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Detector software

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Workshop Proton Beams at SIS100

Workshop „Physics Opportunities with Proton Beams at SIS100” was held in Wuppertal

Physicist of the week

Meike Küßner is DPG female physicist of calendar week 30 in 2023!

Endcap travel

Forward Endcap travels to Jülich

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PANDA meetings


04/11-06/11 2024 CM 24/3 at GSI
05/03-07/03 2025 WS at GSI
24/03/2025 16.00 CM 25-ZOOM1
13/05/2025 16.00 CM 25-ZOOM2
16/06-18/06 2025 CM 25/1 at GSI
24/11-26/11 2025 CM25/2 at GSI

Upcoming events

RICH2025 - XII International Workshop on Ring Imaging Cherenkov Detectors
15 September, 2025 - 19 September, 2025
DRD1 Gaseous Detectors School 2025
17 September, 2025 - 24 September, 2025
7th international workshop on new Photon-Detectors (PD2025)
3 December, 2025 - 5 December, 2025

 

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E.g. simulation of detector components

Beschleunigung eines Spurfindealgorithmus für den Straw Tube Tracker des PANDA-Detektors durch Parallelisierung mit CUDA C
Jette Schumann
TH-MAS-2015-011.pdf (7.32 MB)
Thesis
Master (MAS)
Detector software
Wednesday, September 30, 2015 - 12:00
TH-MAS-2015-011: Beschleunigung eines Spurfindealgorithmus für den Straw Tube T…
Entwicklung eines schnellen Alogrithmus zur Suche von Teilchenspuren im "Straw Tube Tracker" des PANDA-Detektors
Jette Schumann
TH-BAC-2013-010.pdf (4.81 MB)
Thesis
Bachelor (BAC)
Detector software
Thursday, August 15, 2013 - 12:00
TH-BAC-2013-010: Entwicklung eines schnellen Alogrithmus zur Suche von Teilchen…
PANDA Annual Report 2023
K. Peters
k.peters
RE-PRO-2024-001.pdf (14.66 MB)
Report
Progress Report (PRO)
Detector hardware
Detector software
Physics analysis
Monday, June 24, 2024 - 12:00
PANDA Annual Report 2023
RE-PRO-2024-001: PANDA Annual Report 2023
Studying the hadron structure with PANDA and CLAS using machine learning techniques
Aron Kripko
a.kripko
PANDOC-3402-Thesis-2024-20250312_164918.pdf (20.8 MB)
Thesis
Phd (PHD)
Detector software
Physics analysis
Friday, February 16, 2024 - 12:00
The hadron spectroscopy and structure are currently very active fields of research to study the non-perturbative regime of quantum chronodynamics. The first one studies the complex structure of excited hadrons by looking at their decay products, while the latter uses lepton scattering on nucleons. Both methods require reconstruction algorithms with great efficiency and good particle identification and background rejection rates. This work aims to provide these by either improving the existing methods or developing new ones.

The first part of this document presents a feasibility study of a predicted hybrid charmonium state for the $\mathrm{\overline{P}}$ANDA experiment. Lattice QCD calculations predict the ground state hybrid charmonium to be a spin exotic with quantum numbers of $J^{PC}=1^{-+}$ at a mass of around 4.3 GeV with a width to be around 20 MeV. A machine learning based data analysis scheme is proposed to further improve the signal efficiency and the background reduction, alongside with improvements of the analysis software (PandaRoot), that are vital for this study. These improvements include a reworked clustering algorithm for the electromagnetic calorimeter (EMC) and an optimized monte carlo matching for neutral particles.

The second part of this document is about studying the proton structure. A multidimensional study of the structure function ratio $\mathrm{F_{LU}^{sin(\phi)}/F_{UU}}$ has been performed for K$^\mathrm{\pm}$, based on the measurement of beam-spin asymmetries. It uses the high statistics data recorded with the CLAS12 spectrometer at Jefferson Laboratory. $\mathrm{F_{LU}^{sin(\phi)}}$ is a twist-3 quantity that provides information about the quark gluon correlations in the proton. This document will present for the first time a simultaneous analysis of two kaon channels over a large kinematic range of $z$, $x_B$, $P_T$ and $Q^2$ with virtualities $Q^2$ ranging from 1 GeV$^2$ up to 8 GeV$^2$ using machine learning techniques for improved particle identification.
TH-PHD-2024-001: Studying the hadron structure with PANDA and CLAS using machin…
4D Track Reconstruction on Free-Streaming Data at PANDA at FAIR
Jenny Taylor, Michael Papenbrock, Tobias Stockmanns, Ralf Kliemt, Tord Johansson, Adeel Akram, Karin Schönning
PA-JOU-2024-001.pdf (2.71 MB)
Paper
Journal (JOU)
Detector software
Thursday, January 11, 2024 - 12:00
A new generation of experiments is being developed, where the challenge of separating rare signal processes from background at high intensities requires a change
of trigger paradigm. At the future PANDA experiment at FAIR, hardware triggers will be abandoned and instead a purely software-based system will be used.
This requires novel reconstruction methods with the ability to process data from
many events simultaneously.
A 4D tracking algorithm based on the cellular automaton has been developed which will utilize the timing information from detector signals. Simulation studies
have been performed to test its performance on the foreseen free-streaming data from the PANDA detector. For this purpose, a quality assurance procedure for
tracking on free-streaming data was implemented in the PANDA software. The studies show that at higher interaction rates, 4D tracking performs better than
the 3D algorithm in terms of efficiency, 84% compared to 77%. The fake track suppression is also greatly improved, compared to the 3D tracking with roughly
a 50% decrease in the ghost rate.
PA-JOU-2024-001: 4D Track Reconstruction on Free-Streaming Data at PANDA at FAIR
Read-out and online processing for the Forward Tracker in HADES and PANDA
Akshay Malige
TH-PHD-2023-003.pdf (10.77 MB)
Thesis
Phd (PHD)
Detector hardware
Detector software
Friday, November 3, 2023 - 12:00
TH-PHD-2023-003: Read-out and online processing for the Forward Tracker in HADE…
Towards Realistic Hyperon Reconstruction in PANDA: From Tracking with Machine Learning to Interactions with Residual Gas
Adeel Akram
a.akram
TH-PHD-2023-002.pdf (5.51 MB)
Thesis
Phd (PHD)
Detector software
Friday, May 19, 2023 - 12:00
The PANDA (anti-Proton ANnihilation at DArmstadt) experiment at FAIR (Facility for Anti-proton and Ion Research) aims to study strong interactions in the confinement domain. In PANDA, a continuous beam of anti-protons will impinge on a fixed hydrogen target inside the High Energy Storage Ring (HESR), a feature intended to attain high interaction rates for various physics studies e.g. hyperon production.

This thesis addresses the challenges of running PANDA under realistic conditions. The focus is two-fold: developing deep learning methods to reconstruct particle trajectories and reconstruct hyperons using realistic target profiles. Two approaches are used: (i) standard deep learning model such as dense network, and (ii) geometric deep leaning model such as interaction graph neural networks. The deep learning methods have given promising results, especially when it comes to (i) reconstruction of low-momentum particles that frequently occur in hadron physics experiments and (ii) reconstruction of tracks originating far from the interaction point. Both points are critical in many hyperon studies. However, further studies are needed to mitigate e.g. high clone rate. For the realistic target profiles, these pioneering simulations address the effect of residual gas on hyperon reconstruction. The results have shown that the signal-to-background ratio becomes worse by about a factor of 2 compared to the ideal target, however, the background level is still sufficiently low for these studies to be feasible. Further improvements can be made on the target side to achieve a better vacuum in the beam pipe and on the analysis side to improve the event selection.

Finally, solutions are suggested to improve results, especially for the geometric deep learning method in handling low-momentum particles contributing to the high clone rate. In addition, a better way to build ground truth can improve the performance of our approach.
TH-PHD-2023-002: Towards Realistic Hyperon Reconstruction in PANDA: From Tracki…
Development of fast track finding algorithms for densely packed straw tube trackers and its application to Xi(1820) hyperon reconstruction for the PANDA experiment
Anna Alicke
a.scholl@fz-juelich.de
TH-PHD-2023-001.pdf (26.61 MB)
Thesis
Phd (PHD)
Detector software
Tuesday, June 13, 2023 - 12:00
TH-PHD-2023-001: Development of fast track finding algorithms for densely packe…
Build & Deployment of the PANDA DCS system
Florian Feldbauer
f.feldbauer
TA-CON-2022-034.pdf (4.76 MB)
Talk
Conference (CON)
EPICS Collaboration Meeting 2022
Detector software
Tuesday, September 20, 2022 - 12:00
Presentation of the build & deployment mechanisms forseen for the DCS software system within PANDA at the Build and Deployment Workshop at the EPICS Collaboration Meeting.
TA-CON-2022-034: Build & Deployment of the PANDA DCS system
Development of software alignment algorithms and optimization of the luminosity extraction via alignment of the PANDA luminosity detector
Roman Klasen
klasen
TH-PHD-2021-003.pdf (12.31 MB)
Thesis
Phd (PHD)
Detector software
Thursday, September 30, 2021 - 12:00
TH-PHD-2021-003: Development of software alignment algorithms and optimization …
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