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Record W4412122628 · doi:10.5194/epsc-dps2025-1132

The Luminosity Function Of Ultra-Faint Trans-Neptunian Objects Detected By James Webb Space Telescope

2025· preprint· en· W4412122628 on OpenAlexaff
Marielle R. Eduardo, Anastasia Morgan, Wesley C. Fraser, David E. Trilling, G. M. Bernstein, Matthew J. Holman, John Stansberry, B. Hilbert, W. M. Grundy, Kevin J. Napier

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsTrans-Neptunian objectLuminosity functionPhysicsLuminosityJames Webb Space TelescopeSpace (punctuation)AstronomyFunction (biology)TelescopeSpitzer Space TelescopeAstrophysicsAstrobiologyPhilosophyAsteroidGalaxy

Abstract

fetched live from OpenAlex

Trans-Neptunian Objects (TNOs), which are the small bodies beyond the orbit of Neptune, are regarded to be the most primitive members of the Solar System, and as such, provides valuable insights into both history and the current state of the outer Solar System.Their size distribution (SD), which can be inferred from their observed magnitude distributions, has remained relatively unaltered since the formation of the Solar System. This physical property is crucial for testing theoretical models of planet formation because it reflects the outcomes of accretion, collisional processes, and dynamical evolution over the history of the Solar System [1]. Therefore, comparing the observed size distribution with those predicted by models helps to constrain the proposed physical processes and underlying initial conditions that shaped the current Solar System. However, the relative faintness and distance of TNOs limits ground-based searches to only about m(r)~27 magnitude [2], while the lack of observations on the SD of TNOs smaller than m(r)~28 (D~20km) leaves theoretical models poorly constrained [3,4].Using images obtained from our JWST Cycle 1 program #1568 we searched for ultra-faint TNOs to further constrain planet formation models. With this program’s NIRCam images, and simultaneous HST imaging, we detect and characterize TNOs as faint as m(r)~29.8 mag and as small as ~7 km (assuming 15% albedo) in diameter to explore never-before probed regions of the TNO size distribution. This is by far the deepest Solar System survey to date, with at least a visible magnitude deeper than the landmark survey by Bernstein et al. (2004) that used the Hubble Space Telescope (HST). Program #1568 is a 3-epoch pencil beam sky survey conducted using NIRCam filters with effective wavelengths of ~1.5µm (F150W2) and 3.2µm (F322W2), centered on a region of the sky near 13h RA, -10° Dec. The observations are near the ecliptic plane, where the sky density of cold classical TNOs is maximal. The observations were taken from Jan 24 - Feb 4, 2023, at solar elongation of ~100 degrees, where the TNOs are near their turnaround points and are least likely to move off of the NIRCAM field of view. Figure 1 shows the observation layout of this program. A deep combined background image is subtracted from individual exposures, which are then digitally tracked and stacked at different rates of motion to search for TNOs.The probability with which a TNO will be detected as a good track during a single epoch, whether it falls on a detector during both dithers, is quantified using the implanted artificial moving objects. It is well fit by the functional form , with the bright-end efficiency p0=0.96, the magnitude of half that efficiency at m0=28.92 (F150W2), and transition width w = 0.61 mag (see Figure 2).We present our preliminary set of candidate sources detected with a total SNR of 15. By constraining their orbital parameters, we measure the faint end of the luminosity function for both the dynamically cold and hot components, and present their implications to the TNO SD down to diameters of 7 km. In future work, we will conduct a detailed analysis to determine which functional form of the size distribution best characterizes the observed population. This will offer deeper insights into the physical mechanisms governing the formation and evolution of the cold and hot populations, as well as the Kuiper Belt as a whole. Figures:Figure 1. Observation footprints of the survey, consisting of 10×2 mosaic tiles. Each tile was observed with eight short-wavelength detectors (small squares with a 64″×64″ FOV) and two long-wavelength detectors, each equivalent in size to four short-wavelength detectors, covering 129″ × 129″. Two exposures were taken at each of the 20 mosaic tiles. Each of the two exposures consisted of three 215s integrations, and were acquired at dither positions

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.006
GPT teacher head0.199
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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