Private:Student Projects

Project 1

PDF for dark scalar boson       (Click "Expand" to the right for more details -->):

• Determine the Probability Density Function (PDF) of the dark scalar gauge boson, S, for the process gamma proton -> eta + proton, eta -> S + pi0, S -> gamma gamma. Since the hypothetical S mass is unknown, the PDF has to be determined for all masses between ~ a few MeV/c^2 and ~ 420 MeV/c^2 scannable by JEF. This can be done in 3 steps:

1. Determine PDF for fixed masses from histograms I will provide
2. Parametrize the PDF vs mass and possibly vs incident photon-beam energy
3. Toy Monte Carlo simulation study to show that the model is not introducing biases for our observables#:
   

Jared G. Richards report

Project 2

Island Algorithm       (Click "Expand" to the right for more details -->):

• Use Simon's and Igal's work to test the GAMS Island algorithm. Steps:

1. Grab the farm version (also exists on a GitHub branch: https://github.com/JeffersonLab/halld_recon/tree/FCALIsland)
2. Use Igal's environment and build scripts.
3. Use factory flag/tag to change clustering algorithms on the command line (or in config file): DEFTAG:DFCALCluster=Island
4. Merge/convert with Jon's code.
5. Run photon guns through MCWRAPPER, to see single photon, and two-photon hits.
6. Check upstream conversions in TOF/DIRC.
7. Check average no of reconstructed clusters. Extract 'resolving power' of FCAL-I and FCAL-II eventually.
8. Stitch boundary between insert and outer blocks.
9. Vaildate with data? Use omega skims for FCAL-II / COMCAL is subtends too small of an angle

Project 3

Background suppression via MVA (eta -> pi^0 gamma gamma)       (Click "Expand" to the right for more details -->):

Study of the process gamma + proton -> eta + proton [1], eta -> pi^0 gamma gamma , and pi^0 -> gamma gamma; and in particular background suppression via multivariate analysis (MVA) using the Fisher discriminant [2] method
in the TMVA [3] package.

[1]G.Liping et al, Precision tests of fundamental physics with η\etaη and η′\eta^\primeη′ mesons, [arXiv:2007.00664]

[2]R. A. Fisher, The use of multiple measurements in taxonomic problems, Annals Eugen.7(1936) 179.

[3]H. Voss, A. Hocker, J. Stelzer and F. Tegenfeldt,TMVA - Toolkit for Multivariate DataAnalysis, PoS ACAT (2007) 040 [arXiv:physics/0703039]

Chase W. Peterson talk & report

Project 4

Background suppression via MVA (eta -> pi^0 e^+ e^-)       (Click "Expand" to the right for more details -->):

Study of the process gamma + proton -> eta + proton [1], eta -> pi^0 e^+ e^- , and pi^0 -> gamma gamma; and in particular background suppression via multivariate analysis (MVA) using the Fisher discriminant [2] method
in the TMVA [3] package.

[1]G.Liping et al, Precision tests of fundamental physics with η\etaη and η′\eta^\primeη′ mesons, [arXiv:2007.00664]

[2]R. A. Fisher, The use of multiple measurements in taxonomic problems, Annals Eugen.7(1936) 179.

[3]H. Voss, A. Hocker, J. Stelzer and F. Tegenfeldt,TMVA - Toolkit for Multivariate DataAnalysis, PoS ACAT (2007) 040 [arXiv:physics/0703039]

Project 5

Classification methods optimizable for unknown cross-sections and particle masses.       (Click "Expand" to the right for more details -->):

Search for dark particles needs powerful classification methods, with the capacity to be optimized for unknown cross-sections and particle masses, and also be able to account for systematic effects ie a fully differentiable analysis framework.

Project 6

Create a PID model to distinguish e/pi

Create a model within the Jlab ML workflow for Particle IDentification and determine PID systematic error with the ensemble method