Literature Search

70 results

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Measurement of jet production in deep inelastic scattering and NNLO determination of the strong coupling at ZEUS

ZEUS

Collaboration

•

I. Abt
(
- Munich, Max Planck Inst.
)

et al.

(Sep 6, 2023)

Published in:
- Eur.Phys.J.C 83 (2023) 11, 1082
•
e-Print:
- 2309.02889 [hep-ex]

DOIdatasets

reference search14 citations

Measurement of CollinearDrop jet mass and its correlation with SoftDrop groomed jet substructure observables in

\sqrt{s}=200

GeV

pp

collisions by STAR

STAR

Collaboration

•

Youqi Song

for the collaboration. (Jul 15, 2023)

e-Print:
- 2307.07718 [nucl-ex]

pdf

reference search13 citations

Toward a generative modeling analysis of CLAS exclusive

2 π

photoproduction

T. Alghamdi
(
- Old Dominion U. and
- Prince Mohammad U., Al Khobar
)
,
Y. Alanazi
(
- Jefferson Lab
)
,
M. Battaglieri
(
- INFN, Genoa
)
,
L. Bibrzycki
(
- AGH-UST, Cracow
)
,
A.V. Golda
(
- Moscow State U.
)

et al.

(Jul 10, 2023)

Published in:
- Phys.Rev.D 108 (2023) 9, 094030
•
e-Print:
- 2307.04450 [hep-ph]

pdflinksDOI

reference search6 citations

End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics

Alexander Shmakov
(
- UC, Irvine (main)
)
,
Kevin Greif
(
- UC, Irvine
)
,
Michael Fenton
(
- UC, Irvine
)
,
Aishik Ghosh
(
- UC, Irvine
)
,
Pierre Baldi
(
- UC, Irvine (main)
)

et al.

(May 17, 2023)

e-Print:
- 2305.10399 [hep-ex]

pdf

reference search35 citations

Gradient boosting MUST taggers for highly-boosted jets

J.A. Aguilar-Saavedra
(
- Madrid, IFT
)
,
E. Arganda
(
- Madrid, IFT and
- La Plata U.
)
,
F.R. Joaquim
(
- Lisbon, IST
)
,
R.M. Sandá Seoane
(
- Madrid, IFT
)
,
J.F. Seabra
(
- Madrid, IFT and
- Lisbon, IST
)

(May 8, 2023)

Published in:
- Eur.Phys.J.Plus 139 (2024) 11, 1019
•
e-Print:
- 2305.04957 [hep-ph]

DOI

reference search6 citations

Unbinned deep learning jet substructure measurement in high Q2ep collisions at HERA

Collaboration

•

V. Andreev
(
- Lebedev Inst.
)

et al.

(Mar 23, 2023)

Published in:
- Phys.Lett.B 844 (2023) 138101
•
e-Print:
- 2303.13620 [hep-ex]

pdfDOI

reference search23 citations

Unbinned profiled unfolding

Jay Chan
(
- Wisconsin U., Madison and
- LBNL, Berkeley
)
,
Benjamin Nachman
(
- LBNL, Berkeley and
- UC, Berkeley
)

(Feb 10, 2023)

Published in:
- Phys.Rev.D 108 (2023) 1, 016002
•
e-Print:
- 2302.05390 [hep-ph]

pdfDOI

reference search10 citations

An unfolding method based on conditional invertible neural networks (cINN) using iterative training

Mathias Backes
(
- Kirchhoff Inst. Phys.
)
,
Anja Butter
(
- LPNHE, Paris and
- U. Heidelberg, ITP
)
,
Monica Dunford
(
- Kirchhoff Inst. Phys.
)
,
Bogdan Malaescu
(
- LPNHE, Paris
)

(Dec 16, 2022)

Published in:
- SciPost Phys.Core 7 (2024) 1, 007
•
e-Print:
- 2212.08674 [hep-ph]

pdfDOI

reference search40 citations

Unbinned multivariate observables for global SMEFT analyses from machine learning

Raquel Gomez Ambrosio
(
- Milan Bicocca U.
)
,
Jaco ter Hoeve
(
- Vrije U., Amsterdam and
- NIKHEF, Amsterdam
)
,
Maeve Madigan
(
- Cambridge U., DAMTP
)
,
Juan Rojo
(
- Vrije U., Amsterdam and
- NIKHEF, Amsterdam
)
,
Veronica Sanz
(
- Valencia U., IFIC and
- Sussex U.
)

(Nov 3, 2022)

Published in:
- JHEP 03 (2023) 033
•
e-Print:
- 2211.02058 [hep-ph]

DOI

reference search23 citations

Measurement of the differential

\hbox {t}\overline{\hbox {t}}

production cross section as a function of the jet mass and extraction of the top quark mass in hadronic decays of boosted top quarks

#10

Collaboration

•

Armen Tumasyan
(
- Yerevan Phys. Inst. and
- Yerevan State U.
)

et al.

(Nov 2, 2022)

Published in:
- Eur.Phys.J.C 83 (2023) 7, 560
•
e-Print:
- 2211.01456 [hep-ex]

DOIdatasets

reference search32 citations

Multidifferential study of identified charged hadron distributions in

Z

-tagged jets in proton-proton collisions at

\sqrt{s}=

13 TeV

#11

LHCb

Collaboration

•

Roel Aaij
(
- Nikhef, Amsterdam
)

et al.

(Aug 24, 2022)

Published in:
- Phys.Rev.D 108 (2023) L031103
•
e-Print:
- 2208.11691 [hep-ex]

DOI

reference search28 citations

Disentangling quarks and gluons in CMS open data

#12

Patrick T. Komiske
(
- MIT, Cambridge, CTP and
- IAIFI, Cambridge
)
,
Serhii Kryhin
(
- MIT, Cambridge, CTP and
- IAIFI, Cambridge
)
,
Jesse Thaler
(
- MIT, Cambridge, CTP and
- IAIFI, Cambridge
)

(May 9, 2022)

Published in:
- Phys.Rev.D 106 (2022) 9, 094021
•
e-Print:
- 2205.04459 [hep-ph]

pdfDOI

reference search26 citations

Optimizing observables with machine learning for better unfolding

#13

Miguel Arratia
(
- UC, Riverside and
- Jefferson Lab
)
,
Daniel Britzger
(
- Munich, Max Planck Inst.
)
,
Owen Long
(
- UC, Riverside
)
,
Benjamin Nachman
(
- LBNL, Berkeley and
- Sao Paulo, IFT and
- UC, Berkeley
)

(Mar 30, 2022)

Published in:
- JINST 17 (2022) 07, P07009
•
e-Print:
- 2203.16722 [hep-ex]

DOI

reference search9 citations

Event generators for high-energy physics experiments

#14

J.M. Campbell
(
- Fermilab
)
,
M. Diefenthaler
(
- Jefferson Lab
)
,
T.J. Hobbs
(
- Fermilab and
- IIT, Chicago
)
,
Stefan Höche
(
- Fermilab
)
,
Joshua Isaacson
(
- Fermilab
)

et al.

(Mar 21, 2022)

Published in:
- SciPost Phys. 16 (2024) 5, 130
•
Contribution to:
- Snowmass 2021
•
e-Print:
- 2203.11110 [hep-ph]

DOI

reference search127 citations

neos: End-to-End-Optimised Summary Statistics for High Energy Physics

#15

Nathan Simpson
(
- Lund U.
)
,
Lukas Heinrich
(
- Munich, Tech. U.
)

(Mar 10, 2022)

Published in:
- J.Phys.Conf.Ser. 2438 (2023) 1, 012105
•
Contribution to:
- ACAT 2021
  ,
- ACAT 2021
•
e-Print:
- 2203.05570 [physics.data-an]

reference search22 citations

Reconstructing the kinematics of deep inelastic scattering with deep learning

#16

Miguel Arratia
(
- UC, Riverside and
- Jefferson Lab
)
,
Daniel Britzger
(
- Munich, Max Planck Inst.
)
,
Owen Long
(
- UC, Riverside
)
,
Benjamin Nachman
(
- LBL, Berkeley and
- UC, Berkeley (main)
)

(Oct 11, 2021)

Published in:
- Nucl.Instrum.Meth.A 1025 (2022) 166164
•
e-Print:
- 2110.05505 [hep-ex]

pdfDOI

reference search24 citations

Publishing unbinned differential cross section results

#17

Miguel Arratia
(
- UC, Riverside and
- Jefferson Lab
)
,
Anja Butter
(
- U. Heidelberg, ITP
)
,
Mario Campanelli
(
- University Coll. London
)
,
Vincent Croft
(
- Pennsylvania U.
)
,
Dag Gillberg
(
- Ottawa Carleton Inst. Phys.
)

et al.

(Sep 27, 2021)

Published in:
- JINST 17 (2022) 01, P01024
•
e-Print:
- 2109.13243 [hep-ph]

pdfDOI

reference search39 citations

The path to proton structure at 1% accuracy

#18

NNPDF

Collaboration

•

Richard D. Ball
(
- U. Edinburgh, Higgs Ctr. Theor. Phys.
)

et al.

(Sep 6, 2021)

Published in:
- Eur.Phys.J.C 82 (2022) 5, 428
•
e-Print:
- 2109.02653 [hep-ph]

DOI

reference search451 citations

Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

#19

Collaboration

•

V. Andreev
(
- LPI, Moscow (main)
)

et al.

(Aug 27, 2021)

Published in:
- Phys.Rev.Lett. 128 (2022) 13, 132002
•
e-Print:
- 2108.12376 [hep-ex]

pdfDOI

reference search70 citations

Preservation through modernisation: The software of the H1 experiment at HERA

#20

Collaboration

•

Daniel Britzger
(
- Munich, Max Planck Inst.
)

et al.

(Jun 21, 2021)

Published in:
- EPJ Web Conf. 251 (2021) 03004
•
Contribution to:
- vCHEP2021
  ,
- vCHEP2021
•
e-Print:
- 2106.11058 [hep-ex]

DOI

reference search11 citations

Uncertainty-aware machine learning for high energy physics

#21

Aishik Ghosh
(
- UC, Irvine and
- LBL, Berkeley
)
,
Benjamin Nachman
(
- LBL, Berkeley and
- UC, Berkeley, Miller Inst.
)
,
Daniel Whiteson
(
- UC, Irvine
)

(May 18, 2021)

Published in:
- Phys.Rev.D 104 (2021) 5, 056026
•
e-Print:
- 2105.08742 [physics.data-an]

pdfDOI

reference search47 citations

Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution

#22

Anders Andreassen
(
- Unlisted
)
,
Patrick T. Komiske
(
- IAIFI, Cambridge and
- MIT
)
,
Eric M. Metodiev
(
- IAIFI, Cambridge and
- MIT
)
,
Benjamin Nachman
(
- LBL, Berkeley
)
,
Adi Suresh
(
- UC, Berkeley
)

et al.

(May 10, 2021)

Contribution to:
- ICLR 2021
•
e-Print:
- 2105.04448 [stat.ML]

pdf

reference search33 citations

Learning to simulate high energy particle collisions from unlabeled data

#23

(Jan 21, 2021)

Published in:
- Sci.Rep. 12 (2022) 7567
•
e-Print:
- 2101.08944 [hep-ph]

DOI

reference search57 citations

Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference

#24

(Nov 11, 2020)

e-Print:
- 2011.05836 [stat.ML]

pdf

reference search20 citations

Enhancing searches for resonances with machine learning and moment decomposition

#25

Ouail Kitouni
(
- MIT, LNS and
- IAIFI, Cambridge
)
,
Benjamin Nachman
(
- LBL, Berkeley
)
,
Constantin Weisser
(
- MIT, LNS and
- IAIFI, Cambridge
)
,
Mike Williams
(
- MIT, LNS and
- MIT and
- Monash U. and
- IAIFI, Cambridge
)

(Oct 19, 2020)

Published in:
- JHEP 04 (2021) 070,
- JHEP 21 (2020) 070
•
e-Print:
- 2010.09745 [hep-ph]

DOI

reference search24 citations

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