1. Machine Learning applied to CTA Thomas Vuillaume LAPP, September 2017
03/09/2018
Machine Learning applied to CTA Thomas Vuillaume LAPP, September 2017
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2. Standard machine learning
03/09/2018
Standard machine learning
Standard machine learning
Already in use in other IACT (e.g. boosted decision trees, random forest…)
Use physical parameters derived from images (signal amplitude, ellipsoid length/width… )
Supervised learning
Adaptation and developments for CTA
Use of Python = standardisation with reknown packages (e.g. scikit-learn)
Integration in LAPP pipeline and ctapipe
Energy reconstruction
Particles discrimination
LAPP, 19/09/2017
Thomas Vuillaume
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3. Standard machine learning
03/09/2018
Standard machine learning
User friendly:
LAPP, 19/09/2017
Thomas Vuillaume
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4. Standard machine learning
03/09/2018
Standard machine learning
Python makes exploration easy
LAPP, 19/09/2017
Thomas Vuillaume
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5. Standard machine learning
03/09/2018
Standard machine learning
Developments done jointly with ctapipe’s
Comparison and merging of latest results in one week during ctapipe developers workshop
@LAPP
September 25-29
LAPP, 19/09/2017
Thomas Vuillaume
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6. GammaLearn project GammaLearn project Collaboration of three parties
03/09/2018
GammaLearn project
GammaLearn project
Collaboration of three parties
Made possible under ASTERICS project
LAPP, 19/09/2017
Thomas Vuillaume
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7. 03/09/2018
GammaLearn project
ASTERICS call for expression of interest from industrial partners in December 2016 at 1st workshop
Answer with Orobix, an italian start-up specializing in deep learning (life sciences, manufacturers…)
LAPP, 19/09/2017
Thomas Vuillaume
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8. 18 months collaboration (until the end of ASTERICS)
03/09/2018
GammaLearn project
18 months collaboration (until the end of ASTERICS)
Goal : CTA on-site particle discrimination
Why?
CTA
~5Gbps
Data reduction
1 photon for > 100 proton = Most of signal is noise
Data transfer requires a volume reduction of 1/10
Improve sensitivity
Integration with LAPP pipeline and HPC softwares to make the most out of hybrid architectures
LAPP, 19/09/2017
Thomas Vuillaume
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9. 03/09/2018
GammaLearn project
LISTIC = Laboratoire d’Informatique, Traitement de l’Information et de la Connaissace with a team specializing in deep learning
Collaboration proposal in the form of a co-directed PhD with two sources of fundings
ASTERICS
Fondation de l’Université Savoie Mont-Blanc with project accepted in June
LAPP, 19/09/2017
Thomas Vuillaume
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10. Different but complementary approach with Orobix
03/09/2018
GammaLearn project
Collaboration with Orobix on tools and work environment = learning from industry
Using Generative Adversarial Networks to reconstruct electromagnetic showers in 3D based on their 2D images from telescopes
Different but complementary approach with Orobix
LAPP, 19/09/2017
Thomas Vuillaume
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11. MoU signed early September!
03/09/2018
GammaLearn project
MoU signed early September!
Kick-off meeting !
MUST, get prepared !
LAPP, 19/09/2017
Thomas Vuillaume
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