Polarization and two-photon spectroscopy of xenon for optical magnetometry
Bibliographic record
Abstract
This dissertation presents work in the hyperpolarization of ¹²⁹Xe and in precision Xe spectroscopy using two-photon absorption. Both projects contribute to the development of optical magnetometry using ¹²⁹Xe. Motivating this work is the proposal for a new ¹²⁹Xe-based comagnetometer at TRIUMF for experiments searching for a permanent electric dipole moment of the neutron. In these proposed experiments ¹²⁹Xe will occupy the same experimental volume as ultracold neutrons and be used to measure drifts in an applied magnetic field. A scheme is described for optical magnetometry which involves the production of polarized ¹²⁹Xe followed by measurements using two-photon laser induced fluorescence as a probe. Spin exchange optical pumping is used to produce polarized ¹²⁹Xe, which is a necessary precursor for optical magnetometry. The first part of this dissertation presents the implementation and operation of a polarizer using a diode laser and a Xe-Rb-N₂-He mixture. We have achieved hyperpolarization of ¹²⁹Xe up to PXe ~ 5%, which is many times greater than the thermal equilibrium polarization. We measure the nuclear magnetic resonance signal from polarized ¹²⁹Xe using a low-field detection apparatus, and compare the signal with predictions based on a rate equation model. Efforts to optimize the degree of polarization in the present apparatus are described, as well as purification of Xe gas through freezeout. The second part of this dissertation presents precision spectroscopy on natural abundance Xe using a narrow linewidth laser. The two-photon transition studied here ( 5p⁵(²P₃/₂)6p²[3/2]₂ ← 5p⁶ (¹S₀)) is suitable to probe the ground state ¹²⁹Xe polarization for optical magnetometry. We present the implementation of a CW laser source with narrow linewidth followed by the excitation of Xe two-photon absorption in a resonant cavity. We measure and report hyperfine constants and isotope shifts from the observed laser induced fluorescence spectra. From the observed signal to noise ratio we estimate a magnetometric sensitivity based on this detection scheme over a range of Xe pressures. Results from this two-photon absorption measurement are essential in the determination of parameters for final implementation in the nEDM experiment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".