Difference between revisions of "AI Optimized Polarization"
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* Proposal: [https://www.overleaf.com/project/636ebdb8f12e5e40fc6750ab overleaf], [[Media:FOA_002875_AIEC_v0.3.pdf|PDF]] | * Proposal: [https://www.overleaf.com/project/636ebdb8f12e5e40fc6750ab overleaf], [[Media:FOA_002875_AIEC_v0.3.pdf|PDF]] | ||
* Victoria Lagerquist's thesis: [https://www.jlab.org/Hall-B/general/thesis/VLagerquist_thesis.pdf Design and Construction of a Longitudinally Polarized Solid Nuclear Target for CLAS12] | * Victoria Lagerquist's thesis: [https://www.jlab.org/Hall-B/general/thesis/VLagerquist_thesis.pdf Design and Construction of a Longitudinally Polarized Solid Nuclear Target for CLAS12] | ||
| + | * Noémie's polarization extracted from elastic scattering: [https://clasweb.jlab.org/wiki/index.php/Elastic_Analysis_for_PbPt_Extraction Elastic Analysis for PbPt extraction] | ||
== Resources == | == Resources == | ||
Revision as of 12:48, 25 April 2024
Meetings
Repositories
Raw data storage
- Photon Source: /work/halld3/home/AIOP/source/
- Target: /work/halld3/home/AIOP/target/
Presentations/Papers
| Date | Presenter | Event | Slides | Proceedings |
|---|
Experimental Data Locations
Run Group C, 2022-23
- /group/poltar/HallB/RGC
- Proton data in directory data-p
- Deuteron data in directory data-d
SANE, 2009
- /group/poltar/HallC/SANE
- all_data.csv contains NMR system meta-data
- epics_export.txt contains EPICS meta-data
- events folder contains online data with raw NMR signals
- Several ipynb files give examples of reading the above files
Documentation
- Proposal: overleaf, PDF
- Victoria Lagerquist's thesis: Design and Construction of a Longitudinally Polarized Solid Nuclear Target for CLAS12
- Noémie's polarization extracted from elastic scattering: Elastic Analysis for PbPt extraction
Resources
| Title/Link | Type | Notes |
|---|---|---|
| The Stonehenge Technique. A new method for aligning coherent bremsstrahlung radiators (NIM, arXiv) | Paper | |
| Coherent Bremsstrahlun of Electrons in Crystals(GlueX DocDB) | Paper | |
| Development of Novel Attention-Aware Deep Learning Models and Their Applications in Computer Vision and Dynamical System Calibration | Thesis |