arXiv subjects

M. Granvik

Publications and source records attributed to M. Granvik.

17 recordsLinked to original sources

arXiv2026

Euclid: Asteroid rotation periods from the Euclid Ecliptic Survey

The Euclid Ecliptic Survey was conducted during the calibration phase of the mission, 23-31 December 2023, as a campaign to study Solar System objects. We used data from this survey to analyse more than 23 000 appeareances of 2321 known asteroids. Due to their high apparent angular motion relative to the background stars (5-$60^{\prime\prime}\,\mathrm{h}^{-1}$), these objects appear as streaks in VIS long-exposure images. We set out to estimate their spin periods, since only $7\%$ of them have periods published in the literature. We used multiple apertures along each streak to increase the time resolution of our light curves. Our method combines a Lomb-Scargle approach with a Markov chain Monte Carlo (MCMC) algorithm to characterise the posterior distributions. Some asteroids show multimodality in the MCMC search, indicating period aliases; in these cases, we report all aliases and their likelihoods. We validate our pipeline by comparing our fitted periods with 48 published periods, including period harmonics. We find that $44\%$ of our periods are within $1\%$ of those published and $98\%$ are within $15\%$, and we establish that with $98\%$ confidence the best solution can be found among the first three aliases. All reliable periods reported agree with our current understanding of the spin-period distribution for asteroids. We find 16 periods below the spin barrier of 2.2 h with absolute magnitudes below 19, and thus 16 candidate super-fast rotators. We provide light curves for all 2321 objects observed and 889 high-quality periods in an open-access catalogue. The asteroids with reported periods include five Mars crossers, four Cybeles, four Hildas, three Hungarias, and 877 asteroids in other regions of the main belt. Our results represent the first batch of spin periods extracted from Euclid light curves and include the first-ever period measurements for $93\%$ of the objects.

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arXiv2026

Machine Learning Assisted NEO Discovery and Polarimetric Characterisation with Astronomical Surveys

We are a group of over two dozen astronomers, computer scientists, data scientists and digital Big Data research platform experts at 11 universities and research institutes in South Africa and Europe. We study Near-Earth Objects (NEOs) for Planetary Defence and scientific purposes. We present our research and development programme for algorithms and digital data analysis platforms for machine learning-assisted NEO discovery and polarimetric characterisation in astronomical surveys. Typically, this is serendipitous because these surveys are designed for galactic and extragalactic science.

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arXiv2026

Origin of asteroid (469219) Kamo`oalewa: the main asteroid belt or the Giordano Bruno crater on the Moon?

Asteroid Kamo`oalewa is the target of the Tianwen-2 sample-return mission by CNSA. Because of its orbit and its spectral properties, it was proposed that Kamo`oalewa originated from the Moon as impact ejecta, possibly from the Giordano Bruno crater. We aim at estimating the relative contribution of Kamo`oalewa-like objects originating from the general near-Earth asteroid (NEA) population which originated in the main asteroid belt, and compare it with the relative contribution of Giordano Bruno ejecta. We first estimate the average fraction of quasi-satellite orbits at any given time. By using recently developed NEA population models, we extract the expected number of Earth co-orbitals of the same size of Kamo`oalewa, and then get an estimate of the average number of Kamo`oalewa-like objects using the fraction computed before. Similarly, we obtain an estimate for the number of Kamo`oalewa-like objects that may originate as ejecta from the Giordano Bruno impact. We also performed survey simulations to estimate their efficiency in the detection of Kamo`oalewa-like objects. We found that the main belt accounts for 1.23 \pm 0.13 Kamo`oalewa-like objects on average. The expected number of Kamo`oalewa-like objects originated as Giordano Bruno ejecta is 0.042, which is more than order of magnitude smaller. We found a discovery efficiency of Earth quasi-satellites between 95% and 70% for absolute magnitude between 22 and 25 for the Pan-STARRS survey, and population models show that this is in agreement with the known population. The Vera Rubin Observatory should reach an efficiency of 92% down to absolute magnitude 25. These estimates show that population models of NEAs are capable to account for Kamo`oalewa-like objects, thus supporting the hypothesis that that Kamo'oalewa originated from the main belt. This will be further investigated by the in-situ exploration of the Tianwen-2 mission.

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arXiv2025

Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

The ESA Euclid mission will survey more than 14,000 deg$^2$ of the sky in visible and near-infrared wavelengths, mapping the extra-galactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 deg from the ecliptic, it should allow for the detection of more than about $10^5$ Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1-10 arcsec/h, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on Sourcextractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.

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arXiv2024

The Palomar twilight survey of 'Ayl\'o'chaxnim, Atiras, and comets

Near-sun sky twilight observations allow for the detection of asteroid interior to the orbit of Venus (Aylos), the Earth (Atiras), and comets. We present the results of observations with the Palomar 48-inch telescope (P48)/Zwicky Transient Facility (ZTF) camera in 30 s r-band exposures taken during evening astronomical twilight from 2019 Sep 20 to 2022 March 7 and during morning astronomical twilight sky from 2019 Sep 21 to 2022 Sep 29. More than 46,000 exposures were taken in evening and morning astronomical twilight within 31 to 66 degrees from the Sun with an r-band limiting magnitude between 18.1 and 20.9. The twilight pointings show a slight seasonal dependence in limiting magnitude and ability to point closer towards the Sun, with limiting magnitude slightly improving during summer. In total, the one Aylo, (594913) 'Ayl\'o'chaxnim, and 4 Atiras, 2020 OV1, 2021 BS1, 2021 PB2, and 2021 VR3, were discovered in evening and morning twilight observations. Additional twilight survey discoveries also include 6 long-period comets: C/2020 T2, C/2020 V2, C/2021 D2, C/2021 E3, C/2022 E3, and C/2022 P3, and two short-period comets: P/2021 N1 and P/2022 P2 using deep learning comet detection pipelines. The P48/ZTF twilight survey also recovered 11 known Atiras, one Aylo, three short-period comes, two long-period comets, and one interstellar object. Lastly, the Vera Rubin Observatory will conduct a twilight survey starting in its first year of operations and will cover the sky within 45 degrees of the Sun. Twilight surveys such as those by ZTF and future surveys will provide opportunities for discovering asteroids inside the orbits of Earth and Venus.

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arXiv2024

Object classification with Convolutional Neural Networks: from KiDS to Euclid

Large-scale imaging surveys have grown about 1000 times faster than the number of astronomers in the last 3 decades. Using Artificial Intelligence instead of astronomer's brains for interpretative tasks allows astronomers to keep up with the data. We give a progress report on using Convolutional Neural Networks (CNNs) to classify three classes of rare objects (galaxy mergers, strong gravitational lenses and asteroids) in the Kilo-Degree Survey (KiDS) and the Euclid Survey.

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arXiv2023

Euclid: Identification of asteroid streaks in simulated images using deep learning

Up to 150000 asteroids will be visible in the images of the ESA Euclid space telescope, and the instruments of Euclid offer multiband visual to near-infrared photometry and slitless spectra of these objects. Most asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the StreakDet software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25-0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.

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arXiv2023

Optical spectropolarimetry of binary asteroid Didymos-Dimorphos before and after the DART impact

We have monitored the Didymos-Dimorphos binary asteroid in spectropolarimetric mode in the optical range before and after the DART impact. The ultimate goal was to obtain constraints on the characteristics of the ejected dust for modelling purposes. Before impact, Didymos exhibited a linear polarization rapidly increasing with phase angle, reaching a level of about 5% in the blue and about 4.5 in the red. The shape of the polarization spectrum was anti-correlated with that of its reflectance spectrum, which appeared typical of an S-class asteroid. After impact, the level of polarization dropped by about 1 percentage point (pp) in the blue band and about 0.5 pp in the red band, then continued to linearly increase with phase angle, with a slope similar to that measured prior to impact. The polarization spectra, once normalised by their values at an arbitrary wavelength, show very little or no change over the course of all observations, before and after impact. The lack of any remarkable change in the shape of the polarization spectrum after impact suggests that the way in which polarization varies with wavelength depends on the composition of the scattering material, rather than on its structure, be this a surface or a debris cloud.

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arXiv2022

Isolating the mechanisms for asteroid surface refreshing

Evidence is seen for young, fresh surfaces among Near-Earth and Main-Belt asteroids even though space-weathering timescales are shorter than the age of the surfaces. A number of mechanisms have been proposed to refresh asteroid surfaces on short timescales, such as planetary encounters, YORP spinup, thermal degradation, and collisions. Additionally, other factors such as grain size effects have been proposed to explain the existence of these "fresh-looking" spectra. To investigate the role each of these mechanisms may play, we collected a sample of visible and near-infrared spectra of 477 near-Earth and Mars Crosser asteroids with similar sizes and compositions - all with absolute magnitude H > 16 and within the S-complex and having olivine to pyroxene (ol/(ol+opx)) ratios > 0.65. We taxonomically classify these objects in the Q (fresh) and S (weathered) classes. We find four trends in the Q/S ratio: 1) previous work demonstrated the Q/S ratio increases at smaller sizes down to H<16, but we find a sharp increase near H=19 after which the ratio decreases monotonically 2) in agreement with many previous studies, the Q/S ratio increases with decreasing perihelion distance, and we find it is non-zero for larger perihelia greater than 1.2AU, 3) as a new finding our work reveals the Q/S ratio has a sharp, significant peak near 5 degrees orbital inclination, and 4) we confirm previous findings that the Q/S ratio is higher for objects that have the possibility of encounter with Earth and Venus versus those that don't, however this finding cannot be distinguished from the perihelion trend. No single resurfacing mechanism can explain all of these trends, so multiple mechanisms are required. It is likely that a combination of all four resurfacing mechanisms are needed to account for all observational trends.

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arXiv2022

The discovery and characterization of a kilometre sized asteroid inside the orbit of Venus

Near-Earth asteroid population models predict the existence of bodies located inside the orbit of Venus. Despite searches up to the end of 2019, none had been found. We report discovery and follow-up observations of (594913) 'Ayl\'o'chaxnim, an asteroid with an orbit entirely interior to Venus. (594913) 'Ayl\'o'chaxnim has an aphelion distance of ~0.65 au, is ~2 km in diameter and is red in colour. The detection of such a large asteroid inside the orbit of Venus is surprising given their rarity according to near-Earth asteroid population models. As the first officially numbered and named asteroid located entirely within the orbit of Venus, we propose that the class of interior to Venus asteroids be referred to as 'Ayl\'o'chaxnim asteroids.

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arXiv2020

Euclid: Identification of asteroid streaks in simulated images using StreakDet software

The ESA Euclid space telescope could observe up to 150 000 asteroids as a side product of its primary cosmological mission. Asteroids appear as trailed sources, that is streaks, in the images. Owing to the survey area of 15 000 square degrees and the number of sources, automated methods have to be used to find them. Euclid is equipped with a visible camera, VIS (VISual imager), and a near-infrared camera, NISP (Near-Infrared Spectrometer and Photometer), with three filters. We aim to develop a pipeline to detect fast-moving objects in Euclid images, with both high completeness and high purity. We tested the StreakDet software to find asteroids from simulated Euclid images. We optimized the parameters of StreakDet to maximize completeness, and developed a post-processing algorithm to improve the purity of the sample of detected sources by removing false-positive detections. StreakDet finds 96.9% of the synthetic asteroid streaks with apparent magnitudes brighter than 23rd magnitude and streak lengths longer than 15 pixels ($10\,{\rm arcsec\,h^{-1}}$), but this comes at the cost of finding a high number of false positives. The number of false positives can be radically reduced with multi-streak analysis, which utilizes all four dithers obtained by Euclid. StreakDet is a good tool for identifying asteroids in Euclid images, but there is still room for improvement, in particular, for finding short (less than 13 pixels, corresponding to 8$\,{\rm arcsec\,h^{-1}}$) and/or faint streaks (fainter than the apparent magnitude of 23).

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arXiv2020

Potential asteroid discoveries by the ESA Gaia mission: Results from follow-up observations

Since July 2014, the ESA Gaia mission has been surveying the entire sky down to magnitude 20.7 in the visible. In addition to the millions of stars, thousands of Solar System Objects (SSOs) are observed daily. By comparing their positions to those of known objects, a daily processing pipeline filters known objects from potential discoveries. However, owing to Gaia's specific scanning law designed for stars, potential newly discovered moving objects are characterized by very few observations, acquired over a limited time. This aspect was recognized early in the design of the Gaia data processing. A daily processing pipeline dedicated to these candidate discoveries was set up to release calls for observations to a network of ground-based telescopes. Their aim is to acquire follow-up astrometry and to characterize these objects. From the astrometry measured by Gaia, preliminary orbital solutions are determined, allowing to predict the position of these potentially new discovered objects in the sky accounting for the large parallax between Gaia and the Earth (separated by 0.01 au). A specific task within the Gaia Consortium has been responsible for the distribution of requests for follow-up observations of potential Gaia SSO discoveries. Since late 2016, these calls for observations (called alerts) are published daily via a Web interface, freely available to anyone world-wide. Between November 2016 and July 2020, over 1700 alerts have been published, leading to the successful recovery of more than 200 objects. Among those, six have provisional designation assigned with the Gaia observations, the others being previously known objects with poorly characterized orbits, precluding identification at the time of Gaia observations. There is a clear trend for objects with a high inclination to be unidentified, revealing a clear bias in the current census of SSOs against high inclination populations.

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arXiv2019

Asteroid mass estimation with the robust adaptive Metropolis algorithm

The bulk density of an asteroid informs us about its interior structure and composition. To constrain the bulk density one needs an estimate for the mass of the asteroid. The mass is estimated by analyzing an asteroid's gravitational interaction with another object, such as another asteroid during a close encounter. An estimate for the mass has typically been obtained with linearized least-squares methods despite the fact that this family of methods is not able to properly describe non-Gaussian parameter distributions. In addition, the uncertainties reported for asteroid masses in the literature are sometimes inconsistent with each other and suspected to be unrealistically low. We present a Markov-chain Monte Carlo (MCMC) algorithm for the asteroid mass estimation problem based on asteroid-asteroid close encounters. We verify that our algorithm works correctly by applying it to synthetic data sets. We then use astrometry available through the Minor Planet Center to estimate masses for a few example cases and compare our results to results reported in the literature. Our mass estimates for the synthetic data sets are fully consistent with the ground truth. The nominal masses for real example cases typically agree with the literature but tend to have greater uncertainties than what is reported in recent literature. Possible reasons for this include different astrometric datasets and/or weights, different test asteroids, different force models and different algorithms. For (16) Psyche, the target of NASA's Psyche mission, our maximum likelihood mass is approximately 55% of what is reported in the literature. Such a low mass would imply that the bulk density is significantly lower than previously expected and hence disagrees with the theory of (16) Psyche being the metallic core of a protoplanet. We however note that masses reported in recent literature remain within our 3-sigma limits.

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arXiv2019

The Hamburg Meteorite Fall: Fireball trajectory, orbit and dynamics

The Hamburg (H4) meteorite fell on January 17, 2018 at 01:08 UT approximately 10km North of Ann Arbor, Michigan. More than two dozen fragments totaling under one kilogram were recovered, primarily from frozen lake surfaces. The fireball initial velocity was 15.83 $\pm$ 0.05 km/s, based on four independent records showing the fireball above 50 km altitude. The radiant had a zenith angle of 66.1 $\pm$ 0.29 degs and an azimuth of 121.56 $\pm$ 1.2 degs. The resulting low inclination ($<$ 1 deg) Apollo-type orbit has a large aphelion distance and Tisserand value relative to Jupiter (Tj) of $\sim$ 3. Two major flares dominant the energy deposition profile, centred at 24.1 and 21.7 km altitude respectively under dynamic pressures of 5-7 MPa. Our preferred total energy for the Hamburg fireball is 2 to 7 T TNT (8.4 to 28 x 10$^9$ J), which corresponds to a likely initial mass in the range of 60 to 225 kg or diameter between 0.3 to 0.5 m. Based on the model of Granvik et al (2018), the meteorite originated in an escape route from the mid-outer asteroid belt. Hamburg is the 14th known H-chondrite with an instrumentally-derived pre-atmospheric orbit, half of which have small ($<$5 deg) inclinations making connection with (6) Hebe problematic. A definitive parent body consistent with all 14 known H-chondrite orbits remains elusive

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arXiv2018

Simultaneous LSST and Euclid observations - advantages for Solar System Objects

The ESA Euclid mission is a space telescope that will survey ~15,000 square degrees of the sky, primarily to study the distant universe (constraining cosmological parameters through the lensing of galaxies). It is also expected to observe ~150,000 Solar System Objects (SSOs), primarily in poorly understood high inclination populations, as it will mostly avoid +/-15 degrees from the ecliptic plane. With a launch date of 2022 and a 6 year survey, Euclid and LSST will operate at the same time, and have complementary capabilities. We propose a LSST mini-survey to coordinate quasi-simultaneous observations between these two powerful observatories, when possible, with the primary aim of greatly improving the orbits of SSOs discovered by these facilities. As Euclid will operate from a halo orbit around the Sun-Earth L2 Lagrangian point, there will be significant parallax between observations from Earth and Euclid (0.01 AU). This means that simultaneous observations will give an independent distance measurement to SSOs, giving additional constraints on orbits compared to single Euclid visits.

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arXiv2017

CASTAway: An Asteroid Main Belt Tour and Survey

CASTAway is a mission concept to explore our Solar System's main asteroid belt. Asteroids and comets provide a window into the formation and evolution of our Solar System and the composition of these objects can be inferred from space-based remote sensing using spectroscopic techniques. Variations in composition across the asteroid populations provide a tracer for the dynamical evolution of the Solar System. The mission combines a long-range (point source) telescopic survey of over 10,000 objects, targeted close encounters with 10 to 20 asteroids and serendipitous searches to constrain the distribution of smaller (e.g. 10 m) size objects into a single concept. With a carefully targeted trajectory that loops through the asteroid belt, CASTAway would provide a comprehensive survey of the main belt at multiple scales. The scientific payload comprises a 50 cm diameter telescope that includes an integrated low-resolution (R = 30 to 100) spectrometer and visible context imager, a thermal (e.g. 6 to 16 microns) imager for use during the flybys, and modified star tracker cameras to detect small (approx. 10 m) asteroids. The CASTAway spacecraft and payload have high levels of technology readiness and are designed to fit within the programmatic and cost caps for a European Space Agency medium class mission, whilst delivering a significant increase in knowledge of our Solar System.

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arXiv2017

Asteroid mass estimation using Markov-chain Monte Carlo

Estimates for asteroid masses are based on their gravitational perturbations on the orbits of other objects such as Mars, spacecraft, or other asteroids and/or their satellites. In the case of asteroid-asteroid perturbations, this leads to an inverse problem in at least 13 dimensions where the aim is to derive the mass of the perturbing asteroid(s) and six orbital elements for both the perturbing asteroid(s) and the test asteroid(s) based on astrometric observations. We have developed and implemented three different mass estimation algorithms utilizing asteroid-asteroid perturbations: the very rough 'marching' approximation, in which the asteroids' orbital elements are not fitted, thereby reducing the problem to a one-dimensional estimation of the mass, an implementation of the Nelder-Mead simplex method, and most significantly, a Markov-chain Monte Carlo (MCMC) approach. We describe each of these algorithms with particular focus on the MCMC algorithm, and present example results using both synthetic and real data. Our results agree with the published mass estimates, but suggest that the published uncertainties may be misleading as a consequence of using linearized mass-estimation methods. Finally, we discuss remaining challenges with the algorithms as well as future plans.

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