The visibility of the \={O}tautahi-Oxford interstellar object population model in LSST

TL;DR

This study uses a new probabilistic sampling method to evaluate how interstellar objects (ISOs) will be observed by LSST, revealing complex sky patterns, detection biases, and the potential to constrain ISO luminosity functions.

Contribution

It introduces an efficient probabilistic technique for sampling ISO orbits and assesses their observability with LSST using the f4tautahi-Oxford population model.

Findings

Expected ISO discoveries range from 6 to 51 based on spatial densities.

Most ISOs will be visible for over a month, often with magnitude fcmr fcm 23.

The ISO luminosity function slope can be constrained quickly.

Abstract

With a new probabilistic technique for sampling interstellar object (ISO) orbits with high efficiency, we assess the observability of ISOs under a realistic cadence for the upcoming Vera Rubin Observatory's Legacy Survey of Space and Time (LSST). Using the \={O}tautahi-Oxford population model, we show that there will be complex on-sky structure in the pattern of direction and velocity revealed by the detected ISO population, with the expected enhanced northern flux complicating efforts to derive population parameters from the LSST's predominately southern footprint. For luminosity functions with slopes of $2.5\leq q_s\leq 4.0$, the most discoverable ISOs have $H_r\simeq 14.6-20.7$; for previously estimated spatial densities, between 6 and 51 total ISOs are expected. The slope of the luminosity function of ISOs will be relatively quickly constrained. Discoveries are evenly split around their perihelion passage and are biased to lower velocities. After their discovery by LSST, it will be rare for ISOs to be visible for less than a month; most will have $m_r \leq 23$ for months, and the window for spectroscopic characterization could be as long as two years. These probabilistic assessments are robust against model or spatial density refinements that change the absolute numbers of ISO discoveries.