Tootfinder

Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Alejandra M. Mu\~noz Arancibia, Pavlos Protopapas, Francisco F\"orster, M\'arcio Catelan, A. Bayo, Pablo A. Est\'evez, P. S\'anchez-S\'aez, Franz E. Bauer, M. Pavez-Herrera, L. Hern\'andez-Garc\'ia, Gonzalo Rojas

Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
We explore the use of Swin Transformer V2, a pre-trained vision Transformer, for photometric classification in a multi-survey setting by leveraging light curves from the Zwicky Transient Facility (ZTF) and the Asteroid Terrestrial-impact Last Alert System (ATLAS). We evaluate different strategies for integrating data from these surveys and find that a multi-survey architecture which processes them jointly achieves the best performance. These results highlight the importance of modeling survey-s…

The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): VII. Testing accretion mechanisms from disk population synthesis
Beno\^it Tabone, Giovanni P. Rosotti, Leon Trapman, Paola Pinilla, Ilaria Pascucci, Alice Somigliana, Richard Alexander, Miguel Vioque, Rossella Anania, Aleksandra Kuznetsova, Ke Zhang, Laura M. P\'erez, Lucas A. Cieza, John Carpenter, Dingshan Deng, Carolina Agurto-Gangas, Dary A. Ru\'iz-Rodr\'iguez, Anibal Sierra, Nicol\'as T. Kurtovic, …

The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): VII. Testing accretion mechanisms from disk population synthesis
The architecture of planetary systems depends on the evolution of the disks in which they form. In this work, we develop a population synthesis approach to interpret the AGE-PRO measurements of disk gas mass and size considering two scenarios: turbulence-driven evolution with photoevaporative winds and MHD disk-wind-driven evolution. A systematic method is proposed to constrain the distribution of disk parameters from the disk fractions, accretion rates, disk gas masses, and CO gas sizes. We fi…

Quantum Executor: A Unified Interface for Quantum Computing
Giuseppe Bisicchia, Alessandro Bocci, Antonio Brogi
https://arxiv.org/abs/2507.07597 https://…

Quantum Executor: A Unified Interface for Quantum Computing
As quantum computing evolves from theoretical promise to practical deployment, the demand for robust, portable, and scalable tools for quantum software experimentation is growing. This paper introduces Quantum Executor, a backend-agnostic execution engine designed to orchestrate quantum experiments across heterogeneous platforms. Quantum Executor provides a declarative and modular interface that decouples experiment design from backend execution, enabling seamless interoperability and code reus…

The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): II. Dust and Gas Disk Properties in the Ophiuchus Star-forming Region
Dary A. Ruiz-Rodriguez, Camilo Gonzalez-Ruilova, Lucas A. Cieza, Ke Zhang, Leon Trapman, Anibal Sierra, Paola Pinilla, Ilaria Pascucci, Laura M. Perez, Dingshan Deng, Carolina Agurto-Gangas, John Carpenter, Beno\^it Tabone, Giovanni P. Rosotti, Rossella Anania, James Miley, Kamber Schwarz, Aleksandra Kuznetsova, Miguel Vioque, Nicolas Kurtovic

The ALMA Survey of Gas Evolution of PROtoplanetary Disks (AGE-PRO): II. Dust and Gas Disk Properties in the Ophiuchus Star-forming Region
The ALMA survey of Gas Evolution in PROtoplanetary disks (AGE-PRO) Large Program aims to trace the evolution of gas disk mass and size throughout the lifetime of protoplanetary disks. This paper presents Band-6 ALMA observations of 10 embedded (Class I and Flat Spectrum) sources in the Ophiuchus molecular cloud, with spectral types ranging from M3 to K6 stars, which serve as the evolutionary starting point in the AGE-PRO sample. While we find 4 nearly edge on disks (>70 deg.), and 3 highly incl…

Join the 2025 Maine AI 'unconference' on June 13 in Orono for face-to-face discussions whose topics will be democratically chosen by the attenders. (We've got expert panels too.) Register by this Friday—more at https://www.linkedin.com/posts/jonippolito

Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
Aliaksandr Hubin
https://arxiv.org/abs/2507.06776 https://

Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
Sparse Identification of Nonlinear Dynamics (SINDy) has become a standard methodology for inferring governing equations of dynamical systems from observed data using statistical modeling. However, classical SINDy approaches rely on predefined libraries of candidate functions to model nonlinearities, which limits flexibility and excludes robust uncertainty quantification. This paper proposes Bayesian Generalized Nonlinear Models (BGNLMs) as a principled alternative for more flexible statistical …

STARE: Predicting Decision Making Based on Spatio-Temporal Eye Movements
Moshe Unger, Alexander Tuzhilin, Michel Wedel
https://arxiv.org/abs/2508.04148 https://

STARE: Predicting Decision Making Based on Spatio-Temporal Eye Movements
The present work proposes a Deep Learning architecture for the prediction of various consumer choice behaviors from time series of raw gaze or eye fixations on images of the decision environment, for which currently no foundational models are available. The architecture, called STARE (Spatio-Temporal Attention Representation for Eye Tracking), uses a new tokenization strategy, which involves mapping the x- and y- pixel coordinates of eye-movement time series on predefined, contiguous Regions of…

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
Mohammed Baharoon, Luyang Luo, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Mahmoud Hussain Alabbad, Maha Sbayel Alhazmi, Neel P. Mistry, Kent Ryan Kleinschmidt, Brady Chrisler, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Noah Michael Prudlo, Mark David Marino, Jeremy Palacio, Rithvik Akula, Hong-Yu Zhou, Ibrahim Ethem Hamamci, Scott J. Adams, Hassan Rayhan AlOmaish, P…

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
We present ReXGroundingCT, the first publicly available dataset to link free-text radiology findings with pixel-level segmentations in 3D chest CT scans that is manually annotated. While prior datasets have relied on structured labels or predefined categories, ReXGroundingCT captures the full expressiveness of clinical language represented in free text and grounds it to spatially localized 3D segmentation annotations in volumetric imaging. This addresses a critical gap in medical AI: the abilit…

Finding easy regions for short-read variant calling from pangenome data
Heng Li
https://arxiv.org/abs/2507.03718 https://arxiv.org/pd…

Finding easy regions for short-read variant calling from pangenome data
Background: While benchmarks on short-read variant calling suggest low error rate below 0.5%, they are only applicable to predefined confident regions. For a human sample without such regions, the error rate could be 10 times higher. Although multiple sets of easy regions have been identified to alleviate the issue, they fail to consider non-reference samples or are biased towards existing short-read data or aligners. Results: Here, using hundreds of high-quality human assemblies, we derived …

Terrestrial Planet Formation from Two Source Reservoirs
David Nesvorny, Alessandro Morbidelli, William F. Bottke, Rogerio Deienno, Max Goldberg
https://arxiv.org/abs/2507.14814

Terrestrial Planet Formation from Two Source Reservoirs
This work describes new dynamical simulations of terrestrial planet formation. The simulations started at the protoplanetary disk stage, when planetesimals formed and accreted into protoplanets, and continued past the late stage of giant impacts. We explored the effect of different parameters, such as the initial radial distribution of planetesimals and Type-I migration of protoplanets, on the final results. In each case, a thousand simulations were completed to characterize the stochastic natu…