A Monte Carlo Forecast for the Detection of Planet Nine

This preprint forecasts the detectability of the hypothesized Planet Nine by propagating a weighted three-model parameter ensemble — drawn from Batygin et al. (2019), Brown & Batygin (2021), and Siraj et al. (2025) — through a Monte Carlo orbit simulation (N = 100,000). For each sample it solves Kepler's equation, projects to geocentric equatorial coordinates with astropy, estimates an r-band apparent magnitude, applies existing survey null-detection masks (ZTF, Pan-STARRS, DES), and models future detection by the Vera C. Rubin Observatory/LSST, Subaru/HSC, and infrared surveys through 2036. The current heliocentric distance dominates all detection uncertainty. The combined cumulative detection probability rises steeply once LSST reaches full depth and asymptotes near 0.61 by 2030, leaving a roughly two-fifths residual too faint or too distant for current facilities. The analysis treats Planet Nine's existence as an unproven hypothesis and reports how a sustained null result would revise a stated prior; it does not claim the planet exists. METHODOLOGICAL TRANSPARENCY: This is a human-directed AI synthesis, not a peer-reviewed study. The human author curated the inquiry, selected the source models, and is responsible for all claims; an agentic AI instrument (Google Antigravity) assisted with drafting, simulation, and literature synthesis under that direction. All quantitative results are reproducible from the accompanying simulation.py (numpy seed 42), available in the linked repository. Parameter values quoted from secondary sources should be confirmed against the primary papers before being relied upon. This work is offered as a conditional forecast and a hypothesis for empirical testing, not as an established result.