Phd (PHD)

Forward Tracker (FT) developed for the PANDA - HADES experiments, will be used for tracking and identification of charged particles in the forward regions by measuring the drift-time and the energy loss with the Time Over Threshold (TOT) method of the track. In the thesis, the methods required to achieve the energy and position resolution for the tracker are developed and evaluated in two stages. In the first stage, the detector and readout calibration methods are developed to endow uniform gain characteristics from a large number of detector channels. These methods are also used for the qualification of PASTTRECv3 ASIC (PANDA Straw Tube Tracker REadout Chip, Application Specific Integrated Circuit) developed for the FT. The obtained calibration parameters are validated by tracking the performance of prototypes of straw tubes under realistic beam conditions inside the HADES
experiment and prototypes of the PANDA detectors. In the second stage, a Data AcQuisition (DAQ) system performing online event selection, filtering and particle track reconstruction on FPGA-based hardware has been developed and evaluated in experiments using proton beams and cosmic rays.
The application of online event processing in FT will accelerate event processing and introduce data reduction, which is one of the components of the DAQ system in the PANDA experiment. The FT detector setup and the DAQ have been integrated for the HADES experiment and the successful operation of the detector in the full system run has confirmed the effectiveness of the developed methods.

Up until now, elementary particles and their interactions have been satisfactorily characterised by the Standard Model (SM) of particle physics. But a lot of difficult questions remain unanswered. At high energy frontiers like the LHC at CERN, some of these are being researched. The high precision/high intensity frontier made possible by exclusive observations of hadronic reactions at intermediate energies offers an alternative strategy. The upcoming antiProton ANnihilation at DArmstadt (PANDA) experiment at FAIR will utilise antiproton-nucleus and antiproton-proton interactions as diagnostic tools. The PANDA experiment may be used to analyse the spectra of many different particles. Z(4430) is among the most significant of the many XYZ states and they are being examined in numerous global experiments, such as BESIII, Belle, BaBaR, and LHCb. Therefore, integrating this research into the PANDA framework and utilising PANDA software to work with this subject is a crucial challenge for the PANDA experiment pertaining to charmonium and exotics. Z(4430) can potentially provide more precise information on mass, width, and other parameters in the PANDA detector spectrum when the entire simulation offered by the PANDA software chain is utilised. To test this, the thesis study titled "Feasibility Study of Z(4430) Exotic State at PANDA Experiment" was designed with the aim of determine whether Z(4430) is feasible in the PANDA detector spectrum. Consequently, according to the results of this study, Z(4430) is shown to be observable in the framework of the PANDA experiment.

The PANDA (antiProton ANnihilation at DArmstadt) experiment aims to investigate
the strong interaction using an antiproton beam and a stationary cluster jet
target, resulting in annihilation reactions. The Micro-Vertex Detector (MVD) is the
innermost detector among PANDA’s sub-detectors and is positioned closest to
the interaction point. It is designed for precise vertex and tracking detection, employing
double-sided silicon strip and silicon pixel detectors. In conjunction with
other sub-detector systems, PANDA is capable of particle tracking, identification,
and calorimetry. In addition to PANDA, further applications of the MVD as well
as the use of silicon strip sensors in different configurations are being discussed.
The double-sided silicon strip detectors allow high-precision spatial resolution,
but require stringent compliance with specifications. Sensor characterization and
detailed quality checks are conducted, including irradiation with protons at the
Marburg Ion Beam Therapy Center (MIT) to assess radiation damage. The signal
behavior of the sensors is investigated during the development of amplification
stages and prepared for a sub-experiment for dosimetry on a femto satellite in
Low Earth Orbit (LEO).
For the sensor readout in the MVD, an ASIC named ToASt (Torino Amplifier for
Silicon Strip Detectors) was developed at INFN Turin and was connected to the
sensors for the first time via wire bonding. The ASIC offers the advantage of
determining both the event time stamp and the energy deposited in the sensor
using the Time-over-Threshold and Time-of-Arrival methods. Combining the
ToASt-Sensor combination with the MDC (Module Data Concentrator) ASIC
developed at KIT forms the first fully functional detector module. A combination
of two of these modules was tested at the proton beam of the COSY facility in Jülich.
Data obtained from beam tests and laboratory tests with sources are analyzed
to demonstrate the functionality of the prototype and perform characterization.
Important data have been collected to enable the development of the second
prototype and to advance the construction and functionality of the MVD.

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.

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.