arXiv subjects

Jacob A. Kurlander

Publications and source records attributed to Jacob A. Kurlander.

12 recordsLinked to original sources

arXiv2026

NSF-DOE Vera C. Rubin Observatory Observations of Interstellar Comet 3I/ATLAS (C/2025 N1)

We report on the observation and measurement of astrometry, photometry, morphology, and activityof the interstellar object 3I/ATLAS, also designated C/2025 N1 (ATLAS) with the NSF-DOE Vera C. Rubin Observatory. Comet 3I/ATLAS, the third known interstellar object, was discovered on UT 2025 July 1. Rubin Observatory had coincidentally collected images of the object's region of the sky during routine commissioning. Facilitated by Rubin's high resolution and large aperture, we successfully recovered object detections from Rubin observations spanning UT 2025 June 21 (10 days before discovery, when 3I/ATLAS was 4.5 au from the Sun) through the date of discovery, and we acquired additional images through UT 2025 July 20 as part of commissioning. We measure on-sky locations of 3I/ATLAS in Rubin ugrizy bands, with a typical precision of about 70 mas, and briefly describe the reason this is coarser than our measured static source astrometric precision of about 3 mas in Rubin images. We measure grizy magnitudes of 3I/ATLAS photometry at about 0.01 mag precision, detecting no short-term photometric variability above 0.01 mag. We derive an estimated near-nucleus dust-to-nucleus scattering cross-section ratio of eta >= 13 on UT 2025 July 2 based on Rubin photometry and an upper limit nucleus size computed from Hubble Space Telescope observations. We find Rubin colors of g - r = (0.657 +/- 0.013) mag, r - i = (0.235 +/- 0.018) mag, i - z = (0.147 +/- 0.042) mag, z - y = (0.047 +/- 0.052) mag. These data represent the earliest observations of this object by a large (>=8-meter class) telescope and illustrate the type of measurements (and discoveries) Rubin's Legacy Survey of Space and Time (LSST) will begin to provide after it begins in early 2026.

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arXiv2026

Predictions of Imminent Earth Impactors Discovered by LSST

Imminent impactors are natural bodies discovered in space before impacting the Earth. They provide a rare opportunity to characterize individual near-Earth objects (NEOs) in great detail as asteroids in space, meteors in Earth's atmosphere and meteorites on the ground. The Vera C. Rubin Observatory's upcoming Legacy Survey of Space and Time (LSST) is expected to transform our understanding of the NEO population. In this work, we evaluate LSST's expected discovery performance for imminent impactors using $343$ meter-size objects previously recorded in NASA's CNEOS database as fireballs impacting Earth's atmosphere. We simulate pre-impact observations of these CNEOS impactors with the Sorcha survey simulator under LSST's default three-night discovery strategy and a one-night strategy for fast-moving objects that relies on matching aligned streaks in two exposures on the same night. We estimate that LSST will discover $\sim1-2$ meter-size and larger imminent impactors per year, representing $\sim4\%$ of all Earth impactors $\gtrsim1$ m in diameter and almost doubling the current discovery rate of imminent impactors. The median time of discovery and median time of first observation for impactors discovered in our simulations are $\sim1.57$ and $\sim3.06$ days before impact, respectively. The spatial distribution of the 11 previously discovered imminent impactors is biased towards the Northern Hemisphere, where the observatories that discovered them are located. We find a similar trend towards Southern Hemisphere impacts in our simulated LSST detections of the CNEOS impactors, suggesting Rubin will provide a powerful counterpart to existing asteroid surveys primarily located in the Northern Hemisphere.

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arXiv2026

Assessing the Vera Rubin Observatory's Ability to Discover Asteroid Impactors Before They Collide with Earth

Asteroid impactors larger than ~10 m, from Chelyabinsk-scale airburst and Tunguska-scale events to >300 m continental threats, remain the dominant planetary-defense risk. While the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will transform Solar System science, its observing cadence and survey design were not specifically optimized to discover imminent impactors. To assess its performance, we introduce a new method for efficiently generating synthetic impactor populations by minimally perturbing sampled NEOMOD3 orbits and evaluate their discovery efficiency with the Sorcha survey simulator. Our simulations show that LSST discovers 79.7% of large impactors (>140 m), decreasing to 50.3% for upper mid-sized (50-140 m), 26.8% for lower mid-sized (20 - 50 m), and 10.5% for small objects (10-20 m). Warning times of the discovered impactors show a similar size dependence: small objects are typically discovered only weeks before impact (median:12.4 days), lower mid-sized within a month (median: 21.5 days), and upper mid-sized objects on timescales of a few months (median: 106.2 days). 39.0% of large impactors are discovered more than a year before impact, lacking long-lead warning despite their brightness. A loss-mode analysis reveals the underlying cause that small impactors are limited mainly by photometric sensitivity, whereas mid-sized and large objects are missed primarily due to cadence and linking constraints from LSST and its Solar System Processing (SSP) Pipelines. These results show that LSST excels at discovering faint, small impactors, but cannot by itself guarantee long-lead warning across the hazardous size spectrum. Coordinated multi-survey strategies will therefore be essential in the LSST era to achieve robust planetary-defense capability, and we study a complementary high-cadence, shallow-depth example with the Argus Array.

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arXiv2025

Predictions of the LSST Solar System Yield: Neptune Trojans

The NSF-DOE Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), beginning full operations in late 2025, will dramatically transform solar system science by vastly expanding discoveries and providing detailed characterization opportunities across all small body populations. This includes the co-orbiting 1:1 resonant Neptune Trojans, which are thought to be dynamically hot captures from the protoplanetary disk. Using the survey simulator $\texttt{Sorcha}$, combined with the latest LSST cadence simulations, we present the very first predictions for the Neptune Trojan yield within the LSST. We forecast a model-dependent median number of $\sim130-300$ discovered Neptune Trojans, and infer a notable 2:1 detection bias toward the recently emerged L5 cloud near the galactic plane versus the L4 cloud, reflecting the lower-cadence coverage in the Northern Ecliptic Spur region that suppresses L4 detections. The additionally simulated Science Validation survey will offer the very first early insights into this understudied cloud. Around 60\% of detected main survey Neptune Trojans will meet stringent color light curve quality criteria, increasing the sample size more than fourfold compared to existing datasets. This enhanced sample will enable robust statistical analyses of Neptune Trojan color and size distributions, crucial for understanding their origins and relationship to the broader trans-Neptunian population. These comprehensive color measurements represent a major step forward in characterizing the Neptune Trojan population and will facilitate future targeted spectroscopic observations.

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arXiv2025

Rotational Light-curve Recovery and Predictions of the LSST Yield of Hildas

The Hilda population occupies the stable 3:2 mean-motion resonance of Jupiter and provides a window into solar system evolution, including collisional processes. The National Science Foundation and Department of Energy Vera C. Rubin Observatory will conduct the 10 yr Legacy Survey of Space and Time (LSST). We present a simulation of Rubin's discovery of Hildas with the Sorcha survey simulator and the recovery of their light curves. We constructed a synthetic Hilda population model that includes distributions of orbital properties, sizes, collisional families, and colors. We applied three distinct populations of sinusoidal light curves to this same orbit-size-color model: (1) a Gaussian kernel density estimate fit to rotational periods and amplitudes from the Lightcurve Database (LCDB), (2) a superfast rotator population, and (3) a superslow rotator population. Over the 10 yr simulated survey, we predict LSST will discover ~33,400 Hildas, a fivefold increase over the known population. Using a multiband Lomb-Scargle Periodogram via Astropy we confidently recover ~45.96% of Hildas in our LCDB-based population, higher than typical in observational searches. This suggests our light-curve population model may differ from the intrinsic population. We find strong biases in light-curve amplitude, with recovery efficiency dropping sharply below 0.1 magnitudes, while biases from rotational period are comparatively weak aside from cadence-related features such as LSST's ~36 minute revisit cadence. Our recovery efficiency is likely overestimated due to our assumption of constant sinusoidal light curves, which correspond to optimal pole orientations. These results are the first test of light-curve recovery from simulated LSST observations.

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arXiv2025

Predictions of the LSST Solar System Yield: Near-Earth Objects, Main Belt Asteroids, Jupiter Trojans, and Trans-Neptunian Objects

The NSF-DOE Vera C. Rubin Observatory is a new 8m-class survey facility presently being commissioned in Chile, expected to begin the 10yr-long Legacy Survey of Space and Time (LSST) by the end of 2025. Using the purpose-built Sorcha survey simulator (Merritt et al. In Press), and near-final observing cadence, we perform the first high-fidelity simulation of LSST's solar system catalog for key small body populations. We show that the final LSST catalog will deliver over 1.1 billion observations of small bodies and raise the number of known objects to 1.27E5 near-Earth objects, 5.09E6 main belt asteroids, 1.09E5 Jupiter Trojans, and 3.70E4 trans-Neptunian objects. These represent 4-9x more objects than are presently known in each class, making LSST the largest source of data for small body science in this and the following decade. We characterize the measurements available for these populations, including orbits, griz colors, and lightcurves, and point out science opportunities they open. Importantly, we show that ~70% of the main asteroid belt and more distant populations will be discovered in the first two years of the survey, making high-impact solar system science possible from very early on. We make our simulated LSST catalog publicly available, allowing researchers to test their methods on an up-to-date, representative, full-scale simulation of LSST data.

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arXiv2025

Predictions of the LSST Solar System Yield: Discovery Rates and Characterizations of Centaurs

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will start by the end of 2025 and operate for ten years, offering billions of observations of the southern night sky. One of its main science goals is to create an inventory of the Solar System, allowing for a more detailed understanding of small body populations including the Centaurs, which will benefit from the survey's high cadence and depth. In this paper, we establish the first discovery limits for Centaurs throughout the LSST's decade-long operation using the best available dynamical models. Using the survey simulator $\texttt{Sorcha}$, we predict a $\sim$7-12 fold increase in Centaurs in the Minor Planet Center (MPC) database, reaching $\sim$1200-2000 (dependent on definition) by the end of the survey - about 50$\%$ of which are expected within the first 2 years. Approximately 30-50 Centaurs will be observed twice as frequently as they fall within one of the LSST's Deep Drilling Fields (DDF) for on average only up to two months. Outside of the DDFs, Centaurs will receive $\sim$200 observations across the $\textit{ugrizy}$ filter range, facilitating searches for cometary-like activity through PSF extension analysis, as well as fitting light-curves and phase curves for color determination. Regardless of definition, over 200 Centaurs will achieve high-quality color measurements across at least three filters in the LSST's six filters. These observations will also provide over 300 well-defined phase curves in the $\textit{griz}$ bands, improving absolute magnitude measurements to a precision of 0.2 mags.

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arXiv2025

Sorcha: A Solar System Survey Simulator for the Legacy Survey of Space and Time

The upcoming Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory is expected to revolutionize solar system astronomy. Unprecedented in scale, this ten-year wide-field survey will collect billions of observations and discover a predicted $\sim$5 million new solar system objects. Like all astronomical surveys, its results will be affected by a complex system of intertwined detection biases. Survey simulators have long been used to forward-model the effects of these biases on a given population, allowing for a direct comparison to real discoveries. However, the scale and tremendous scope of the LSST requires the development of new tools. In this paper we present Sorcha, an open-source survey simulator written in Python. Designed with the scale of LSST in mind, Sorcha is a comprehensive survey simulator to cover all solar system small-body populations. Its flexible, modular design allows Sorcha to be easily adapted to other surveys by the user. The simulator is built to run both locally and on high-performance computing (HPC) clusters, allowing for repeated simulation of millions to billions of objects (both real and synthetic).

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arXiv2025

Sorcha: Optimized Solar System Ephemeris Generation

Sorcha is a solar system survey simulator built for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and future large-scale wide-field surveys. Over the ten-year survey, the LSST is expected to collect roughly a billion observations of minor planets. The task of a solar system survey simulator is to take a set of input objects (described by orbits and physical properties) and determine what a real or hypothetical survey would have discovered. Existing survey simulators have a computational bottleneck in determining which input objects lie in each survey field, making them infeasible for LSST data scales. Sorcha can swiftly, efficiently, and accurately calculate the on-sky positions for sets of millions of input orbits and surveys with millions of visits, identifying which exposures these objects cross, in order for later stages of the software to make detailed estimates of the apparent magnitude and detectability of those input small bodies. In this paper, we provide the full details of the algorithm and software behind Sorcha's ephemeris generator. Like many of Sorcha's components, its ephemeris generator can be easily used for other surveys.

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arXiv2025

A Pan-STARRS Search for Distant Planets: Part 1

We present a search for distant planets in Pan-STARRS1. We calibrated our search by injecting an isotropic control population of synthetic detections into Pan-STARRS1 source catalogs, providing a high-fidelity alternative to injecting synthetic sources at the image level. We found that our method is sensitive to a wide range of distances, as well as all rates and directions of motion. We identified 692 solar system objects (109 of which are not yet listed in the Minor Planet Center's database), including 642 TNOs, 23 of which are dwarf planets. By raw number of detections, this makes our search the third most productive Kuiper Belt survey to date, in spite of the fact that we did not explicitly search for objects closer than 80 au. Although we did not find Planet Nine or any other planetary objects, we were able to show that the remaining parameter space for Planet Nine is highly concentrated in the galactic plane.

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arXiv2025

A Link Between White Dwarf Pulsars and Polars: Multiwavelength Observations of the 9.36-Minute Period Variable Gaia22ayj

White dwarfs (WDs) are the most abundant compact objects, and recent surveys have suggested that over a third of WDs in accreting binaries host a strong (B $\gtrsim$ 1 MG) magnetic field. However, the origin and evolution of WD magnetism remain under debate. Two WD pulsars, AR Sco and J191213.72-441045.1 (J1912), have been found, which are non-accreting binaries hosting rapidly spinning (1.97-min and 5.30-min, respectively) magnetic WDs. The WD in AR Sco is slowing down on a $P/\dot{P}\approx 5.6\times 10^6$ yr timescale. It is believed they will eventually become polars, accreting systems in which a magnetic WD (B $\approx 10-240$ MG) accretes from a Roche lobe-filling donor spinning in sync with the orbit ($\gtrsim 78$ min). Here, we present multiwavelength data and analysis of Gaia22ayj, which outbursted in March 2022. We find that Gaia22ayj is a magnetic accreting WD that is rapidly spinning down ($P/\dot{P} = 6.1^{+0.3}_{-0.2}\times 10^6$ yr) like WD pulsars, but shows clear evidence of accretion, like polars. Strong linear polarization (40%) is detected in Gaia22ayj; such high levels have only been seen in the WD pulsar AR Sco and demonstrate the WD is magnetic. High speed photometry reveals a 9.36-min period accompanying a high amplitude ($\sim 2$ mag) modulation. We associate this with a WD spin or spin-orbit beat period, not an orbital period as was previously suggested. Fast (60-s) optical spectroscopy reveals a broad ``hump'', reminiscent of cyclotron emission in polars, between 4000-8000 Angstrom. We find an X-ray luminosity of $L_X = 2.7_{-0.8}^{+6.2}\times10^{32} \textrm{ erg s}^{-1}$ in the 0.3-8 keV energy range, while two VLA radio campaigns resulted in a non-detection with a $F_r < 15.8μ\textrm{Jy}$ 3$ σ$ upper limit. The shared properties of both WD pulsars and polars suggest that Gaia22ayj is a missing link between the two classes of magnetic WD binaries.

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arXiv2024

A Well-Characterized Survey for Centaurs in Pan-STARRS1

To prepare for the upcoming Legacy Survey of Space and Time, we develop methods for quantifying the selection function of a wide-field survey as a function of all six orbital parameters and absolute magnitude. We perform a HelioLinC3D search for Centaurs in the Pan-STARRS1 detection catalog and use a synthetic debiasing population to characterize our survey's selection function. We find nine new objects, including Centaur 2010 RJ$_{226}$, among 320 real objects, along with $\sim$70,000 debiasing objects. We use the debiasing population to fit a selection function and apply the selection function to a model Centaur population with literature orbital and size distributions. We confirm the model's marginal distributions but reject its joint distribution, and estimate an intrinsic population of 21,400$^{+3,400}_{-2,800}$ Centaurs with $H_r < 13.7$. The discovery of only nine new objects in archival data verifies that the Pan-STARRS discovery pipeline had high completeness, but also shows that new linking algorithms can contribute even to traditional single-tracklet surveys. As the first systematic application of HelioLinC3D to a survey with extensive sky coverage, this project proves the viability of HelioLinC3D as a discovery algorithm for big-data wide-field surveys.

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