On the kinematic reconstruction of deep inelastic scattering at HERA

doi:10.1016/0168-9002(95)00173-5

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Volume 361, Issues 1–2, 1 July 1995, Pages 197-208

https://doi.org/10.1016/0168-9002(95)00173-5 Get rights and content

Abstract

We review and compare the reconstruction methods of the inclusive deep inelastic scattering variables used at HERA. We introduce a new prescription, the sigma (Σ) method, which allows to measure the structure function of the proton F₂(x, Q²) in a large kinematic domain, and in particular in the low x-lowQ² region, with small systematic errors and small radiative corrections. A detailed comparison between the Σ method and the other methods is shown. Extensions of the Σ method are presented. The effect of QED radiation on the kinematic reconstruction and on the structure function measurement is discussed.

References (27)

I Abt
Nucl. Phys. B
(1993)
T Ahmed
Phys. Lett. B
(1993)
M Derrick
Z. Phys. C
(1993)
J Feltesse
A Blondel et al.
S Bentvelsen
C Hoeger
G Bernardi et al.
J Blümlein et al.
U Bassler

V Brisson

LAL preprint 94-61

(1994)

V Brisson

G.A Schuler et al.

A Kwiatkowski et al.

Cited by (106)

Unbinned deep learning jet substructure measurement in high Q<sup>2</sup> ep collisions at HERA
2023, Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics
The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of the complications present at hadron colliders are absent. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. All of the available reconstructed object information of the respective jets is interpreted by a graph neural network, achieving superior precision on a selected set of jet angularities. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the $k_{T}$ jet clustering algorithm. Results are reported at high transverse momentum transfer $Q^{2} > 150 {GeV}^{2}$ , and inelasticity $0.2 < y < 0.7$ . The analysis is also performed in sub-regions of $Q^{2}$ , thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.
Reconstructing the kinematics of deep inelastic scattering with deep learning
2022, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
We introduce a method to reconstruct the kinematics of neutral-current deep inelastic scattering (DIS) using a deep neural network (DNN). Unlike traditional methods, it exploits the full kinematic information of both the scattered electron and the hadronic-final state, and it accounts for QED radiation by identifying events with radiated photons and event-level momentum imbalance. The method is studied with simulated events at HERA and the future Electron–Ion Collider (EIC). We show that the DNN method outperforms all the traditional methods over the full phase space, improving resolution and reducing bias. Our method has the potential to extend the kinematic reach of future experiments at the EIC, and thus their discovery potential in polarized and nuclear DIS.
Multi-differential Jet Substructure Measurement in High Q<sup>2</sup> ep collisions with HERA-II Data
2024, Proceedings of Science
Measurement of the 1-jettiness event shape observable in deep-inelastic electron-proton scattering at HERA
2024, arXiv
Measurement of groomed event shape observables in deep-inelastic electron-proton scattering at HERA
2024, arXiv
Observation and differential cross section measurement of neutral current DIS events with an empty hemisphere in the Breit frame
2024, arXiv

View all citing articles on Scopus

View full text

On the kinematic reconstruction of deep inelastic scattering at HERA

Abstract

Nucl. Phys. B

Phys. Lett. B

Z. Phys. C

LAL preprint 94-61