QuSpin zero-field magnetometer characterization for the TUCAN experiment
Bibliographic record
Abstract
Abstract The TUCAN neutron electric dipole moment experiment utilizes the QuSpin Zero-Field Magnetometer (QZFM) to accurately map residual fields within a large magnetically shielded room. Three potential flaws of the QZFM are characterized in preparation for mapping. The magnetometer’s intrinsic offset was measured to be within <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mo>±</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:mrow> </mml:math> nT and stable over a period of one year. The response was shown to be within 2 percent of linearity in the zero-field regime, up to 2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>nT</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>pp</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , and then follows a smooth dispersion curve. Crosstalk effects induced by multisensor operation were determined to have a small effect, and inconsequential with a separation above 6 cm. These results enable the QZFM for accurate measurement of DC fields, increase the operational range of QZFM by a factor of more than an order of magnitude, and allow for higher efficiency and flexibility by green-lighting simultaneous operation of multiple QZFMs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".