STI Publications - View Publication Form #16923
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Publication Information
| Title | AI for Experimental Controls at Jefferson Lab | ||||
| Abstract | The AI for Experimental Controls project is developing an AI system to control and calibrate detector systems located at Jefferson Laboratory. Currently, calibrations are performed offline and require significant time and attention from experts. This work would reduce the amount of data and the amount of time spent calibrating in an offline setting. The first use case involves the Central Drift Chamber (CDC) located inside the GlueX spectrometer in Hall D. We use a combination of environmental and experimental data, such as atmospheric pressure, gas temperature, and the flux of incident particles as inputs to a Sequential Neural Network (NN) to recommend a high voltage setting and the corresponding calibration constants in order to maintain consistent gain and optimal resolution throughout the experiment. Utilizing AI in this manner represents an initial shift from offline calibration towards near real time calibrations performed at Jefferson Laboratory. | ||||
| Author(s) | Torri Jeske, Naomi Jarvis  , Diana McSpadden, Nikhil Kalra, David Lawrence, Thomas Britton |
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| Publication Date | March 2022 | ||||
| Document Type | Meeting, Journal Article | ||||
| Primary Institution | Thomas Jefferson National Accelerator Facility, Newport News | ||||
| Affiliation | Comp Sci&Tech (CST) Div / Scientific Computing / Scientific Computing | ||||
| Funding Source | Nuclear Physics (NP) | ||||
| Proprietary? | No | ||||
| This publication conveys | Technical Science Results | ||||
| Document Numbers |
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| Associated with an experiment | No | ||||
| Associated with EIC | No | ||||
| Supported by Jefferson Lab LDRD Funding | No |
Meeting / Conference
| Meeting Name | AI4EIC 2021 |
| Meeting Date | 9/7/2021 |
| Document Subtype | Invited Talk (proceedings) |
Journal Article
| Journal Name | Journal of Instrumentation |
| Refereed | Yes |
| Volume | 17 |
| Issue | |
| Page(s) | C03043 |
Attachments/Datasets/DOI Link
| Document(s) |
AI4EIC_proceedings-51.pdf
(STI Document)
AI4EIC_proceedings-51.pdf
(Accepted Manuscript)
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| DOI Link | |
| Dataset(s) | (none) |
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