Using GeoSnap Mid-Infrared Detectors for Exoplanet Research on Large Telescopes
Bibliographic record
Abstract
In the past few decades, the study of planets around other stars, or exoplanets, has flourished. Various methods can be used to discover and characterize these targets, enabling astronomers to learn more about how distant worlds and our own came to be. A key means of studying exoplanets is through direct imaging which can be used to determine a target's luminosity, temperature (and thus radius), and atmospheric abundances. The robust information gained via direct imaging is essential to constraining existing exoplanet models which struggle to accurately predict certain structural and evolutionary properties, including the current luminosity of Jupiter. In this thesis, I advance the study of exoplanets by developing and commissioning new infrared instruments that can be used to study wide-orbit gas giants and brown dwarfs. These targets will enable better constraints on evolutionary models. They are of further interest since they can significantly influence their neighboring terrestrial worlds, possibly enhancing or destroying habitability. At the University of Michigan, I tested multiple GeoSnap detectors in cryogenic environments. These particular GeoSnap arrays have been bonded with photosensitive material that can capture mid-infrared light, making them well-suited for studying exoplanets that emit primarily in this wavelength regime due to their cool temperatures. GeoSnap detectors are at the forefront of mid-infrared technology, featuring a combination of extremely deep wells, fast readouts, high quantum efficiency, and low noise while remaining sensitive from 2 to 13 microns. These traits are critical since Earth's atmosphere and the telescope emission in the mid-infrared is immense and will otherwise saturate most detectors. I characterize properties of the detectors including quantum efficiency and prominent noise sources. Following the characterization of the detectors, they must then be implemented into instruments that can be paired with telescopes. I discuss our implementation of one of the GeoSnap detectors in MIRAC-5, a ground-based mid-infrared instrument on the 6.5 m MMT telescope. MIRAC-5 science cases include estimates of the abundance of nitrogen in nearby brown dwarfs. We commissioned MIRAC-5 on the MMT telescope, calculated the on-sky performance, determined the future sensitivity limits, and built a SNR model code and exposure time calculator for the instrument. I discuss potential applications of the instrument and future work necessary to achieve optimal performance. I pivot to the future of ground-based mid-IR astronomy by discussing the planned METIS instrument on the 39-meter ELT. METIS can observe rocky planets on the order of 2 Earth radii around the very nearest stars and has significant potential to detect at least one small and presumably rocky planet. I conclude by returning to the near future, outlining applications for MIRAC-5 including quantifying the negative impact of megasatellite constellations on infrared observing and constraining exoplanet evolutionary models via observations of poorly sampled gas giants and brown dwarfs (with dynamical mass constraints orbiting stars of known distance and age). With updated MIRAC-5 performance estimates, I rule out the feasibility of nitrogen abundance estimates even with future system upgrades.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".