Built on

J. Neyman and E. S. Pearson, On the problem of the most efficient tests of statistical hypotheses
1933
Earlier work this paper cites.
S. Catani, Y. L. Dokshitzer, M. H. Seymour, and B. R. Webber, Longitudinally invariant K t K_{t} clustering algorithms for hadron hadron collisions
1993
Earlier work this paper cites.
S. D. Ellis and D. E. Soper, Successive combination jet algorithm for hadron collisions
1993
Earlier work this paper cites.
Y. L. Dokshitzer, G. D. Leder, S. Moretti, and B. R. Webber, Better jet clustering algorithms
1997
Earlier work this paper cites.
hep-ph/9907280
M. Wobisch and T. Wengler, Hadronization corrections to jet cross-sections in deep inelastic scattering · 1998
Earlier work this paper cites.
hep-ex/0005012
G. C. Blazey et al., Run II jet physics · 2000
Earlier work this paper cites.
T. Sjostrand, S. Mrenna, and P. Z. Skands, PYTHIA 6.4 Physics and Manual
2006
Earlier work this paper cites.
M. Cacciari and G. P. Salam, Dispelling the N 3 N^{3} myth for the k t k_{t} jet-finder
2006
Earlier work this paper cites.
M. Bahr et al., Herwig++ Physics and Manual
Original
2008
Earlier work this paper cites.
M. Cacciari, G. P. Salam, and G. Soyez, The Anti-k(t) jet clustering algorithm
Original
2008
Earlier work this paper cites.
I. W. Stewart, F. J. Tackmann, and W. J. Waalewijn, N-Jettiness: An Inclusive Event Shape to Veto Jets
Original
2010
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness
Original
2011
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Maximizing Boosted Top Identification by Minimizing N-subjettiness
Original
2012
Earlier work this paper cites.

Similar

M. Cacciari, G. P. Salam, and G. Soyez, FastJet User Manual
Original
2012
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M. Dasgupta, A. Fregoso, S. Marzani, and G. P. Salam, Towards an understanding of jet substructure
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2013
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M. Dasgupta, A. Fregoso, S. Marzani, and A. Powling, Jet substructure with analytical methods
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2013
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Original
2013
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A. J. Larkoski and J. Thaler, Unsafe but Calculable: Ratios of Angularities in Perturbative QCD
Original

Then

F. Chollet, “Keras.” https://github.com/fchollet/keras , 2015
2015
Later among the works it cites.
A. J. Larkoski, S. Marzani, and J. Thaler, Sudakov Safety in Perturbative QCD
Original
2015
Later among the works it cites.
L. de Oliveira, M. Kagan, L. Mackey, B. Nachman, and A. Schwartzman, Jet-images ? deep learning edition
Original
2016
Later among the works it cites.
P. Baldi, K. Bauer, C. Eng, P. Sadowski, and D. Whiteson, Jet Substructure Classification in High-Energy Physics with Deep Neural Networks
Original
2016
Later among the works it cites.
D. Guest, J. Collado, P. Baldi, S.-C. Hsu, G. Urban, and D. Whiteson, Jet Flavor Classification in High-Energy Physics with Deep Neural Networks
Original
2016

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2017

Novel Jet Observables from Machine Learning

Datta, Kaustuv, Larkoski, Andrew J.

Understand

Previous studies have demonstrated the utility and applicability of machine learning techniques to jet physics.

In this paper, we construct new observables for the discrimination of jets from different originating particles exclusively from information identified by the machine.
The approach we propose is to first organize information in the jet by resolved phase space and determine the effective $N$-body phase space at which discrimination power saturates.
This then allows for the construction of a discrimination observable from the $N$-body phase space coordinates.

Built on

J. Neyman and E. S. Pearson, On the problem of the most efficient tests of statistical hypotheses
1933
Earlier work this paper cites.
S. Catani, Y. L. Dokshitzer, M. H. Seymour, and B. R. Webber, Longitudinally invariant K t K_{t} clustering algorithms for hadron hadron collisions
1993
Earlier work this paper cites.
S. D. Ellis and D. E. Soper, Successive combination jet algorithm for hadron collisions
1993
Earlier work this paper cites.
Y. L. Dokshitzer, G. D. Leder, S. Moretti, and B. R. Webber, Better jet clustering algorithms
1997
Earlier work this paper cites.
hep-ph/9907280
M. Wobisch and T. Wengler, Hadronization corrections to jet cross-sections in deep inelastic scattering · 1998
Earlier work this paper cites.
hep-ex/0005012
G. C. Blazey et al., Run II jet physics · 2000
Earlier work this paper cites.
T. Sjostrand, S. Mrenna, and P. Z. Skands, PYTHIA 6.4 Physics and Manual
2006
Earlier work this paper cites.
M. Cacciari and G. P. Salam, Dispelling the N 3 N^{3} myth for the k t k_{t} jet-finder
2006
Earlier work this paper cites.
M. Bahr et al., Herwig++ Physics and Manual
Original
2008
Earlier work this paper cites.
M. Cacciari, G. P. Salam, and G. Soyez, The Anti-k(t) jet clustering algorithm
Original
2008
Earlier work this paper cites.
I. W. Stewart, F. J. Tackmann, and W. J. Waalewijn, N-Jettiness: An Inclusive Event Shape to Veto Jets
Original
2010
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness
Original
2011
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Maximizing Boosted Top Identification by Minimizing N-subjettiness
Original
2012
Earlier work this paper cites.