Solar system

Abstract:

Introduction: The Lucy mission's first asteroid flyby provided a unique and unexpected opportunity to study a binary asteroid system up close. Originally expected to encounter a single target, Dinkinesh, the discovery of its small, tidally locked moon, Selam, introduced additional opportunity and complexity to the interpreting flyby observations [1]. We present thermal modelling of the binary system, quantifying how the presence of Selam influenced radiance measurements and indicating its possible impact on thermal inertia estimates. Thermal inertia (TI) offers insight into surface properties such as grain size and regolith structure. Determining the TI of Dinkinesh adds to our understanding of small S-type asteroids and enables comparison within a binary, potentially revealing differences driven by tidal effects or surface evolution.Methods: We modelled the flyby geometry and instrument measurements using the new TESBY (Thermal Emissions Spectrometer flyBY) module of TEMPEST (the Thermophysical Equilibrium Model for Planetary Environment Surface Temperatures) [2] to simulate the thermal radiance of both bodies and assess their combined effect on interpretation of data from the Lucy Thermal Emission Spectrometer (L’TES) instrument [3].The Thermal Model: Dinkinesh and its satellite, Selam, were modelled in TEMPEST. A stereo-photogrammetric shape model is available for the primary target – Dinkinesh [4], with ~2 m lateral and ~0.5 m vertical resolution, covering ~60% of the surface. This shape model was downsampled to a dimensionally accurate model with 1266 facets with a resolution of ~35 m. A sphere of representative diameter (230 m [1]) was used for the satellite Selam.Figure 1: TESBY visualization of flyby. Global view of the flyby trajectory (left), and the FOV of the instrument (centre), with corresponding L’LORRI image for comparison [1] taken 0.54 minutes before closest approach (right). Input is the TEMPEST [5] result for the shape model of Dinkinesh, and representative diameter sphere for Selam. Parameters used: solar distance = 2.19 AU, rotation periods = 3.74 hours (Dinkinesh) and 52.7 hours (Selam) [1] thermal inertia (provisional) = 40 J m-2 s-1/2 K-1, geometric albedo = 0.27Flyby geometry: Building on the TEMPEST framework, the TESBY module is given the geometry information for the flyby and the thermal data from TEMPEST. Based on the 7.3 mrad Field-of-View (FOV) of the L’TES instrument [3] TESBY produces simulated radiance measurements by computing a weighted sum of blackbody curves from each visible facet, based on its temperature, projected area, and emission angle. Matching these modelled radiances to the instrument data allows us to fit for the thermal inertia of the asteroid. A complicating factor in this study is that the sensitivity of L’TES is not uniform across its FOV, including this effect in the model is the subject of ongoing work.Figure 2: Preliminary modelled radiance results (blue line) compared to L’TES observation (red) using the same model settings as Fig. 1. Scaled radiances (dotted line) are also provided (see main text for more information).Results: An example of the currently predicted model radiance is given by Figure 2. As it shows, there is a notable offset between the predicted and observed radiances. Accounting for the position of the targets in the L’TES FOV is expected to resolve the observed discrepancy in absolute radiance levels. However, as the scaled model shows, the predicted radiances are able to capture the shape of the L’TES radiance.We find that due to the slower rotation rate of Selam, the maximum surface temperatures on the satellite can be as much as 25 K higher than those on Dinkinesh (Fig. 1), meaning that despite the small size (lobe diameter of only 230 m, compared with 790 m for Dinkinesh [1]), the contribution to measured radiance is significant. This effect is highlighted by investigation of the integrated radiances of the targets throughout the flyby (Fig. 3), where the entry and exit of Selam within the FOV is visible, as well as the dip in integrated radiance while Selam is partially eclipsed by Dinkinesh. Our results demonstrate the importance of considering the full system in flyby analysis, informing techniques for similar encounters in the future. This work highlights how the thermal signature of even a small secondary body can significantly impact observations, shaping our understanding of asteroid surface properties and thermal environments.Continued analysis will focus on the use of TEMPEST/TESBY to constrain the thermal inertia of this binary asteroid from L’TES flyby observations.  Figure 3: Variation in integrated wavelength for Dinkinesh (target, blue), Selam (satellite, red) and combined effect (green). Radiances were integrated over the 200–1500 cm⁻¹ spectral range. The results show that despite its small size, Selam makes a significant difference to the spectral radiance, particularly at shorter wavelengths. The dip in combined spectral radiance at observations 3315-3320 is due to Selam being eclipsed by Dinkinesh.The thermal model code is open source and available at: github.com/duncanLyster/TEMPEST/Acknowledgement: This work was made possible by support from the UK Science and Technology Facilities Council.  References: [1] Levison, H.F., Marchi, S., Noll, K.S. et al. A contact binary satellite of the asteroid (152830) Dinkinesh. Nature 629, 1015–1020 (2024).[2] Lyster, D., Howett, C., & Penn, J. (2024). Predicting surface temperatures on airless bodies: An open-source Python tool. EPSC Abstracts, 18, EPSC2024-1121.[3] Christensen, P. R., et al. The Lucy Thermal Emission Spectrometer (L’TES) Instrument, Space Sci. Rev. (2023)[4] Preusker, F. et al. (2024). Shape Model of Asteroid (152830) Dinkinesh from Photogrammetric Analysis of Lucy’s Frame Camera L’LORRI. 55th Lunar and Planetary Science Conference, Abstract #1903.[5] Lyster, D., Howett, C., & Penn, J. (2025). TEMPEST: A Modular Thermophysical Model for Airless Bodies with Support for Surface Roughness and Non-Periodic Heating. Submitted to EPSC Abstracts, 2025

Abstract:

. IntroductionPerhaps one of the most fascinating ice-covered moons in our solar system is the Galilean satellite Europa. The successful launch of Europa Clipper has motivated the re-evaluation of our current knowledge of the Jovian moon -- specifically thermal measurements of the moon's surface, which may contain information about recent geologic activity. After the discovery of active plumes on Enceladus [1], similar phenomena were searched for on Europa [2]. While evidence of surface alteration -- such as troughs, ridges, chaos terrain, and the lack of prevalent craters -- indicate ongoing activity and a relatively young surface [3], the presence of plumes is still being debated. While no endogenic thermal anomalies have yet been observed on Europa's surface [4], we re-assess the thermal IR data from Galileo Orbiter's photopolarimeter-radiometer instrument (PPR) [5]. We perform a thermal analysis of the surface properties of Europa, including mapping the thermal inertia and albedo similar to what was done by Rathbun et al. [4], with a goal of extending thermal surface mapping beyond the previous 20% surface coverage. We also perform a sensitivity study of PPR in hotspot detection by determining the minimum detectable hotspot temperature across the surface of the moon and compare our results to previous work. 2. Data AnalysisWe use 29 PPR radiometry datasets taken during various orbits ranging from November 1996 to November 1999. Both narrow band and open filters were used, with a total wavelength range of 0.3-110 μm. We divide the surface into 3°x3° longitude/latitude grid cells and determine each cell's temperature at a given local time to produce diurnal temperature curves. To determine the thermal inertia and albedo, we fit a thermophysical model to each cell's diurnal curve using the Thermophysical Body Model Simulation Script (TEMPEST) [6] as our modelling tool. The best-fit diurnal curve is chosen by minimizing the reduced chi-squared of the model fit, while all data with χred2

Abstract:

NASA’s New Horizons spacecraft continues to explore the Kuiper belt after its historic close flybys of the Pluto system in 2015 at ~33 astronomical units (AU) [1] and the cold classical Kuiper belt object (KBO) Arrokoth in 2019 at ~43 AU [2].  New Horizons is located at ~61.7 AU as of this writing in May 2025, and travels about 3 AU per year.  New Horizons has sufficient power, propellant, and communications capability to continue operations until the mid-to-late 2040s and, thus, should be able to collect data out to distances of ~120 AU or greater. In its extended mission, New Horizons’ main planetary science focus is studying Kuiper belt dwarf planets and small KBOs, and their environment.  We will provide an overview of results for the dwarf planets and smaller KBOs observed by New Horizons from a distance ([3-6]; also see Porter et al., 2025 abstract at this conference).  New Horizons can observe KBOs from much higher phase angles than possible from Earth, and some of the observed KBOs come as close as 0.1 AU to the spacecraft.  This allows for the study of shapes, poles, surface properties, and  searches for close satellites in some cases.  New Horizons also made high-phase, color observations of the ice giants Uranus and Neptune [7] in coordination with the Hubble Space Telescope and as an exoplanet observation analogue.  Further, the New Horizons Student Dust Counter continues to observe elevated dust fluxes at larger distances than expected, and the team is exploring possible explanations for why the dust flux has not yet started to decrease as predicted by previous models [8, 9].  We will also highlight some new products and findings related to Arrokoth, including a new shape model [10], images draped onto the shape model, and a study placing Arrokoth’s crater size-frequency distribution into the context of those on other small bodies [11].  Looking towards the future of New Horizons: We will provide a status update on the ground-based, Subaru Telescope search [12-14] for a future close flyby target and other KBOs that New Horizons could observe as point sources.  We will also discuss how future work would enhance the chances of finding a future flyby target for New Horizons, including the additional use of machine learning/artificial intelligence, supercomputing, and potential observations from the Vera Rubin Observatory (also see Kavelaars et al. 2025 abstract in this conference) or the Roman Space Telescope.References:[1]  Stern S. A. et al., 2015, The Pluto system: Initial results from its exploration by New Horizons, Science 350, id.aad1815. doi:10.1126/science.aad1815[2]  Stern S. A. et al., 2019, Initial results from the New Horizons exploration of 2014 MU69, a small Kuiper Belt object, Science 364. doi:10.1126/science.aaw9771[3]  Verbiscer A. J. et al., 2024, The New Horizons Photometric Phase Angle Survey of Deep Outer Solar System Objects: From the Kuiper Belt to the Scattered Disk, 55th Lunar and Planetary Science Conference. 3040, 2531.[4]  Verbiscer A. J. et al., 2022, The Diverse Shapes of Dwarf Planet and Large KBO Phase Curves Observed from New Horizons, The Planetary Science Journal 3, 95. doi:10.3847/PSJ/ac63a6[5]  Verbiscer A. J. et al., 2019, Phase Curves from the Kuiper Belt: Photometric Properties of Distant Kuiper Belt Objects Observed by New Horizons, Astron. J. 158. doi:10.3847/1538-3881/ab3211[6]  Porter S. B. et al., 2016, The First High-phase Observations of a KBO: New Horizons Imaging of (15810) 1994 JR1 from the Kuiper Belt, ApJ Letters 828. doi:10.3847/2041-8205/828/2/L15[7]  Hasler S. N. et al., 2024, Observations of Uranus at High Phase Angle as Seen by New Horizons, The Planetary Science Journal 5, 267. doi:10.3847/PSJ/ad8cdb[8]  Corbett T. et al., 2025, Production, Transport, and Destruction of Dust in the Kuiper Belt: The Effects of Refractory and Volatile Grain Compositions, Astrophys J. 979, L50. doi:10.3847/2041-8213/adab75[9]  Doner A. et al., 2024, New Horizons Venetia Burney Student Dust Counter Observes Higher than Expected Fluxes Approaching 60 AU, pp. arXiv:2401.01230.[10]  Porter S. B. et al., 2024, The Shape and Formation of Arrokoth, 55th Lunar and Planetary Science Conference. 3040, 2332.[11]  Knudsen I. E. et al., 2024, An Analysis of Impact Craters on Small Bodies Throughout the Solar System, The Trans-neptunian Solar System.[12]  Yoshida F. et al., 2024, A deep analysis for New Horizons' KBO search images, Publications of the Astronomical Society of Japan 76, 720-732. doi:10.1093/pasj/psae043[13]  Fraser W. C. et al., 2024, Candidate Distant Trans-Neptunian Objects Detected by the New Horizons Subaru TNO Survey, The Planetary Science Journal 5, 227. doi:10.3847/PSJ/ad6f9e[14]  Buie M. W. et al., 2024, The New Horizons Extended Mission Target: Arrokoth Search and Discovery, The Planetary Science Journal 5, 196. doi:10.3847/PSJ/ad676d

Abstract:

We present work to update current maps of the thermal properties of Enceladus using thermal observations from the Cassini Composite InfraRed Spectrometer (CIRS).  In 2010, the first maps of Enceladus’ thermal inertia were published that used what CIRS data was available at the time (Howett et al., 2010). These maps were resolved into some latitude zones, and overall conveyed lower thermal inertia and albedo at higher latitudes, and confirmed that like other cold, icy moons of Saturn its surface had low (< 50 MKS) thermal inertia.  Improvements to these maps using the totality of the CIRS Focal Plane 1 data (10-600 cm-1 / 16.7-1000 μm) from the mission with updated error estimates will yield better spatial resolution in addition to higher precision estimates of thermal inertia and albedo.   This will be particularly useful for improving models of surface temperature or estimating endogenic heat fluxes, like those at Enceladus’ south pole, associated with dissipation of heat from beneath.Acknowledgements: Thanks are given to the NASA Cassini Data Analysis program that funded this work (80NSSC20K0477 and 80NSSC24K0373). Reference:Howett, C.J.A., Spencer, J.R., Pearl, J. and Segura, M., 2010. Thermal inertia and bolometric Bond albedo values for Mimas, Enceladus, Tethys, Dione, Rhea and Iapetus as derived from Cassini/CIRS measurements. Icarus, 206(2), pp.573-593.

Abstract:

IntroductionSaturn’s largest moon, Titan, has a dense atmosphere comprised mostly of nitrogen and methane. The photolysis and ionization of these major componentsleads to complex chemical reactions, which create substantial diversity among Titan’s minor atmospheric constituents. Remote sensing and molecular  pectroscopy historically have been a critical tool for detecting trace gases in Titan’s atmosphere and help corroborate predictions of Titan’s atmospheric composition from photochemical models. Following the Voyager and Cassini missions, which provided a wealth of spectroscopic studies of Titan’s  atmosphere, ground-based measurements have been useful for detecting elusive trace gases. The Echelon-Cross-Echelle Spectrometer (EXES) is a high-resolution (R ∼ 90, 000) mid-infrared spectrometer that was previously operated aboard NASA’s Stratospheric Observatory For Infrared Astronomy (SOFIA)(1 ). EXES benefited from the high altitude flights during the SOFIA mission to make observations above the bulk of the atmosphere to avoid strong telluric absorption lines that inhibit ground based mid-IR spectrometers such as its sister instrument TEXES.Here we present EXES observations of Titan which were made in an attempt to detect two trace gases, triacetylene (C6H2) and dicyanoacetylene (C4N2). C6H2 is an important polyyne and is predicted to form readily from the addition of the ethynyl (C2H) radical with diacetylene (C4H2). It remains yet tobe detected, though, and the previous upper limit study was limited by the lower spectral resolution of Voyager’s IRIS (R ∼ 145)(2 ). Delpech et al. 1994 derived an upper-limit of 6 × 10−11 which would be detectable by EXES.Gas-phase C4N2 formation is primarily completed through C3N addition to HCN or, alternatively, CN addition to HC3N(3 ). The ice-phase C4N2, which is formed through solid-state photochemical reactions on the surface of HC3N ice grains, has been detected in spectra measured by Voyager’s IRIS and CIRSduring the Cassini mission (4, 5 ), yet C4N2 in the gas-phase remains elusive to spectroscopic detections. Again, previous studies of the gas-phase upper limits (3σ = 1.53 × 10−9) were performed using spectra collected by CIRS (R ∼ 1240) which has a resolving power significantly lower than EXES(6 ). The high-resolution of EXES will help improve on the upper limits of both of these species and allow for an updated comparison to photochemical model predictions of their vertical profiles in Titan’s atmosphere.Observations and ModelingMid-infrared observations of Titan were made in June of 2021, using EXES. These observations aim to detect the ν11 out-of-plane bending mode of C6H2 at 621 cm−1 and the perpendicular ν9 stretch of the gasphase C4N2 at 472 cm−1. Figure 1 shows a small portion of the EXES spectrum measured at the 621 cm−1 spectral setting. In this region there are strong emission features from diacetylene (C4H2) and propyne (C3H4) which must be fit before analyzing the C6H2 upper limits. Highlighted in the blue box is the region where the ν11 vibrational mode for C6H2 should be present.To model the collected spectra, we use the arch-NEMESIS radiative transfer package which is a new Python implementation of the NEMESIS radiative transfer code (7, 8 ). The radiative transfer modeling of the measured spectra occurs in two steps. The initial step is to retrieve the atmospheric profiles of the aerosols and known gases using the archNEMESIS optimal estimation algorithm. For the 621 cm−1 spectral setting, the vertical profiles of C4H2, C3H4, and aerosol continuum are retrieved, however, at the 472 cm−1 region, there are no emission features to fit and just the continuum level is retrieved by adjusting the aerosol profile. For both spectral regions, we use a temperature profile and initial gas profiles defined in Vuitton et al. 2019 photochemical model (3 ). The quality of each retrieval is determined by a goodnessof-fit metric (χ2) which compares the residual of the modeled spectrum to the noise of the measurement. Following the retrieval, we derive the upper limits by building forward models of the spectral regions where the abundance of each target species is iteratively increased and a subsequent χ2 is determined. We then take the difference, Δχ2, between the retrieved and updated forward model χ2 to find where the abundance causes significant deviation from the retrieved spectrum. Step-profiles, which have a cutoff altitude and constant abundance above this cutoff, were used to determine the upper-limits for each species. This method has been applied for many different upper limits studies of gases predicted in Titan’s atmosphere (9, 10 ).ResultsBased on these observations, C6H2 and gas-phase C4N2 remain undetected and therefore, we derive the upper limits to their atmospheric abundance. We improve upon the upper limits of C6H2 and C4N2 by an order of magnitude for both species. Figure 2 shows Δχ2 increase sharply with increased abundance for both C6H2 and C4N2. For C6H2 the 3σ upper limit (Δχ2 = 9) is on the order of 10−11 and for C4N2, 10−10. These new upper limits improve on the previously derived upper limits by an order of magnitude for each target species. More work is still being done to precisely determine the upper limits and compare these values to the current photochemical model predictions of their abundance. The values of the 1σ, 2σ, and 3σ upper limits for each species will be reported in the presentation. The upper limits derived improved upon the previous upper limits by an order of magnitude and we are currently working on comparing these upper limits to photochemical models of Titan’s atmospheric composition to build a better understanding of the chemical pathways in Titan’s atmosphere which will also be discussed in the presentation. AcknowledgmentsThe material is based upon work supported by NASA under award number 80GSFC24M0006.References1. Richter et al., 20182. Delpech et al., 19943. Vuitton et al., 20194. Samuelson et al, 19975. Anderson et al, 20166. Jolly et al., 20157. Alday et al, 20258. Irwin et al., 20089. Nixon et al., 201010. Teanby et al., 2013