Literature Search

23 results

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Fingerprinting New Physics with Effective Field Theories

Jongejan Jacobus ter Hoeve
(
- Vrije U., Amsterdam
)

(Jan 8, 2025)

reference search0 citations

Fingerprinting New Physics with Effective Field Theories

Jaco ter Hoeve

(Jan 8, 2025)

e-Print:
- 2501.08818 [hep-ph]

links

reference search0 citations

Constraints on standard model effective field theory for a Higgs boson produced in association with W or Z bosons in the H

\to\mathrm{b\bar{b}}

decay channel in proton-proton collisions at

\sqrt{s}

= 13 TeV

Collaboration

•

Vladimir Chekhovsky
(
- Yerevan Phys. Inst.
)

et al.

(Nov 25, 2024)

e-Print:
- 2411.16907 [hep-ex]

pdfdatasets

reference search3 citations

Hyperparameter Optimisation in Deep Learning from Ensemble Methods: Applications to Proton Structure

Juan Cruz-Martinez
(
- CERN
)
,
Aaron Jansen
(
- Netherlands eScience Center
)
,
Gijs van Oord
(
- Netherlands eScience Center
)
,
Tanjona R. Rabemananjara
(
- Vrije U., Amsterdam and
- NIKHEF, Amsterdam
)
,
Carlos M.R. Rocha
(
- Netherlands eScience Center
)

et al.

(Oct 21, 2024)

e-Print:
- 2410.16248 [hep-ph]

pdf

reference search1 citation

Advancing Tools for Simulation-Based Inference

Henning Bahl
(
- U. Heidelberg, ITP
)
,
Victor Bresó
(
- U. Heidelberg, ITP
)
,
Giovanni De Crescenzo
(
- U. Heidelberg, ITP
)
,
Tilman Plehn
(
- U. Heidelberg, ITP and
- U. Heidelberg (main)
)

(Oct 9, 2024)

e-Print:
- 2410.07315 [hep-ph]

pdf

reference search4 citations

Refinable modeling for unbinned SMEFT analyses

Robert Schöfbeck
(
- Vienna, OAW
)

(Jun 27, 2024)

Published in:
- Mach.Learn.Sci.Tech. 6 (2025) 1, 015007,
- Mach.Learn.Sci.Tech. 6 (2025) 015007
•
e-Print:
- 2406.19076 [hep-ph]

DOI

reference search2 citations

Constraining the Higgs potential with neural simulation-based inference for di-Higgs production

Radha Mastandrea
(
- UC, Berkeley and
- LBNL, Berkeley and
- Sao Paulo, IFT
)
,
Benjamin Nachman
(
- LBNL, Berkeley and
- Sao Paulo, IFT and
- UC, Berkeley
)
,
Tilman Plehn
(
- U. Heidelberg, ITP and
- U. Heidelberg (main)
)

(May 24, 2024)

Published in:
- Phys.Rev.D 110 (2024) 5, 056004
•
e-Print:
- 2405.15847 [hep-ph]

pdfDOI

reference search3 citations

Equivariant neural networks for robust

C P

observables

Sergio Sánchez Cruz
(
- CERN
)
,
Marina Kolosova
(
- U. Florida, Gainesville (main)
)
,
Clara Ramón Álvarez
(
- ICTEA, Oviedo
)
,
Giovanni Petrucciani
(
- CERN
)
,
Pietro Vischia
(
- ICTEA, Oviedo
)

(May 22, 2024)

Published in:
- Phys.Rev.D 110 (2024) 9, 096023
•
e-Print:
- 2405.13524 [hep-ph]

DOI

reference search0 citations

Mapping the SMEFT at high-energy colliders: from LEP and the (HL-)LHC to the FCC-ee

Eugenia Celada
(
- Manchester U.
)
,
Tommaso Giani
(
- NIKHEF, Amsterdam and
- Vrije U., Amsterdam
)
,
Jaco ter Hoeve
(
- NIKHEF, Amsterdam and
- Vrije U., Amsterdam
)
,
Luca Mantani
(
- Cambridge U., DAMTP
)
,
Juan Rojo
(
- NIKHEF, Amsterdam and
- Vrije U., Amsterdam
)

et al.

(Apr 19, 2024)

Published in:
- JHEP 09 (2024) 091
•
e-Print:
- 2404.12809 [hep-ph]

DOI

reference search46 citations

SIMUnet: an open-source tool for simultaneous global fits of EFT Wilson coefficients and PDFs

#10

PBSP

Collaboration

•

Mark N. Costantini
(
- Cambridge U., DAMTP
)

et al.

(Feb 5, 2024)

Published in:
- Eur.Phys.J.C 84 (2024) 8, 805
•
e-Print:
- 2402.03308 [hep-ph]

DOI

reference search15 citations

Rotation-equivariant graph neural network for learning hadronic SMEFT effects

#11

(Jan 18, 2024)

Published in:
- Phys.Rev.D 109 (2024) 7, 076012
•
e-Print:
- 2401.10323 [hep-ph]

pdfDOI

reference search4 citations

From optimal observables to machine learning: an effective-field-theory analysis of e

^{+}

^{−}

→ W

^{+}

^{−}

at future lepton colliders

#12

Shengdu Chai
(
- Fudan U. and
- Shanghai, Astron. Observ.
)
,
Jiayin Gu
(
- Fudan U. and
- Shanghai, Astron. Observ.
)
,
Lingfeng Li
(
- Brown U.
)

(Jan 4, 2024)

Published in:
- JHEP 05 (2024) 292
•
e-Print:
- 2401.02474 [hep-ph]

DOI

reference search4 citations

Constraints on standard model effective field theory effects with Higgs bosons produced in association with W or Z bosons in the H

\rightarrow

\mathrm{\bar{b}}

decay channel in proton-proton collisions at

\sqrt{s}=13~\mathrm{TeV}

#13

Collaboration

(2024)

reference search0 citations

Interpretable deep learning models for the inference and classification of LHC data

#14

(Dec 14, 2023)

Published in:
- JHEP 05 (2024) 004
•
e-Print:
- 2312.12330 [hep-ph]

DOI

reference search7 citations

Combining chromomagnetic and four-fermion operators with leading SMEFT operators for gg → hh at NLO QCD

#15

Gudrun Heinrich
(
- KIT, Karlsruhe, TP
)
,
Jannis Lang
(
- KIT, Karlsruhe, TP
)

(Nov 25, 2023)

Published in:
- JHEP 05 (2024) 121
•
e-Print:
- 2311.15004 [hep-ph]

DOI

reference search18 citations

Designing observables for measurements with deep learning

#16

Owen Long
(
- UC, Riverside
)
,
Benjamin Nachman
(
- LBNL, Berkeley and
- Sao Paulo, IFT and
- UC, Berkeley
)

(Oct 12, 2023)

Published in:
- Eur.Phys.J.C 84 (2024) 8, 776
•
e-Print:
- 2310.08717 [physics.data-an]

DOI

reference search0 citations

Boosting likelihood learning with event reweighting

#17

Siyu Chen
(
- ITPP, Lausanne
)
,
Alfredo Glioti
(
- IPhT, Saclay
)
,
Giuliano Panico
(
- Florence U. and
- INFN, Florence
)
,
Andrea Wulzer
(
- Barcelona, IFAE and
- ICREA, Barcelona and
- Barcelona, Autonoma U.
)

(Aug 10, 2023)

Published in:
- JHEP 03 (2024) 117
•
e-Print:
- 2308.05704 [hep-ph]

DOI

reference search8 citations

Hadronic Jets: flavour and substructure

#18

Simone Caletti
(
- Genoa U.
)

(Apr 12, 2023)

DOI

reference search0 citations

The top quark legacy of the LHC Run II for PDF and SMEFT analyses

#19

Zahari Kassabov
(
- Cambridge U., DAMTP
)
,
Maeve Madigan
(
- Cambridge U., DAMTP
)
,
Luca Mantani
(
- Cambridge U., DAMTP
)
,
James Moore
(
- Cambridge U., DAMTP
)
,
Manuel Morales Alvarado
(
- Cambridge U., DAMTP
)

et al.

(Mar 10, 2023)

Published in:
- JHEP 05 (2023) 205
•
e-Print:
- 2303.06159 [hep-ph]

DOI

reference search48 citations

SMEFiT: a flexible toolbox for global interpretations of particle physics data with effective field theories

#20

Tommaso Giani
(
- Vrije U., Amsterdam and
- Nikhef, Amsterdam
)
,
Giacomo Magni
(
- Vrije U., Amsterdam and
- Nikhef, Amsterdam
)
,
Juan Rojo
(
- Vrije U., Amsterdam and
- Nikhef, Amsterdam
)

(Feb 13, 2023)

Published in:
- Eur.Phys.J.C 83 (2023) 5, 393
•
e-Print:
- 2302.06660 [hep-ph]

DOI

reference search28 citations

Double insertions of SMEFT operators in gluon fusion Higgs boson production

#21

(Dec 6, 2022)

Published in:
- Phys.Rev.D 107 (2023) 5, 055038
•
e-Print:
- 2212.03258 [hep-ph]

pdfDOI

reference search24 citations

Machine-learned exclusion limits without binning

#22

Ernesto Arganda
(
- Madrid, IFT and
- La Plata U.
)
,
Andres D. Perez
(
- La Plata U.
)
,
Martin de los Rios
(
- Madrid, IFT and
- Madrid, Autonoma U.
)
,
Rosa María Sandá Seoane
(
- Madrid, IFT
)

(Nov 9, 2022)

Published in:
- Eur.Phys.J.C 83 (2023) 12, 1158
•
e-Print:
- 2211.04806 [hep-ph]

DOI

reference search9 citations

Simultaneous CTEQ-TEA extraction of PDFs and SMEFT parameters from jet and

t\overline{t}

data

#23

Jun Gao
(
- Shanghai Jiao Tong U. and
- Shanghai Jiaotong U.
)
,
MeiSen Gao
(
- Shanghai Jiao Tong U. and
- Shanghai Jiaotong U.
)
,
T.J. Hobbs
(
- Argonne
)
,
DianYu Liu
(
- Shanghai Jiao Tong U. and
- Shanghai Jiaotong U.
)
,
XiaoMin Shen
(
- Shanghai Jiao Tong U. and
- Shanghai Jiaotong U.
)

(Nov 2, 2022)

Published in:
- JHEP 05 (2023) 003
•
e-Print:
- 2211.01094 [hep-ph]

DOI

reference search27 citations

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