arXiv subjects

Mario Juric

Publications and source records attributed to Mario Juric.

At least 19 recordsLinked to original sources

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

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

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

Using LSDB to enable large-scale catalog distribution, cross-matching, and analytics

The Vera C. Rubin Observatory will generate an unprecedented volume of data, including approximately 60 petabytes of raw data and around 30 trillion observed sources, posing a significant challenge for large-scale and end-user scientific analysis. As part of the LINCC Frameworks Project we are addressing these challenges with the development of the HATS (Hierarchical Adaptive Tiling Scheme) format and analysis package LSDB. HATS partitions data adaptively using a hierarchical tiling system to balance the file sizes, enabling efficient parallel analysis. Recent updates include improved metadata consistency, support for incremental updates, and enhanced compatibility with evolving datasets. LSDB complements HATS by providing a scalable, user-friendly interface for large catalog analysis, integrating spatial queries, crossmatching, and time-series tools while utilizing Dask for parallelization. We have successfully demonstrated the use of these tools with datasets such as ZTF and Pan-STARRS data releases on both cluster and cloud environments. We are deeply involved in several ongoing collaborations to ensure alignment with community needs, with future plans for IVOA standardization and support for upcoming Rubin, Euclid and Roman data. We provide our code and materials at lsdb.io.

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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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arXiv2024

The DECam Ecliptic Exploration Project (DEEP). VII. The Strengths of Three Superfast Rotating Main-belt Asteroids from a Preliminary Search of DEEP Data

Superfast rotators (SFRs) are small solar system objects that rotate faster than generally possible for a cohesionless rubble pile. Their rotational characteristics allow us to make inferences about their interior structure and composition. Here, we present the methods and results from a preliminary search for SFRs in the DECam Ecliptic Exploration Project (DEEP) data set. We find three SFRs from a sample of 686 main-belt asteroids, implying an occurrence rate of 0.4 -0.3/+0.1 percent - a higher incidence rate than has been measured by previous studies. We suggest that this high occurrence rate is due to the small sub-kilometer size regime to which DEEP has access: the objects searched here were as small as 500 m. We compute the minimum required cohesive strength for each of these SFRs and discuss the implications of these strengths in the context of likely evolution mechanisms. We find that all three of these SFRs require strengths that are more than that of weak regolith but consistent with many cohesive asteroid strengths reported in the literature. Across the full DEEP data set, we have identified ~70,000 Main-Belt Asteroids and expect ~300 SFRs - a result that will be assessed in a future paper.

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arXiv2024

Expected Impact of Rubin Observatory LSST on NEO Follow-up

We simulate and analyse the contribution of the Rubin Observatory Legacy Survey of Space and Time (LSST) to the rate of discovery of Near Earth Object (NEO) candidates, their submission rates to the NEO Confirmation page (NEOCP), and the resulting demands on the worldwide NEO follow-up observation system. We find that, when using current NEOCP listing criteria, Rubin will typically contribute ~129 new objects to the NEOCP each night in the first year, an increase of ~8x relative to present day. Only 8.3% of the objects listed for follow-up will be NEOs, with the primary contaminant being a background of yet undiscovered, faint, main belt asteroids (MBAs). We consider follow-up prioritisation strategies to lessen the impact on the NEO follow-up system. We develop an algorithm that predicts (with 68% accuracy) whether Rubin itself will self recover any given tracklet; external follow-up of such candidates can be de-prioritised. With this algorithm enabled, the follow-up list would be reduced to 64 NEO candidates per night (with ~8.4% purity). We propose additional criteria based on trailing, apparent magnitude, and ecliptic latitude to further prioritise follow-up. We hope observation planners and brokers will adopt some of these open-source algorithms, enabling the follow-up community to effectively keep up with the NEOCP in the early years of LSST.

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arXiv2023

The DECam Ecliptic Exploration Project (DEEP) II. Observational Strategy and Design

We present the DECam Ecliptic Exploration Project (DEEP) survey strategy including observing cadence for orbit determination, exposure times, field pointings and filter choices. The overall goal of the survey is to discover and characterize the orbits of a few thousand Trans-Neptunian Objects (TNOs) using the Dark Energy Camera (DECam) on the Cerro Tololo Inter-American Observatory (CTIO) Blanco 4 meter telescope. The experiment is designed to collect a very deep series of exposures totaling a few hours on sky for each of several 2.7 square degree DECam fields-of-view to achieve a magnitude of about 26.2 using a wide VR filter which encompasses both the V and R bandpasses. In the first year, several nights were combined to achieve a sky area of about 34 square degrees. In subsequent years, the fields have been re-visited to allow TNOs to be tracked for orbit determination. When complete, DEEP will be the largest survey of the outer solar system ever undertaken in terms of newly discovered object numbers, and the most prolific at producing multi-year orbital information for the population of minor planets beyond Neptune at 30 au.

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arXiv2023

The DECam Ecliptic Exploration Project (DEEP) III: Survey characterization and simulation methods

We present a detailed study of the observational biases of the DECam Ecliptic Exploration Project's (DEEP) B1 data release and survey simulation software that enables direct statistical comparisons between models and our data. We inject a synthetic population of objects into the images, and then subsequently recover them in the same processing as our real detections. This enables us to characterize the survey's completeness as a function of apparent magnitudes and on-sky rates of motion. We study the statistically optimal functional form for the magnitude, and develop a methodology that can estimate the magnitude and rate efficiencies for all survey's pointing groups simultaneously. We have determined that our peak completeness is on average 80\% in each pointing group, and our magnitude drops to $25\%$ of this value at $m_{25} = 26.22$. We describe the freely available survey simulation software and its methodology. We conclude by using it to infer that our effective search area for objects at 40 au is $14.8\deg^2$, and that our lack of dynamically cold distant objects means that there at most $8\times 10^3$ objects with $60 < a < 80$ au and absolute magnitudes $H \leq 8$.

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arXiv2023

The DECam Ecliptic Exploration Project (DEEP) VI: first multi-year observations of trans-Neptunian objects

We present the first set of trans-Neptunian objects (TNOs) observed on multiple nights in data taken from the DECam Ecliptic Exploration Project (DEEP). Of these 110 TNOs, 105 do not coincide with previously known TNOs and appear to be new discoveries. Each individual detection for our objects resulted from a digital tracking search at TNO rates of motion, using two to four hour exposure sets, and the detections were subsequently linked across multiple observing seasons. This procedure allows us to find objects with magnitudes $m_{VR} \approx 26$. The object discovery processing also included a comprehensive population of objects injected into the images, with a recovery and linking rate of at least $94\%$. The final orbits were obtained using a specialized orbit fitting procedure that accounts for the positional errors derived from the digital tracking procedure. Our results include robust orbits and magnitudes for classical TNOs with absolute magnitudes $H \sim 10$, as well as a dynamically detached object found at 76 au (semi-major axis $a\approx 77 \, \mathrm{au}$). We find a disagreement between our population of classical TNOs and the CFEPS-L7 three component model for the Kuiper belt.

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arXiv2023

Jupiter's Metastable Companions

Jovian co-orbitals share Jupiter's orbit in 1:1 mean motion resonance. This includes $>$10,000 so-called Trojan asteroids surrounding the leading (L4) and trailing (L5) Lagrange points, viewed as stable groups dating back to planet formation. Via a massive numerical study we identify for the first time some Trojans which are certainly only `metastable'; instead of being primordial, they are recent captures from heliocentric orbits into moderately long-lived (10 kyr - 100 Myr) metastable states that will escape back to the scattering regime. We have also identified (1) the first two jovian horseshoe co-orbitals that exist for many resonant libration periods, and (2) eight jovian quasi-satellites with metastable lifetimes of 4-130 kyr. Our perspective on the Trojan population is thus now more complex as Jupiter joins the other giant planets in having known metastable co-orbitals which are in steady-state equilibrium with the planet-crossing Centaur and asteroid populations, in agreement with theoretical estimates.

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arXiv2023

The DECam Ecliptic Exploration Project (DEEP): I. Survey description, science questions, and technical demonstration

We present here the DECam Ecliptic Exploration Project (DEEP), a three year NOAO/NOIRLab Survey that was allocated 46.5 nights to discover and measure the properties of thousands of trans-Neptunian objects (TNOs) to magnitudes as faint as VR~27, corresponding to sizes as small as 20 km diameter. In this paper we present the science goals of this project, the experimental design of our survey, and a technical demonstration of our approach. The core of our project is "digital tracking," in which all collected images are combined at a range of motion vectors to detect unknown TNOs that are fainter than the single exposure depth of VR~23 mag. Through this approach we reach a depth that is approximately 2.5 magnitudes fainter than the standard LSST "wide fast deep" nominal survey depth of 24.5 mag. DEEP will more than double the number of known TNOs with observational arcs of 24 hours or more, and increase by a factor of 10 or more the number of known small (<50 km) TNOs. We also describe our ancillary science goals, including measuring the mean shape distribution of very small main belt asteroids, and briefly outline a set of forthcoming papers that present further aspects of and preliminary results from the DEEP program.

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arXiv2022

Simulating the Legacy Survey of Space and Time stellar content with TRILEGAL

We describe a large simulation of the stars to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The simulation is based on the TRILEGAL code, which resorts to large databases of stellar evolutionary tracks, synthetic spectra, and pulsation models, added to simple prescriptions for the stellar density and star formation histories of the main structures of the Galaxy, to generate mock stellar samples through a population synthesis approach. The main bodies of the Magellanic Clouds are also included. A complete simulation is provided for single stars, down to the $r=27.5$ mag depth of the co-added wide-fast-deep survey images. A second simulation is provided for a fraction of the binaries, including the interacting ones, as derived with the BinaPSE module of TRILEGAL. We illustrate the main properties and numbers derived from these simulations, including: comparisons with real star counts; the expected numbers of Cepheids, long-period variables and eclipsing binaries; the crowding limits as a function of seeing and filter; the star-to-galaxy ratios, etc. Complete catalogs are accessible through the NOIRLab Astro Data Lab, while the stellar density maps are incorporated in the LSST metrics analysis framework (MAF).

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arXiv2021

Characterizing Sparse Asteroid Light Curves with Gaussian Processes

In the era of wide-field surveys like the Zwicky Transient Facility and the Rubin Observatory's Legacy Survey of Space and Time, sparse photometric measurements constitute an increasing percentage of asteroid observations, particularly for asteroids newly discovered in these large surveys. Follow-up observations to supplement these sparse data may be prohibitively expensive in many cases, so to overcome these sampling limitations, we introduce a flexible model based on Gaussian Processes to enable Bayesian parameter inference of asteroid time series data. This model is designed to be flexible and extensible, and can model multiple asteroid properties such as the rotation period, light curve amplitude, changing pulse profile, and magnitude changes due to the phase angle evolution at the same time. Here, we focus on the inference of rotation periods. Based on both simulated light curves and real observations from the Zwicky Transient Facility, we show that the new model reliably infers rotational periods from sparsely sampled light curves, and generally provides well-constrained posterior probability densities for the model parameters. We propose this framework as an intermediate method between fast, but very limited period detection algorithms and much more comprehensive, but computationally expensive shape modeling based on ray-tracing codes.

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arXiv2021

iCompare: A Package for Automated Comparison of Solar System Integrators

We present a tool for the comparison and validation of the integration packages suitable for Solar System dynamics. iCompare, written in Python, compares the ephemeris prediction accuracy of a suite of commonly-used integration packages (JPL/HORIZONS, OpenOrb, OrbFit at present). It integrates a set of test particles with orbits picked to explore both usual and unusual regions in Solar System phase space and compares the computed to reference ephemerides. The results are visualized in an intuitive dashboard. This allows for the assessment of integrator suitability as a function of population, as well as monitoring their performance from version to version (a capability needed for the Rubin Observatory's software pipeline construction efforts). We provide the code on GitHub with a readily runnable version in Binder (https://github.com/dirac-institute/iCompare).

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arXiv2021

Sifting Through the Static: Moving Object Detection in Difference Images

Trans-Neptunian Objects (TNOs) provide a window into the history of the Solar System, but they can be challenging to observe due to their distance from the Sun and relatively low brightness. Here we report the detection of 75 moving objects that we could not link to any other known objects, the faintest of which has a VR magnitude of $25.02 \pm 0.93$ using the KBMOD platform. We recover an additional 24 sources with previously-known orbits. We place constraints on the barycentric distance, inclination, and longitude of ascending node of these objects. The unidentified objects have a median barycentric distance of 41.28 au, placing them in the outer Solar System. The observed inclination and magnitude distribution of all detected objects is consistent with previously published KBO distributions. We describe extensions to KBMOD, including a robust percentile-based lightcurve filter, an in-line graphics processing unit (GPU) filter, new coadded stamp generation, and a convolutional neural network (CNN) stamp filter, which allow KBMOD to take advantage of difference images. These enchancements mark a significant improvement in the readiness of KBMOD for deployment on future big data surveys such as LSST.

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arXiv2021

Galactic Mass Estimates using Dwarf Galaxies as Kinematic Tracers

New mass estimates and cumulative mass profiles with Bayesian credible regions (c.r.) for the Milky Way (MW) are found using the Galactic Mass Estimator (GME) code and dwarf galaxy (DG) kinematic data from multiple sources. GME takes a hierarchical Bayesian approach to simultaneously estimate the true positions and velocities of the DGs, their velocity anisotropy, and the model parameters for the Galaxy's total gravitational potential. In this study, we incorporate meaningful prior information from past studies and simulations. The prior distributions for the physical model are informed by the results of Eadie & Juric (2019), which used globular clusters instead of DGs, as well as by the subhalo distributions of the Ananke Gaia-like surveys from Feedback In Realistic Environments-2 (Fire-2) cosmological simulations (see Sanderson et al. 2020). Using DGs beyond 45 kpc, we report median and 95% c.r estimates for $r_{200}$ = 212.8 (191.12,238.44) kpc, and for the total enclosed mass $M_{200}$ = 1.19 (0.87,1.68)$\times10^{12}M_{\odot}$ (adopting $Δ_c=200$). Median mass estimates at specific radii are also reported (e.g., $M(<50\text{ kpc})=0.52\times10^{12}M_{\odot}$ and $M(100\text{ kpc})=0.78\times10^{12}M_{\odot}$). Estimates are comparable to other recent studies using GAIA DR2 and DGs, but notably different from the estimates of Eadie & Juric (2019). We perform a sensitivity analysis to investigate whether individual DGs and/or a more massive Large Magellanic Cloud (LMC) on the order of $10^{11}M_{\odot}$ may be affecting our mass estimates. We find possible supporting evidence for the idea that some DGs are affected by a massive LMC and are not in equilibrium with the MW.

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arXiv2021

THOR: An Algorithm for Cadence-Independent Asteroid Discovery

We present "Tracklet-less Heliocentric Orbit Recovery" (THOR), an algorithm for linking of observations of Solar System objects across multiple epochs that does not require intra-night tracklets or a predefined cadence of observations within a search window. By sparsely covering regions of interest in the phase space with "test orbits", transforming nearby observations over a few nights into the co-rotating frame of the test orbit at each epoch, and then performing a generalized Hough transform on the transformed detections followed by orbit determination (OD) filtering, candidate clusters of observations belonging to the same objects can be recovered at moderate computational cost and little to no constraints on cadence. We validate the effectiveness of this approach by running on simulations as well as on real data from the Zwicky Transient Facility (ZTF). Applied to a short, 2-week, slice of ZTF observations, we demonstrate THOR can recover 97.4% of all previously known and discoverable objects in the targeted ($a > 1.7$ au) population with 5 or more observations and with purity between 97.7% and 100%. This includes 10 likely new discoveries, and a recovery of an $e \sim 1$ comet C/2018 U1 (the comet would have been a ZTF discovery had THOR been running in 2018 when the data were taken). The THOR package and demo Jupyter notebooks are open source and available at https://github.com/moeyensj/thor.

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