arXiv subjects

Peter Vereš

Publications and source records attributed to Peter Vereš.

At least 19 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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arXiv2025

Upper Limit on the Non-Gravitational Acceleration and Lower Limits on the Nucleus Mass and Diameter of 3I/ATLAS

We use astrometric data on 3I/ATLAS compiled by the Minor Planet Center from May 15 to September 23, 2025, and derive an upper limit on any statistically significant deviation from the best-fit gravity-based trajectory. The residuals imply that the non-gravitational acceleration is smaller than $\sim 3 \times 10^{-10}\,{\rm au\,d^{-2}}$. Based on the total mass-loss rate and outflow speed inferred from JWST data on August 6, 2025, we derive lower limits on the mass and diameter of 3I/ATLAS of $3.3 \times 10^{16}\,{\rm g}$ and $5\,{\rm km}$, respectively.

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arXiv2025

Apache Point rapid response characterization of primitive imminent impactor 2024 RW$_1$

Imminent impactors may be detected only a few hours before their impact with Earth, providing a brief opportunity to characterize them before impact. We describe the characterization of imminent impactor 2024 RW$_1$, which was discovered by the Catalina Sky Survey on 2024 September 4 at 05:43 UTC, before it entered the atmosphere near the northern Philippines at 16:39 UTC. We observed 2024 RW$_1$ with the Astrophysical Research Consortium Telescope Imaging Camera on the Apache Point Astrophysical Research Consortium's 3.5-m telescope on 2024 September 4 10:16 UTC. We obtained g, r, i, and z photometry of 2024 RW$_1$, yielding color indices of g-r = 0.47$\pm$0.04, r-i = 0.13$\pm$0.04, i-z = -0.11$\pm$0.07, and g-i = 0.60$\pm$0.04, corresponding to a spectral slope of 0.67$\pm$0.40~$\%$/100 nm. The closest match to an asteroid spectral type is with B-type asteroids from the C-complex. We detect variations in the time series photometry of the asteroid with an amplitude of $\sim$0.75, and a double-peaked rotation period of $\sim$1900 s. Assuming a visible albedo of 0.07$\pm$0.03, a density of $\sim$1500 kg/m$^3$, and a calculated absolute magnitude of 30.92$\pm$0.05, we estimate that the asteroid has a diameter of 3.3$\pm$0.7 m and a total mass of $\sim$28,000 kg. Comparing our astrometric orbital solutions to NEOMOD3, the most likely source of 2024 RW$_1$ is the 3:1 main belt mean motion resonance (77\% probability) followed by the $ν_6$ resonance (13\% probability), consistent with its organic B-type nature.

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arXiv2025

Improving the discovery of near-Earth objects with machine-learning methods

We present a comprehensive analysis of the digest2 parameters for candidates of the Near-Earth Object Confirmation Page (NEOCP) that were reported between 2019 and 2024. Our study proposes methods for significantly reducing the inclusion of non-NEO objects on the NEOCP. Despite the substantial increase in near-Earth object (NEO) discoveries in recent years, only about half of the NEOCP candidates are ultimately confirmed as NEOs. Therefore, much observing time is spent following up on non-NEOs. Furthermore, approximately 11% of the candidates remain unconfirmed because the follow-up observations are insufficient. These are nearly 600 cases per year. To reduce false positives and minimize wasted resources on non-NEOs, we refine the posting criteria for NEOCP based on a detailed analysis of all digest2 scores. We investigated 30 distinct digest2 parameter categories for candidates that were confirmed as NEOs and non-NEOs. From this analysis, we derived a filtering mechanism based on selected digest2 parameters that were able to exclude 20% of the non-NEOs from the NEOCP while maintaining a minimal loss of true NEOs. We also investigated the application of four machine-learning (ML) techniques, that is, the gradient-boosting machine (GBM), the random forest (RF) classifier, the stochastic gradient descent (SGD) classifier, and neural networks (NN) to classify NEOCP candidates as NEOs or non-NEOs. Based on digest2 parameters as input, our ML models achieved a precision of approximately 95% in distinguishing between NEOs and non-NEOs. Results. Combining the digest2 parameter filter with an ML-based classification model, we demonstrate a significant reduction in non-NEOs on the NEOCP that exceeds 80%, while limiting the loss of NEO discovery tracklets to 5.5%. Importantly, we show that most follow-up tracklets of initially misclassified NEOs are later correctly identified as NEOs.

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arXiv2024

Machine Learning Methods for Automated Interstellar Object Classification with LSST

The Legacy Survey of Space and Time, to be conducted with the Vera C. Rubin Observatory, is poised to revolutionize our understanding of the Solar System by providing an unprecedented wealth of data on various objects, including the elusive interstellar objects (ISOs). Detecting and classifying ISOs is crucial for studying the composition and diversity of materials from other planetary systems. However, the rarity and brief observation windows of ISOs, coupled with the vast quantities of data to be generated by LSST, create significant challenges for their identification and classification. This study aims to address these challenges by exploring the application of machine learning algorithms to the automated classification of ISO tracklets in simulated LSST data. We employed various machine learning algorithms, including random forests (RFs), stochastic gradient descent (SGD), gradient boosting machines (GBMs), and neural networks (NNs), to classify ISO tracklets in simulated LSST data. We demonstrate that GBM and RF algorithms outperform SGD and NN algorithms in accurately distinguishing ISOs from other Solar System objects. RF analysis shows that many derived Digest2 values are more important than direct observables in classifying ISOs from the LSST tracklets. The GBM model achieves the highest precision, recall, and F1 score, with values of 0.9987, 0.9986, and 0.9987, respectively. These findings lay the foundation for the development of an efficient and robust automated system for ISO discovery using LSST data, paving the way for a deeper understanding of the materials and processes that shape planetary systems beyond our own. The integration of our proposed machine learning approach into the LSST data processing pipeline will optimize the survey's potential for identifying these rare and valuable objects, enabling timely follow-up observations and further characterization.

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arXiv2024

Debiasing astro-Photometric Observations with Corrections Using Statistics (DePhOCUS)

Photometric measurements allow the determination of an asteroid's absolute magnitude, which often represents the sole means to infer its size. Photometric observations can be obtained in a variety of filters that can be unique to a specific observatory. Those observations are then calibrated into specific bands with respect to reference star catalogs. In order to combine all the different measurements for evaluation, photometric observations need to be converted to a common band, typically V-band. Current band-correction schemes in use by IAU's Minor Planet Center, JPL's Center for Near Earth Object Studies and ESA's NEO Coordination Centre use average correction values for the apparent magnitude derived from photometry of asteroids as the corrections are dependent on the typically unknown spectrum of the object to be corrected. By statistically analyzing the photometric residuals of asteroids, we develop a new photometric correction scheme that does not only consider the band, but also accounts for reference catalog and observatory. We describe a new statistical photometry correction scheme for asteroid observations with debiased corrections. Testing this scheme on a reference group of asteroids, we see a 36% reduction in the photometric residuals. Moreover, the new scheme leads to a more accurate and debiased determination of the H-G magnitude system and, in turn, to more reliable inferred sizes. We discuss the significant shift in the corrections with this "DePhOCUS" debiasing system, its limitations, and the impact for photometric and physical properties of all asteroids, especially Near-Earth Objects.

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arXiv2023

Improvement of digest2 NEO Classification Code -- utilizing the Astrometry Data Exchange Standard

We describe enhancements to the digest2 software, a short-arc orbit classifier for heliocentric orbits. Digest2 is primarily used by the Near-Earth Object (NEO) community to flag newly discovered objects for a immediate follow-up and has been a part of NEO discovery process for more than 15 years. We have updated the solar system population model used to weight the digest2 score according to the 2023 catalog of known solar system orbits and extended the list of mean uncertainties for 140 observatory codes. Moreover, we have added Astrometry Data Exchange Standard (ADES) input format support to digest2, which provides additional information for the astrometry, such as positional uncertainties for each detection. The digest2 code was also extended to read the roving observer astrometric format as well as the ability to compute a new parameter from the provided astrometric uncertainties ($RMS'$) that can serve as an indicator of in-tracklet curvature when compared with tracklet's great-circle fit RMS. Comparison with the previous version of digest2 confirmed the improvement in accuracy of NEO identification and found that using ADES XML input significantly reduces the computation time of the digest2.

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arXiv2023

Dark Comets? Unexpectedly Large Nongravitational Accelerations on a Sample of Small Asteroids

We report statistically significant detections of non-radial nongravitational accelerations based on astrometric data in the photometrically inactive objects 1998 KY$_{26}$, 2005 VL$_1$, 2016 NJ$_{33}$, 2010 VL$_{65}$, 2016 RH$_{120}$, and 2010 RF$_{12}$. The magnitudes of the nongravitational accelerations are greater than those typically induced by the Yarkovsky effect and there is no radiation-based, non-radial effect that can be so large. Therefore, we hypothesize that the accelerations are driven by outgassing, and calculate implied H$_2$O production rates for each object. We attempt to reconcile outgassing induced acceleration with the lack of visible comae or photometric activity via the absence of surface dust and low levels of gas production. Although these objects are small and some are rapidly rotating, surface cohesive forces are stronger than the rotational forces and rapid rotation alone cannot explain the lack of surface debris. It is possible that surface dust was removed previously, perhaps via outgassing activity that increased the rotation rates to their present day value. We calculate dust production rates of order $\sim10^{-4}$ g s$^{-1}$ in each object assuming that the nuclei are bare, within the upper limits of dust production from a sample stacked image of 1998 KY$_{26}$ of $\dot{M}_{\rm Dust}<0.2$ g s$^{-1}$. This production corresponds to brightness variations of order $\sim0.0025\%$, which are undetectable in extant photometric data. We assess the future observability of each of these targets, and find that the orbit of 1998 KY$_{26}$ -- which is also the target for the extended Hayabusa2 mission -- exhibits favorable viewing geometry before 2025.

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arXiv2019

The digest2 NEO Classification Code

We describe the digest2 software package, a fast, short-arc orbit classifier for small Solar System bodies. The digest2 algorithm has been serving the community for more than 13 years. The code provides a score, D2, which represents a pseudo-probability that a tracklet belongs to a given Solar System orbit type. digest2 is primarily used as a classifier for Near-Earth Object (NEO) candidates, to identify those to be prioritized for follow-up observation. We describe the historical development of digest2 and demonstrate its use on real and synthetic data. We find that digest2 can accurately and precisely distinguish NEOs from non- NEOs. At the time of detection, 14% of NEO tracklets and 98.5% of non-NEOs tracklets have D2 below the critical value of D2 = 65. 94% of our simulated NEOs achieved the maximum D2 = 100 and 99.6% of NEOs achieved $D2 \ge 65$ at least once during the simulated 10-year timeframe. We demonstrate that D2 varies as a function of time, rate of motion, magnitude and sky-plane location, and show that NEOs tend to have lower D2 at low Solar elongations close to the ecliptic. We use our findings to recommend future development directions for the digest2 code.

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arXiv2018

Unconfirmed Near-Earth Objects

We studied the Near-Earth Asteroid (NEA) candidates posted on the Minor Planet Center's Near-Earth Object Confirmation Page (NEOCP) between years 2013 and 2016. Out of more than 17,000 NEA candidates, while the majority became either new discoveries or were associated with previously known objects, about 11% were unable to be followed-up or confirmed. We further demonstrate that of the unconfirmed candidates, 926+/-50 are likely to be NEAs, representing 18% of discovered NEAs in that period. Only 11% (~93) of the unconfirmed NEA candidates were large (having absolute magnitude H<22). To identify the reasons why these NEAs were not recovered, we analyzed those from the most prolific asteroid surveys: Pan-STARRS, the Catalina Sky Survey, the Dark Energy Survey, and the Space Surveillance Telescope. We examined the influence of plane-of-sky positions and rates of motion, brightnesses, submission delays, and computed absolute magnitudes, as well as correlations with the phase of the moon and seasonal effects. We find that delayed submission of newly discovered NEA candidate to the NEOCP drove a large fraction of the unconfirmed NEA candidates. A high rate of motion was another significant contributing factor. We suggest that prompt submission of suspected NEA discoveries and rapid response to fast moving targets and targets with fast growing ephemeris uncertainty would allow better coordination among dedicated follow-up observers, decrease the number of unconfirmed NEA candidates, and increase the discovery rate of NEAs.

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arXiv2017

Near-Earth Object Orbit Linking with the Large Synoptic Survey Telescope

We have conducted a detailed simulation of LSST's ability to link near-Earth and main belt asteroid detections into orbits. The key elements of the study were a high-fidelity detection model and the presence of false detections in the form of both statistical noise and difference image artifacts. We employed the Moving Object Processing System (MOPS) to generate tracklets, tracks and orbits with a realistic detection density for one month of the LSST survey. The main goals of the study were to understand whether a) the linking of Near-Earth Objects (NEOs) into orbits can succeed in a realistic survey, b) the number of false tracks and orbits will be manageable, and c) the accuracy of linked orbits would be sufficient for automated processing of discoveries and attributions. We found that the overall density of asteroids was more than 5000 per LSST field near opposition on the ecliptic, plus up to 3000 false detections per field in good seeing. We achieved 93.6% NEO linking efficiency for H<22 on tracks composed of tracklets from at least three distinct nights within a 12-day interval. The derived NEO catalog was comprised of 96% correct linkages. Less than 0.1% of orbits included false detections, and the remainder of false linkages stemmed from main belt confusion, which was an artifact of the short time span of the simulation. The MOPS linking efficiency can be improved by refined attribution of detections to known objects and by improved tuning of the internal kd-tree linking algorithms.

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arXiv2017

High-fidelity Simulations of the Near-Earth Object Search Performance of the Large Synoptic Survey Telescope

We perform high fidelity simulations of a wide-field telescopic survey searching for Near-Earth Objects (NEO) larger than 140\,m, focusing on the observational and detection model, detection efficiency and accuracy. As a test survey we select the Large Synoptic Survey Telescope. We use its proposed pointings for a 10-year mission and model the detection of near-Earth objects in the fields. We discuss individual model parameters for magnitude losses, vignetting, fading, asteroid rotation and colors, fill factor, limiting magnitude, rate of motion, field shape and rotation and survey patterns and we assess results in terms of the cumulative completeness of the detected population as a function of size and time. Additionally, we examine the sources of modeling uncertainty and derive the overall NEO population completeness for the baseline LSST survey to be $55\pm5$% for NEOs with absolute magnitude brighter than 22. Including already discovered objects and ongoing surveys, the population completeness at the end of the LSST baseline survey should reach $\sim 77\%$.

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arXiv2017

Statistical Analysis of Astrometric Errors for the Most Productive Asteroid Surveys

We performed a statistical analysis of the astrometric errors for the major asteroid surveys. We analyzed the astrometric residuals as a function of observation epoch, observed brightness and rate of motion, finding that astrometric errors are larger for faint observations and some stations improved their astrometric quality over time. Based on this statistical analysis we develop a new weighting scheme to be used when performing asteroid orbit determination. The proposed weights result in ephemeris predictions that can be conservative by a factor as large as 1.5. However, the new scheme is more robust with respect to outliers and better handles faint detections.

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arXiv2016

The size-frequency distribution of H>13 NEOs and ARM targets detected by Pan-STARRS1

We determine the absolute magnitude (H) distribution (or size-frequency distribution, SFD; $N(H) \propto 10^{αH}$ where $α$ is the slope of the distribution) for near-Earth objects (NEO) with $13 22$. There is also another change in slope from steep to shallow around H=27. The three ARM target candidates detected by Pan-STARRS1 in one year of surveying have a corrected SFD with slope $α= 0.40^{+0.33}_{-0.45}$. We also show that the window for follow up observations of small (H$\gtrsim$22) NEOs with the NASA IRTF telescope and Arecibo and Goldstone radars are extremely short - on order of days, and procedures for fast response must be implemented in order to measure physical characteristics of small Earth-approaching objects. CFHT's MegaCam and Pan-STARRS1 have longer observing windows and are capable of following-up more NEOs due to their deeper limiting magnitudes and wider fields of view.

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arXiv2015

Absolute magnitudes and slope parameters for 250,000 asteroids observed by Pan-STARRS PS1 - preliminary results

We present the results of a Monte Carlo technique to calculate the absolute magnitudes (H) and slope parameters (G) of about 240000 asteroids observed by the Pan-STARRS1 telescope during the first 15 months of its 3-year all-sky survey mission. The system's exquisite photometry with photometric errors < 0.04 mag, and well-defined filter and photometric system, allowed us to derive accurate H and G even with a limited number of observations and restricted range in phase angles. Our Monte Carlo method simulates each asteroid's rotation period, amplitude and color to derive the most-likely H and G, but its major advantage is in estimating realistic statistical+systematic uncertainties and errors on each parameter. The method was tested by comparison with the well-established and accurate results for about 500 asteroids provided by Pravec et al. (2012) and then applied to determining H and G for the Pan-STARRS1 asteroids using both the Muinonen et al. (2010) and Bowell et al. (1989) phase functions. Our results confirm the bias in MPC photometry discovered by (Juric et al. 2002).

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arXiv2014

Observational Constraints on the Catastrophic Disruption Rate of Small Main Belt Asteroids

We have calculated 90% confidence limits on the steady-state rate of catastrophic disruptions of main belt asteroids in terms of the absolute magnitude at which one catastrophic disruption occurs per year (HCL) as a function of the post-disruption increase in brightness (delta m) and subsequent brightness decay rate (tau). The confidence limits were calculated using the brightest unknown main belt asteroid (V = 18.5) detected with the Pan-STARRS1 (Pan-STARRS1) telescope. We measured the Pan-STARRS1's catastrophic disruption detection efficiency over a 453-day interval using the Pan-STARRS moving object processing system (MOPS) and a simple model for the catastrophic disruption event's photometric behavior in a small aperture centered on the catastrophic disruption event. Our simplistic catastrophic disruption model suggests that delta m = 20 mag and 0.01 mag d-1 < tau < 0.1 mag d-1 which would imply that H0 = 28 -- strongly inconsistent with H0,B2005 = 23.26 +/- 0.02 predicted by Bottke et al. (2005) using purely collisional models. We postulate that the solution to the discrepancy is that > 99% of main belt catastrophic disruptions in the size range to which this study was sensitive (100 m) are not impact-generated, but are instead due to fainter rotational breakups, of which the recent discoveries of disrupted asteroids P/2013 P5 and P/2013 R3 are probable examples. We estimate that current and upcoming asteroid surveys may discover up to 10 catastrophic disruptions/year brighter than V = 18.5.

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arXiv2014

Density, porosity and magnetic susceptibility of the Košice meteorite shower and homogeneity of its parent meteoroid

Bulk and grain density, porosity, and magnetic susceptibility of 67 individuals of Košice H chondrite fall were measured. The mean bulk and grain densities were determined to be 3.43 g/cm$^\text{3}$ with standard deviation (s.d.) of 0.11 g/cm$^\text{3}$ and 3.79 g/cm$^\text{3}$ with s.d. 0.07 g/cm$^\text{3}$, respectively. Porosity is in the range from 4.2 to 16.1%. The logarithm of the apparent magnetic susceptibility (in 10$^\text{-9}$ m$^\text{3}$/kg) shows narrow distribution from 5.17 to 5.49 with mean value at 5.35 with s.d. 0.08. These results indicate that all studied Košice meteorites are of the same composition down to ~g scale without presence of foreign (non-H) clasts and are similar to other H chondrites. Košice is thus a homogeneous meteorite fall derived from a homogeneous meteoroid.

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arXiv2014

The effect of parallax and cadence on asteroid impact probabilities and warning times

We study the time evolution of the impact probability for synthetic but realistic impacting and close approaching asteroids detected in a simulated all-sky survey. We use the impact probability to calculate the impact warning time as the time interval between when an object reaches a Palermo Scale value of -2 and when it impacts Earth. A simple argument shows that warning time ~ D^x with the exponent in the range [1.0,1.5] and our derived value was $x=1.3\pm0.1$. The low-precision astrometry from the single simulated all-sky survey could require many days or weeks to establish an imminent impact for asteroids >100m diameter that are discovered far from Earth. Most close approaching asteroids are quickly identified as not being impactors but a size-dependent percentage, even for those >50m diameter, have a persistent impact probability of >10^{-6} on the day of closest approach. Thus, a single all-sky survey can be of tremendous value in identifying Earth impacting and close approaching asteroids in advance of their closest approach but it can not solve the problem on its own: high-precision astrometry from other optical or radar systems is necessary to rapidly establish an object as an impactor or close approacher. We show that the parallax afforded by surveying the sky from two sites is only of benefit for a small fraction of the smallest objects detected within a couple days before impact: probably not enough to justify the increased operating costs of a 2-site survey. Finally, the survey cadence within a fixed time span is relatively unimportant to the impact probability calculation. We tested three different reasonable cadences and found that one provided ~10x higher (better) value for the impact probability on the discovery night for the smallest (10m diameter) objects but the consequences on the overall impact probability calculation is negligible.

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