STI Publications - View Publication Form #16799
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Publication Information
Title | Quantum Enhanced Tracker | ||||
Abstract | We report the study and development of a novel new charged particle detector, a "Quantum Enhanced Tracker" for 3D imaging of charged particle tracks. The proposed detector relies on, and benefits from, the extremely high sensitivity of atoms, prepared in a specific quantum superposition, to external perturbations. Atoms are prepared in a so-called "dark superposition" state, a passing charged particle will disturb this quantum state, allowing atoms to change polarization of the probe light or absorb probe light and to fluoresce, enabling direct imaging of the particle trajectory with high resolution. This method has similarities with Cherenkov detectors where a charged particle produces light along its track, but with the major advantages of enhanced sensitivity due to the low energy required to perturb the engineered quantum state, the ability to amplify the signal using a drive laser passing through the medium, and the ability to provide a 3D track. | ||||
Author(s) | Shukui Zhang, Alexandre Camsonne, Todd Averett, Seth Aubin, Eugeniy Mikhailov, Irina Novikova, Nic DeStefano, J. Li | ||||
Publication Date | October 2021 | ||||
Category | Optical Physics & Technology | ||||
Document Type | Meeting | ||||
Primary Institution | Thomas Jefferson National Accelerator Facility, Newport News | ||||
Affiliation | Accelerator Ops, R&D / Ctr For Injectors&Sources / Ctr for Injectors&Sources | ||||
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 | Yes | ||||
LDRD Number(s) |
2022-LDRD-14
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Meeting / Conference
Meeting Name | APS DNP Fall meeting |
Meeting Date | 10/11/2021 |
Document Subtype | Contributed Talk |
Attachments/Datasets/DOI Link
Document(s) |
APS DNP Fall meeting talk_SZ.pdf
(STI Document)
|
Dataset(s) | (none) |
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