Built on

S. Marzani, G. Soyez and M. Spannowsky, Looking inside jets: an introduction to jet substructure and boosted-object phenomenology , 1901.10342
Original
1901
Earlier work this paper cites.
G. Kasieczka, T. Plehn et al., The Machine Learning Landscape of Top Taggers , SciPost Phys. 7
Original
1902
Earlier work this paper cites.
H. Qu and L. Gouskos, ParticleNet: Jet Tagging via Particle Clouds , Physical Review D 101
Original
1902
Earlier work this paper cites.
S. Bollweg, M. Haußmann, G. Kasieczka, M. Luchmann, T. Plehn and J. Thompson, Deep-Learning Jets with Uncertainties and More , SciPost Phys. 8
Original
1904
Earlier work this paper cites.
A. J. Larkoski and E. M. Metodiev, A Theory of Quark vs. Gluon Discrimination , JHEP 10
Original
1906
Earlier work this paper cites.
E. A. Moreno, O. Cerri, J. M. Duarte, H. B. Newman, T. Q. Nguyen, A. Periwal et al., JEDI-net: a jet identification algorithm based on interaction networks , Eur. Phys. J. C80
Original
1908
Earlier work this paper cites.
Z.-B. Kang, K. Lee, X. Liu, D. Neill and F. Ringer, The soft drop groomed jet radius at NLL , JHEP 02
Original
1908
Earlier work this paper cites.
B. Nachman, A guide for deploying Deep Learning in LHC searches: How to achieve optimality and account for uncertainty , SciPost Phys. 8
Original
1909
Earlier work this paper cites.
P. Cal, D. Neill, F. Ringer and W. J. Waalewijn, Calculating the angle between jet axes , JHEP 04
Original
1911
Earlier work this paper cites.
J. Neyman and E. S. Pearson, On the Problem of the Most Efficient Tests of Statistical Hypotheses , Phil. Trans. Roy. Soc. Lond. A231
1933
Earlier work this paper cites.
Y. L. Dokshitzer, G. Leder, S. Moretti and B. Webber, Better jet clustering algorithms , JHEP 9708
1997
Earlier work this paper cites.
G. Kasieczka and D. Shih, DisCo Fever: Robust Networks Through Distance Correlation , 2001.05310
Original
2001
Earlier work this paper cites.
G. Kasieczka, M. Luchmann, F. Otterpohl and T. Plehn, Per-Object Systematics using Deep-Learned Calibration , 2003.11099
Original
2003
Earlier work this paper cites.
S. Amoroso et al., Les Houches 2019: Physics at TeV Colliders: Standard Model Working Group Report , in 11th Les Houches Workshop on Physics at TeV Colliders: PhysTeV Les Houches (PhysTeV 2019) Les Houches, France, June 10-28, 2019 , 2020, 2003.01700
Original
2003
Earlier work this paper cites.
A. J. Larkoski, Improving the Understanding of Jet Grooming in Perturbation Theory , 2006.14680
Original
2006
Earlier work this paper cites.
Y. Yao, L. Rosasco and A. Caponnetto, On early stopping in gradient descent learning , Constructive Approximation 26
2007
Earlier work this paper cites.
M. Cacciari, G. P. Salam and G. Soyez, The Anti-k(t) jet clustering algorithm , JHEP 04
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 , Phys. Rev. Lett. 105
Original
2010
Earlier work this paper cites.
A. Abdesselam et al., Boosted objects: a probe of beyond the standard model physics , EPHJA,C71,1661.2011 C71
Original
2011
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness , JHEP 03
Original
2011
Earlier work this paper cites.
A. Altheimer, S. Arora, L. Asquith, G. Brooijmans, J. Butterworth et al., Jet Substructure at the Tevatron and LHC: New results, new tools, new benchmarks , J.Phys. G39
Original
2012
Earlier work this paper cites.

Similar

J. Thaler and K. Van Tilburg, Maximizing Boosted Top Identification by Minimizing N-subjettiness , JHEP 02
Original
2012
Cited alongside, same era.
M. Cacciari, G. P. Salam and G. Soyez, FastJet User Manual , Eur. Phys. J. C72
Original
2012
Cited alongside, same era.
M. Dasgupta, A. Fregoso, S. Marzani and G. P. Salam, Towards an understanding of jet substructure , JHEP 1309
Original
2013
Cited alongside, same era.
M. Dasgupta, A. Fregoso, S. Marzani and A. Powling, Jet substructure with analytical methods , Eur.Phys.J. C73
Original
2013
Cited alongside, same era.
A. J. Larkoski, G. P. Salam and J. Thaler, Energy Correlation Functions for Jet Substructure , JHEP 1306
Original

Then

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Reading the bibliography…

2020

Towards Machine Learning Analytics for Jet Substructure

Kasieczka, Gregor, Marzani, Simone, Soyez, Gregory et al.

Understand

The past few years have seen a rapid development of machine-learning algorithms.

While surely augmenting performance, these complex tools are often treated as black-boxes and may impair our understanding of the physical processes under study.
The aim of this paper is to move a first step into the direction of applying expert-knowledge in particle physics to calculate the optimal decision function and test whether it is achieved by standard training, thus making the aforementioned black-box more transparent.
In particular, we consider the binary classification problem of discriminating quark-initiated jets from gluon-initiated ones.

Built on

S. Marzani, G. Soyez and M. Spannowsky, Looking inside jets: an introduction to jet substructure and boosted-object phenomenology , 1901.10342
Original
1901
Earlier work this paper cites.
G. Kasieczka, T. Plehn et al., The Machine Learning Landscape of Top Taggers , SciPost Phys. 7
Original
1902
Earlier work this paper cites.
H. Qu and L. Gouskos, ParticleNet: Jet Tagging via Particle Clouds , Physical Review D 101
Original
1902
Earlier work this paper cites.
S. Bollweg, M. Haußmann, G. Kasieczka, M. Luchmann, T. Plehn and J. Thompson, Deep-Learning Jets with Uncertainties and More , SciPost Phys. 8
Original
1904
Earlier work this paper cites.
A. J. Larkoski and E. M. Metodiev, A Theory of Quark vs. Gluon Discrimination , JHEP 10
Original
1906
Earlier work this paper cites.
E. A. Moreno, O. Cerri, J. M. Duarte, H. B. Newman, T. Q. Nguyen, A. Periwal et al., JEDI-net: a jet identification algorithm based on interaction networks , Eur. Phys. J. C80
Original
1908
Earlier work this paper cites.
Z.-B. Kang, K. Lee, X. Liu, D. Neill and F. Ringer, The soft drop groomed jet radius at NLL , JHEP 02
Original
1908
Earlier work this paper cites.
B. Nachman, A guide for deploying Deep Learning in LHC searches: How to achieve optimality and account for uncertainty , SciPost Phys. 8
Original
1909
Earlier work this paper cites.
P. Cal, D. Neill, F. Ringer and W. J. Waalewijn, Calculating the angle between jet axes , JHEP 04
Original
1911
Earlier work this paper cites.
J. Neyman and E. S. Pearson, On the Problem of the Most Efficient Tests of Statistical Hypotheses , Phil. Trans. Roy. Soc. Lond. A231
1933
Earlier work this paper cites.
Y. L. Dokshitzer, G. Leder, S. Moretti and B. Webber, Better jet clustering algorithms , JHEP 9708
1997
Earlier work this paper cites.
G. Kasieczka and D. Shih, DisCo Fever: Robust Networks Through Distance Correlation , 2001.05310
Original
2001
Earlier work this paper cites.
G. Kasieczka, M. Luchmann, F. Otterpohl and T. Plehn, Per-Object Systematics using Deep-Learned Calibration , 2003.11099
Original
2003
Earlier work this paper cites.
S. Amoroso et al., Les Houches 2019: Physics at TeV Colliders: Standard Model Working Group Report , in 11th Les Houches Workshop on Physics at TeV Colliders: PhysTeV Les Houches (PhysTeV 2019) Les Houches, France, June 10-28, 2019 , 2020, 2003.01700
Original
2003
Earlier work this paper cites.
A. J. Larkoski, Improving the Understanding of Jet Grooming in Perturbation Theory , 2006.14680
Original
2006
Earlier work this paper cites.
Y. Yao, L. Rosasco and A. Caponnetto, On early stopping in gradient descent learning , Constructive Approximation 26
2007
Earlier work this paper cites.
M. Cacciari, G. P. Salam and G. Soyez, The Anti-k(t) jet clustering algorithm , JHEP 04
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 , Phys. Rev. Lett. 105
Original
2010
Earlier work this paper cites.
A. Abdesselam et al., Boosted objects: a probe of beyond the standard model physics , EPHJA,C71,1661.2011 C71
Original
2011
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness , JHEP 03
Original
2011
Earlier work this paper cites.
A. Altheimer, S. Arora, L. Asquith, G. Brooijmans, J. Butterworth et al., Jet Substructure at the Tevatron and LHC: New results, new tools, new benchmarks , J.Phys. G39
Original
2012
Earlier work this paper cites.

Similar

J. Thaler and K. Van Tilburg, Maximizing Boosted Top Identification by Minimizing N-subjettiness , JHEP 02
Original
2012
Cited alongside, same era.
M. Cacciari, G. P. Salam and G. Soyez, FastJet User Manual , Eur. Phys. J. C72
Original
2012
Cited alongside, same era.
M. Dasgupta, A. Fregoso, S. Marzani and G. P. Salam, Towards an understanding of jet substructure , JHEP 1309
Original
2013
Cited alongside, same era.
M. Dasgupta, A. Fregoso, S. Marzani and A. Powling, Jet substructure with analytical methods , Eur.Phys.J. C73
Original
2013
Cited alongside, same era.
A. J. Larkoski, G. P. Salam and J. Thaler, Energy Correlation Functions for Jet Substructure , JHEP 1306
Original

Then

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

2013

Cited alongside, same era.

A. L. Maas, A. Y. Hannun and A. Y. Ng, Rectifier nonlinearities improve neural network acoustic models , in Proceedings of ICML Workshop on Deep Learning for Audio, Speech and Language Processing , 2013

2013

Cited alongside, same era.

A. Altheimer, A. Arce, L. Asquith, J. Backus Mayes, E. Bergeaas Kuutmann et al., Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd-27th of July 2012 , Eur.Phys.J. C74

Original

2014

Cited alongside, same era.

A. J. Larkoski, S. Marzani, G. Soyez and J. Thaler, Soft Drop , JHEP 1405

Original

2014

Cited alongside, same era.

A. J. Larkoski, I. Moult and D. Neill, Power Counting to Better Jet Observables , JHEP 12

Original

2014

Cited alongside, same era.

A. J. Larkoski, J. Thaler and W. J. Waalewijn, Gaining (Mutual) Information about Quark/Gluon Discrimination , JHEP 11

Original

2014

Cited alongside, same era.

A. J. Larkoski, D. Neill and J. Thaler, Jet Shapes with the Broadening Axis , JHEP 1404

Original

2014

Cited alongside, same era.

D. Adams et al., Towards an Understanding of the Correlations in Jet Substructure , Eur. Phys. J. C75

Original

2015

Cited alongside, same era.