produced by the interactions of cosmic rays with the atmosphere.
Applications span from geophysics (the study of the interior of mountains and the remote quasi-online monitoring of active volcanoes) to archaeology and mining.
We are using the local facilities at CP3 for the development of high-resolution portable detectors based on Resistive Plate Chambers.
We also participate to the MURAVES collaboration through simulations (including the coordination of the Monte Carlo group), data-analysis developments (an example of the latter is the implementation and in-situ calibration of time-of-flight capabilities), and development of a new database.
We are part of the H2020-RIA project SilentBorder, which aims at developing new muon scanners at border controls. Our role in this project is to develop a parametric simulation and a ML-based detector optimization procedure.
We are also part of the H2020-MSCA-RISE network INTENSE where we coordinate the Muography work package, which brings together particle physicists, geophysicists, archaeologists, civil engineers and private companies for the development and exploitation of this imaging method.
External collaborators: UGent; Kyushu University; INTENSE Research & Innovation Staff Exchange network (Japan, Switzerland, Italy, France, Hungary); SilentBorder network (Estonia, Germany, Finland, Turkey, Italy, UK); MURAVES Collaboration including INFN, INGV, universities of Florence and Federico II Naples, UGent, VUB.
The general goal of this project is to develop muon-based radiography or tomography (“muography”), an innovative multidisciplinary approach to study large-scale natural or man-made structures, establishing a strong synergy between particle physics and other disciplines, such as geology and archaeology.
Muography is an imaging technique that relies on the measurement of the absorption of muons produced by the interactions of cosmic rays with the atmosphere.
Applications span from geophysics (the study of the interior of mountains and the remote quasi-online monitoring of active volcanoes) to archaeology and mining.
We are using the local facilities at CP3 for the development of high-resolution portable detectors based on Resistive Plate Chambers.
We also participate to the MURAVES collaboration through simulations (including the coordination of the Monte Carlo group), data-analysis developments (an example of the latter is the implementation and in-situ calibration of time-of-flight capabilities), and development of a new database.
We are part of the H2020-RIA project SilentBorder, which aims at developing new muon scanners at border controls. Our role in this project is to develop a parametric simulation and a ML-based detector optimization procedure.
We are also part of the H2020-MSCA-RISE network INTENSE where we coordinate the Muography work package, which brings together particle physicists, geophysicists, archaeologists, civil engineers and private companies for the development and exploitation of this imaging method.
External collaborators: UGent; Kyushu University; INTENSE Research & Innovation Staff Exchange network (Japan, Switzerland, Italy, France, Hungary); SilentBorder network (Estonia, Germany, Finland, Turkey, Italy, UK); MURAVES Collaboration including INFN, INGV, universities of Florence and Federico II Naples, UGent, VUB.
Machine-learning Optimized Design of Experiments
Andrea Giammanco, Maxime Lagrange, Zahraa Zaher
We are among the founders of MODE (Machine-learning Optimized Design of Experiments, https://mode-collaboration.github.io/), a multi-disciplinary consortium of European and American physicists and computer scientists who target the use of differentiable programming in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection.
We aim to develop a modular, customizable, and scalable, fully differentiable pipeline for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.
The main goal of our activities is to develop an architecture that can be adapted to the above use cases but will also be customizable to any other experimental endeavour employing particle detection at its core. We welcome suggestions, as well as interest in joining our effort, by researchers focusing on use cases for which this technology can be of benefit.
External collaborators: University of Padova, INFN, Université Clermont Auvergne, Higher School of Economics of Moscow, CERN, University of Oxford, New York University, ULiege.
We are among the founders of MODE (Machine-learning Optimized Design of Experiments, https://mode-collaboration.github.io/), a multi-disciplinary consortium of European and American physicists and computer scientists who target the use of differentiable programming in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection.
We aim to develop a modular, customizable, and scalable, fully differentiable pipeline for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.
The main goal of our activities is to develop an architecture that can be adapted to the above use cases but will also be customizable to any other experimental endeavour employing particle detection at its core. We welcome suggestions, as well as interest in joining our effort, by researchers focusing on use cases for which this technology can be of benefit.
External collaborators: University of Padova, INFN, Université Clermont Auvergne, Higher School of Economics of Moscow, CERN, University of Oxford, New York University, ULiege.
Properties of ttW and ttH production
Anna Benecke, Andrea Giammanco, Oguz Guzel, Jindrich Lidrych
We take advantage of the large statistics already recorded in Run 2 and being recorded in Run 3 by the CMS experiment to launch a systematic study of cross section, angular asymmetries and other properties in the ttW and ttH processes, which have a potentially large sensitivity to non-SM effects.
In synergy with the CP3 phenomenology group, we aim at reporting our results in a form that can be easily translated in EFT constraints.
External collaborators: CMS collaboration.
We take advantage of the large statistics already recorded in Run 2 and being recorded in Run 3 by the CMS experiment to launch a systematic study of cross section, angular asymmetries and other properties in the ttW and ttH processes, which have a potentially large sensitivity to non-SM effects.
In synergy with the CP3 phenomenology group, we aim at reporting our results in a form that can be easily translated in EFT constraints.
External collaborators: CMS collaboration.
Single top studies at LHC
Andrea Giammanco
The electroweak production cross section of single top quarks is an important measurement for LHC, being a potential window on "new physics" effects.
Past achievements of this group include the very first measurement at 7 TeV (in t channel) with 2010 data, followed by the most precise inclusive cross section measurements of t-channel cross section at 7, 8 and 13 TeV, and the first differential measurements at 13 TeV; the most precise |Vtb| extraction from single top in the world; the first measurement of W-helicity fractions in a single-top topology; the first observation of the tW production mode; the first measurement of single-top polarization in t channel; stringent limits on anomalous tWb, tgu, tgc couplings.
External collaborators: CMS collaboration.
The electroweak production cross section of single top quarks is an important measurement for LHC, being a potential window on "new physics" effects.
Past achievements of this group include the very first measurement at 7 TeV (in t channel) with 2010 data, followed by the most precise inclusive cross section measurements of t-channel cross section at 7, 8 and 13 TeV, and the first differential measurements at 13 TeV; the most precise |Vtb| extraction from single top in the world; the first measurement of W-helicity fractions in a single-top topology; the first observation of the tW production mode; the first measurement of single-top polarization in t channel; stringent limits on anomalous tWb, tgu, tgc couplings.
External collaborators: CMS collaboration.
Top quarks in Heavy Ion collisions and other non-standard LHC datasets
Andrea Giammanco
The top quark, being the heaviest known elementary particle, is a powerful tool to test QCD.
The study of top quark pair production in Heavy Ion collisions at the LHC, making use of the dedicated Pb-Pb and p-Pb runs, will open a new road in the investigation of the Quark-Gluon Plasma.
This research project started with the first measurement of top-pair cross section in pp collisions at 5.02 TeV, taking advantage of a "reference run" in Nov.2015. We then update the result with a new publication making use of the larger statistics collected at the end of 2017. This measurement, in addition to being useful as a reference for measurements in Pb-Pb and p-Pb collisions at the same center-of-mass energy per nucleon, also provides a significant broadening of the lever arm for global PDF fits making use of top-quark data.
We then reported the first observation of top quark production in p-Pb collisions, using the data at 8.16 TeV taken in Nov.2016, testing the models of nuclear modification of the gluon PDF at high Bjorken-x. Finally, we provided evidence of top quark production also in Pb-Pb collisions.
We are interested in using future PbPb collision data to probe the time evolution of the QGP using top quarks.
External collaborators: David D'Enterria, Pedro Silva (CERN), Georgios Krintiras (Kansas U.).
The top quark, being the heaviest known elementary particle, is a powerful tool to test QCD.
The study of top quark pair production in Heavy Ion collisions at the LHC, making use of the dedicated Pb-Pb and p-Pb runs, will open a new road in the investigation of the Quark-Gluon Plasma.
This research project started with the first measurement of top-pair cross section in pp collisions at 5.02 TeV, taking advantage of a "reference run" in Nov.2015. We then update the result with a new publication making use of the larger statistics collected at the end of 2017. This measurement, in addition to being useful as a reference for measurements in Pb-Pb and p-Pb collisions at the same center-of-mass energy per nucleon, also provides a significant broadening of the lever arm for global PDF fits making use of top-quark data.
We then reported the first observation of top quark production in p-Pb collisions, using the data at 8.16 TeV taken in Nov.2016, testing the models of nuclear modification of the gluon PDF at high Bjorken-x. Finally, we provided evidence of top quark production also in Pb-Pb collisions.
We are interested in using future PbPb collision data to probe the time evolution of the QGP using top quarks.
External collaborators: David D'Enterria, Pedro Silva (CERN), Georgios Krintiras (Kansas U.).
Non-active projects
Publications in IRMP
All my publications on Inspire
Number of publications as IRMP member: 137
Last 5 publications
More publications
Number of publications as IRMP member: 137
Last 5 publications
2024
IRMP-CP3-24-34: Characterization and stability tests of gas-tight RPC for muography application
Vishal Kumar, Samip Basnet, Eduardo Cortina Gil, R.M.I.D. Gamage, Andrea Giammanco, Marwa Moussawi, Amrutha Samalan, Michael Tytgat, Raveendrababu Karnam
[Full text]
Peer-reviewed proceedings.
Refereed paper. November 11.
[Full text]
Peer-reviewed proceedings.
Refereed paper. November 11.
IRMP-CP3-24-14: Cosmic rays for imaging cultural heritage objects
IRMP-CP3-24-08: A Simulation of a Cosmic Ray Tomography Scanner for Trucks and Shipping Containers
Anzori Georgadze, Andrea Giammanco, Vitaly Kudryavtsev, Maxime Lagrange, Cenk Turkoglu
[Full text]
Proceedings of the International Workshop on Cosmic-Ray Muography (Muography2023), Naples, Italy
Refereed paper. Contribution to proceedings. March 11.
[Full text]
Proceedings of the International Workshop on Cosmic-Ray Muography (Muography2023), Naples, Italy
Refereed paper. Contribution to proceedings. March 11.
2023
IRMP-CP3-23-73: Performance testing of gas-tight portable RPC for muography applications
V. Kumar, S. Basnet, E. Cortina Gil, P. Demin, R. M. I. D. Gamage, A. Giammanco, R. Karnam, M. Moussawi, A. Samalan, M. Tytgat, A. Youssef
[Abstract] [PDF] [Full text]
Proceedings of the Innovative Particle and Radiation Detectors 2023 (IPRD23) workshop.
Published in JINST 19 (2024) C04027
DOI 10.1088/1748-0221/19/04/C04027
Contribution to proceedings. December 13.
[Abstract] [PDF] [Full text]
Proceedings of the Innovative Particle and Radiation Detectors 2023 (IPRD23) workshop.
Published in JINST 19 (2024) C04027
DOI 10.1088/1748-0221/19/04/C04027
Contribution to proceedings. December 13.
More publications