The High Angular Resolution Monolithic Optical and Near-infrared Integral field spectrograph (HARMONI) is the near infrared (NIR) integral field spectrograph for the Extremely Large Telescope (ELT). To reach the diffraction limit of the telescope and maintain an optimal image quality over long exposures, an accurate measurement of geometrical distortions in the field of view of the instrument is needed. This is achieved by means of three articulated guide probes sweeping the focal plane of the instrument. The latest iteration of the design of the guide probes of HARMONI changes the structure of the geometrical distortions of optomechanical origin, and a new formulation of the corrective model is required. In this work, we developed a 3D optomechanical model to simulate these distortions, and characterise their structure to formulate a corrective model with a reduced number of free parameters. The proposed corrective model captures the structure of the systematic pointing error introduced by these contributions based on a new series expansion named the “Lollipop expansion”. The proposed corrective model is able to remove not only the effects of the guide probe motors, but also the effects of the misalignments of the fold mirrors, with a residual well below the acceptance criterion of 10% of the total error budget.
Abstract Building on previous low Earth orbit (LEO) satellite classification work, this paper aims to investigate the hyperparameter space of MMT-9 lightcurves and apply the optimal hyperparameters to classification. Both inter-platform and intra-platform lightcurve classification tasks are considered. The best hyperparameters were found to consist of 500 boosting steps, a learning rate of 0.01 and a max tree depth of 6 nodes. These hyperparameters were then used for classification with a lightcurve dataset size of 1000 lightcurves per platform, an order of magnitude greater than previous work, resulting in a slight increase in classification accuracy (87.92% versus 85.65%), suggesting a plateau was already being approached with 100 lightcurves per platform.
Comparing observed and predicted surface temperatures on airless planetary bodies is crucial for interpreting their surface processes, constraining activity, and deriving their surface properties. We present a new tool in this endeavour: TEMPEST (Thermophysical Evolution Model for Planetary Environment Surface Temperatures). It is a modular, open-source Python model for diurnal thermal evolution on irregular bodies. TEMPEST can reproduce non-Lambertian multiple scattering using arbitrary Bidirectional Reflectance Distribution Functions (BRDFs) and notably incorporates surface roughness on sub-facet scales through representative sphere-section geometry. The model includes an explicit time-stepping one-dimensional periodic conduction solver influenced by Spencer's thermal model Thermprojrs, and a semi-implicit Crank-Nicolson solver, and can be paired with other thermal solvers. Precomputed look-up tables enable fast application of scattering laws (Lambertian, Lommel-Seeliger, Hapke, or input empirical BRDF data), allowing the user to assess their effects in permanently shadowed regions or partially shadowed terrains. TEMPEST is parallelised, running on personal computers in minutes for thousands of facets and scaling to high-performance servers for models exceeding 100,000 facets. Validation was performed against Thermprojrs in one dimension, against Sorli's Binary Thermophysical Model in three dimensions, and with empirical thermal data from the Lunar Reconnaissance Orbiter, showing good agreement in each case. Application to the high-resolution shape-model of 25143 Itokawa shows the importance of self-shadowing and radiative mutual heating in controlling local temperatures. TEMPEST has already been used to analyse data from the Lucy Mission, Galileo, and ground-based observations, and is adaptable to upcoming datasets from targets of missions such as Comet Interceptor and Europa Clipper.
Abstract This paper explores the potential for strategic synergies between the James Webb Space Telescope (JWST) and the Ariel Space Telescope, two flagship observatories poised to revolutionise the study of exoplanet atmospheres. Both telescopes have the potential to address common fundamental questions about exoplanets—especially concerning their nature and origins—and serve a growing scientific community. With their operations now anticipated to overlap from 2031, there is a unique opportunity to enhance the scientific outputs of both observatories through coordinated efforts. In this report, authored by the Ariel-JWST Synergy Working Group, part of the Ariel Consortium Science Team, we summarise the capabilities of both telescopes; we highlight their key differences, similarities, synergies, and distinctive strengths. Ariel is designed to conduct a broad survey of exoplanet atmospheres but remains highly flexible, allowing the mission to integrate insights from JWST’s discoveries. Findings from JWST, including data from initiatives shaped by NASA’s decadal survey priorities and community-driven research themes, will inform the development of Ariel’s survey strategy. Conversely, Ariel’s broad-wavelength coverage for bright targets provides complementary avenues for exoplanet researchers, particularly those interested in time-domain observations and large-scale atmospheric studies. We identify key pathways for fostering JWST-Ariel synergies, many of which can be initiated even before Ariel’s launch. Leveraging their complementary designs and scopes, JWST and Ariel can jointly address fundamental questions about the nature, formation, and evolution of exoplanets. Such collaboration has the potential to maximise the scientific returns of both observatories and lay the foundation for future facilities in the roadmap to exoplanet exploration.
