Liquid crystal polarization rotators for the Miniaturized Absolute Magnetometer (MAM) of the NanoMagSat space mission
Bibliographic record
Abstract
Liquid Crystal Polarization Rotators (LCPRs) have been developed for the Miniaturized Absolute Magnetometer (MAM) instrument in NanoMagSat project, an ESA’s SCOUT program mission. This project consists of a constellation of three nanosatellites aimed to study the Earth’s magnetic and ionospheric environment based on a 16U CubeSat-type structure. The MAM instrument is an optically pumped scalar and vector magnetometer derived from the ASM flown on the ESA Swarm mission. In this type of instruments, a device to rotate the direction of the incident linear polarization of the pumping beam injected into the helium-4 gas cell sensor is required. In NanoMagSat, the LCPRs will replace the sensor head rotor driven by a piezoelectric motor used in the ASM, allowing a very significant miniaturization of the sensor head. The LCPRs developed are miniaturized devices derived from the polarization modulators based on liquid crystals of PHI and METIS instruments on board the Solar Orbiter mission and optimized for the MAM instrument requirements. The key performance parameters of the devices have been evaluated in a validation test campaign, under the different environmental conditions expected in NanoMagSat, including the polarization rotation and the Polarization Extinction Ratio (PER) as a function of voltage, and the response times at the MAM polarization rotation scheme and will be presented in this work. Based on the results found, the LCPRs design and validation test campaign has been considered successful and they have been approved to be implemented for the NanoMagSat mission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".