Tootfinder

Measuring the Two-Dimensional Thermal Structures of Protoplanetary Disks
Anna J. Fehr, Sean M. Andrews
https://arxiv.org/abs/2509.15196 https://arxiv.org/p…

Measuring the Two-Dimensional Thermal Structures of Protoplanetary Disks
We present a flexible, annulus-by-annulus method to constrain the 2-D thermal structure of a protoplanetary disk from optically thick spectral line emission. Using synthetic disk models with a known temperature and density structure, we extracted the vertical emission surfaces and brightness temperatures in radial annuli for multiple CO isotopologue transitions and used them to infer the vertical temperature profiles. This approach reliably recovers the injected temperature structure despite no…

Hubble reveals complex multi-scale structure in the edge-on protoplanetary disk IRAS 23077 6707
Kristina Monsch, Joshua B. Lovell, Karl R. Stapelfeldt, Sean M. Andrews, Ammar Bayyari, Alice S. Booth, Adolfo S. Carvalho, John H. Debes, Jeremy J. Drake, Joshua W. J. Earley, Cecilia Garraffo, Garrett K. Keating, Michael L. Sitko, David J. Wilner
https://

Hubble reveals complex multi-scale structure in the edge-on protoplanetary disk IRAS 23077+6707
We present high-resolution (<0.1") Hubble Space Telescope (HST)/Wide Field Camera 3 (WFC3) imaging of the near edge-on (i~80 deg) protoplanetary disk IRAS 23077+6707 ("Dracula's Chivito") obtained across six broadband filters spanning 0.4-1.6 microns. These observations unveil the scattered light from this unusually large disk (~14", or ~4200 au at 300 pc) in remarkable detail, revealing a rich tapestry of substructure, including brightness asymmetries and signatures of dynamical activity. Exte…

In-Context Clustering with Large Language Models
Ying Wang, Mengye Ren, Andrew Gordon Wilson
https://arxiv.org/abs/2510.08466 https://arxiv.org/pdf/2510.08…

In-Context Clustering with Large Language Models
We propose In-Context Clustering (ICC), a flexible LLM-based procedure for clustering data from diverse distributions. Unlike traditional clustering algorithms constrained by predefined similarity measures, ICC flexibly captures complex relationships among inputs through an attention mechanism. We show that pretrained LLMs exhibit impressive zero-shot clustering capabilities on text-encoded numeric data, with attention matrices showing salient cluster patterns. Spectral clustering using attenti…

A Sentinel-3 foundation model for ocean colour
Geoffrey Dawson, Remy Vandaele, Andrew Taylor, David Moffat, Helen Tamura-Wicks, Sarah Jackson, Rosie Lickorish, Paolo Fraccaro, Hywel Williams, Chunbo Luo, Anne Jones
https://arxiv.org/abs/2509.21273

A Sentinel-3 foundation model for ocean colour
Artificial Intelligence (AI) Foundation models (FMs), pre-trained on massive unlabelled datasets, have the potential to drastically change AI applications in ocean science, where labelled data are often sparse and expensive to collect. In this work, we describe a new foundation model using the Prithvi-EO Vision Transformer architecture which has been pre-trained to reconstruct data from the Sentinel-3 Ocean and Land Colour Instrument (OLCI). We evaluate the model by fine-tuning on two downstrea…

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Paola Pinilla, Anibal Sierra, Nicolas T. Kurtovic, Rossella Anania, Sean Andrews, John Carpenter, Osmar Guerra-Alvarado, Feng Long, Sebastian Marino, Miguel Vioque, Ke Zhang
https://arxiv.org/abs/2509.19442

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Protoplanetary discs in the Upper Scorpius star-forming region are excellent laboratories to investigate late stages of planet formation. In this work, we analyse the morphology of the dust continuum emission of 121 discs from an ALMA Band 7 survey of the Upper Scorpius region. This analysis is done in the visibility plane, to measure the flux, geometry and characterise potential structures. We compare the results with state-of-the art gas and dust evolution models that include external photoev…