Software Simulation of Electronics Readout Chain for the Silicon Vertex Tracker Department of Physics, University of New Hampshire, Durham, NH, Daniel Mannarino and Kyle Snavely Advised by Maurik Holtrop and Sarah Phillips Jefferson Laboratory will soon upgrade the capabilities of their particle accelerator from 6 GeV to 12 GeV. This necessitates the building and testing of new particle detectors to take advantage of the new opportunities to produce scientific data. Our research for the last year has primarily been focused on the software simulation of one of these detector systems, the Silicon Vertex Tracker. (SVT) The SVT is one of many detectors being developed for the CLAS12 (CEBAF Large Acceptance Spectrometer) assembly at Hall B in Jefferson Laboratory. (See Fig. 1.) Finally, we have been busy preparing a laboratory for the Nuclear Physics Group to test prototypes of the SVT detector staves. The test facility we are constructing will include a light-tight box to house a detector stave and a laser mounted on an articulating test stand. The laser, which will be able to move in the x, y, and z planes, will be used as a source in order to test the response of the detector to radiation. The entire assembly will need to be housed in a clean room in order to prevent contamination of the delicate silicon microstrip detectors. The results of testing will allow us to fine-tune our simulations, and at the same time our simulation may allow us to predict any interesting or problematic behaviour. These results will allow us to better analyze data from the SVT when it is built and used in the CLAS12 assembly. We would like to thank the following people for aiding us and answering our questions; we are very grateful for their help and guidance: Maurik Holtrop – University of New Hampshire Sarah Phillips – University of New Hampshire Maurizio Ungaro – University of Connecticut Samuel Meehan – University of New Hampshire Introduction Acknowledgements Figure 3. The unprocessed signal for a Kaon of energy 2 GeV incident normal to the detector as compared to a processed signal below.. Figure 2. Here are graphs of energy deposition versus the energy of the particle. The right graph shows the graph for Pions, the middle for Protons, and the left shows the two data sets superimposed As you can see, the signals of the Protons and the Pions are clearly distinguishable. Figure 4. Some of the newly purchased equipment we are testing. A good simulation will allow for the generation of realistic processed signals, which are essential for the testing of particle data reconstruction software. These signals will eventually be used to reconstruct the tracks of generated particles and for the analysis of potential problems in particle detection. The name of the software simulation we are working on is GEMC, for GEant 4 Monte Carlo. GEMC is written in C++, and uses the Geant4 toolkit to model the physical behavior of detectors, focusing on the CLAS12 assembly of detectors in Hall B at Jefferson Laboratory. We have previously made small feature additions to this code. Initially time was spent familiarizing ourselves with the existing codebase by reproducing some initial simulations done by the original author, Maurizio Ungaro. (See Fig. 2) We did this to become proficient with using Geant4 as a basis for our programs, and with using the ROOT data analysis framework to interpret the output. Software Simulation Our primary goal was to add realistic modeling of the SVT's signal processing electronics to GEMC. Currently, it uses Geant4 to determine the details of particle events based on probabilistic models. Modeling the behavior starting with the initial event, and the passage of the signal through the electronics toolchain would allow us to see something much closer to the data that will be produced by the real detector than the perfect list of particles, locations, and times provided by the current simulation in GEMC. In addition, we wanted to add the ability to simulate the introduction of noise of various types to the input. Eventually we found that implementing a simulation of the low level electronics was not possible within the existing GEMC framework. Our colleague, Samuel Meehan, was using code written by M. Mazziota [2], which contained a model for the electronics backend of a similar detector. His code simulates the electron/hole pair production in silicon semiconductor strips as a response to ionizing particles. It does so with a polynomial transfer function which approximates the behavior of a signal traveling through a circuit. We used this as our starting place and adapted the code to our own purposes, beginning by translating it from Fortran into C++. We are currently in the process of testing it and integrating it into GEMC. The bulk of the simulated electronics toolchain will be formed by using our new noise generation and pulse shaping code in conjunction with a body of example data Sam has generated for us. As can be seen in Figure 3, the electronics code dramatically improves the clarity of a signal. However, these graphs are implemented with a very minimalistic noise simulation. It is necessary to account for the many types of noise; it may originate within the detector itself, or in the electronics the detector is dependent on. Electronics Background The initial signal that is produced by a particle passing through the detector is not ideal for our purposes. In order to retrieve data about the actual physical process one is investigating, it is necessary to prepare the output signal for further processing and analysis. This may entail removing noise, dropping uninteresting events below a certain energy threshold, and shaping a pulse so it is fed to the next electronics stage in an optimal manner. Each component improves the quality of the signal before the Analog to Digital Converter (ADC) passes the signal's digital fingerprint to further digital logic components. The current design for the electronics calls for the FSSR2, or Fermilab Silicon Strip Readout Chip, to read-out the data from the detector. The FSSR2 features (among other components) an amplifier, shaper, baseline restorer, discriminator, and ADC. A preamplifier is necessary as the amount of charge coming from the SVT is very small – the original pulse contains only the electron/hole pairs generated by the ionizing particle. Next, the pulse shaper attenuates high and low frequencies in order to maximize the signal to noise ratio. Pulses must also be narrow enough to avoid piling them atop each other's decaying tails. The baseline restorer helps with this problem by quickly dropping decaying tales to a selectable level. Finally, the discriminator and ADC drop low amplitude signals and convert the analog signal into a digital one – storing information about the signal's amplitude without keeping the entire noisy signal itself. This data is further processed by software until multiple versions (differing by their amount of post-processing) are available for analysis, e.g. path reconstruction. Figure 1. A rendering of some of the components for the assembly in Hall B. The entire structure is immersed in a magnetic field; this alters the path of charged objects and allows further differentiation of particles. [1] Valerio Re et al, 2005, in 2005 IEEE Nuclear Science Symposium Conference Record, Volume: 2, p [2] M. Brigida et al., Nucl. Instr. and Meth. A 533 (2004), p Future Research Acknowledgements