70 citations · 279 across the 13 of their papers we have counts for
13 papers
B-Jet Tagging with Retentive Networks: A Novel Approach and Comparative Study
Ayse Asu Guvenli, Bora Isildak
Identifying jets originating from bottom quarks is vital in collider experiments for new physics searches. This paper proposes a novel approach based on Retentive Networks (RetNet)…
Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
M. Aamir, G. Adamov, T. Adams +568
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…
Study of time and energy resolution of an ultra-compact sampling calorimeter (RADiCAL) module at EM shower maximum over the energy range 25 GeV E 150 GeV
Carlos Perez-Lara, James Wetzel, Ugur Akgun +36
The RADiCAL Collaboration is conducting R\&D on high performance electromagnetic (EM) calorimetry to address the challenges expected in future collider experiments under conditions…
CALPAGAN: Calorimetry for Particles using GANs
Ebru Simsek, Bora Isildak, Anil Dogru +3
In this study, a novel approach is demonstrated for converting calorimeter images from fast simulations to those akin to comprehensive full simulations, utilizing conditional Gener…
Investigating the Violation of Charge Parity Symmetry Through Top Quark Chromo-Electric Dipole Moments by Using Machine Learning Techniques
B. Işıldak, A. Hayreter, M. Hüdaverdi +4
There are a number of studies in the literature on search for Charge-Parity (CP) violating signals in top quark productions at the LHC. In most of these studies, ChromoMagnetic Dip…
FACET: A new long-lived particle detector in the very forward region of the CMS experiment
S. Cerci, D. Sunar Cerci, D. Lazic +28
We describe a proposal to add a set of very forward detectors to the CMS experiment for the high-luminosity era of the Large Hadron Collider to search for beyond the standard model…
Deconvolution of the High Energy Particle Physics Data with Machine Learning
Bora Işıldak, Alper Hayreter, Aidan R. Wiederhold
A method for correcting smearing effects using machine learning technique is presented. Compared to the standard deconvolution approaches in high energy particle physics, the metho…
"Higgs" Factory at the Greek-Turkish Border
Serkant Ali Çetin, Evangelos N. Gazis, Bora Işildak +7
We would like to propose the construction of the photon collider based "Higgs factory" in the coming years at the Greek-Turkish border, starting from its test facility with a high…
Dose rate effects in the radiation damage of the plastic scintillators of the CMS Hadron Endcap Calorimeter
HCAL collaboration
We present measurements of the reduction of light output by plastic scintillators irradiated in the CMS detector during the 8 TeV run of the Large Hadron Collider and show that the…
Search for lepton flavour violating decays of the Higgs boson to e tau and e mu in proton-proton collisions at sqrt(s) = 8 TeV
CMS Collaboration
A direct search for lepton flavour violating decays of the Higgs boson (H) in the H to e tau and H to e mu channels is described. The data sample used in the search was collected i…
Electromagnetic structure of charmed baryons in Lattice QCD
K. U. Can, G. Erkol, B. Isildak +2
As a continuation of our recent work on the electromagnetic properties of the doubly charmed baryon, we compute the charge radii and the magnetic moments of the singly cha…
Measurement of the differential dijet production cross section in proton-proton collisions at \sqrt{s} = 7 tev
Bora Isildak
A measurement of the double-differential inclusive dijet production cross section in proton-proton collisions at \sqrt{s}= 7 TeV is presented as a function of the dijet invariant m…
Electromagnetic properties of doubly charmed baryons in Lattice QCD
K. U. Can, G. Erkol, B. Isildak +2
We compute the electromagnetic properties of Ξ_cc baryons in 2+1 flavor Lattice QCD. By measuring the electric charge and magnetic form factors of Ξ_cc baryons, we extract the magn…