Tootfinder

Investigating non-LTE abundances of Neodymium (Nd) in metal-poor FGK stars
John D. Dixon (Texas A&M University), Rana Ezzeddine (University of Florida), Yangyang Li (University of Florida), Thibault Merle (Institut d'Astronomie et d'Astrophysique and Brussels Laboratory of the Universe, Royal Observatory of Belgium), Manuel Bautista (United States Department of Energy), Yanjun Guo (Chinese Academy of Sciences)

Investigating non-LTE abundances of Neodymium (Nd) in metal-poor FGK stars
The dominant site(s) of the $r$-process are a subject of current debate. Ejecta from $r$-process enrichment events like kilonovae are difficult to directly measure, so we must instead probe abundances in metal-poor stars to constrain $r$-process models. This requires state-of-the-art Non-Local Thermodynamic Equilibrium (NLTE) modeling, as LTE is a poor approximation for the low-opacity atmospheres of metal-poor giants. Neodymium (Nd) is a prominent $r$-process element detected in both near-infr…

Light in Slices: How to Enable Precise Laser Processing?
Stefan Nolte, J\"orn Bonse, Nadezhda M. Bulgakova
https://arxiv.org/abs/2509.22665 https://ar…

Light in Slices: How to Enable Precise Laser Processing?
Ultrashort (femtosecond, fs) laser pulses have fascinating properties as they allow to confine optical energy on extreme scales in space and time. Such fs-laser pulsed beams can be seen as spatially thin slices of intense light that are radially and axially constrained to the micrometer scale, while simultaneously propagating at the extremely high speed of light. Their high peak intensities and their short time lapse makes such laser pulses unique tools for materials processing, as their durati…

SilvaScenes: Tree Segmentation and Species Classification from Under-Canopy Images in Natural Forests
David-Alexandre Duclos, William Guimont-Martin, Gabriel Jeanson, Arthur Larochelle-Tremblay, Th\'eo Defosse, Fr\'ed\'eric Moore, Philippe Nolet, Fran\c{c}ois Pomerleau, Philippe Gigu\`ere
https://arxiv.org/abs/2510.09458…

SilvaScenes: Tree Segmentation and Species Classification from Under-Canopy Images in Natural Forests
Interest in robotics for forest management is growing, but perception in complex, natural environments remains a significant hurdle. Conditions such as heavy occlusion, variable lighting, and dense vegetation pose challenges to automated systems, which are essential for precision forestry, biodiversity monitoring, and the automation of forestry equipment. These tasks rely on advanced perceptual capabilities, such as detection and fine-grained species classification of individual trees. Yet, exi…

Hop, Skip, and Overthink: Diagnosing Why Reasoning Models Fumble during Multi-Hop Analysis
Anushka Yadav, Isha Nalawade, Srujana Pillarichety, Yashwanth Babu, Reshmi Ghosh, Samyadeep Basu, Wenlong Zhao, Ali Nasaeh, Sriram Balasubramanian, Soundararajan Srinivasan
https://arxiv.org/abs/2508.04699

Hop, Skip, and Overthink: Diagnosing Why Reasoning Models Fumble during Multi-Hop Analysis
The emergence of reasoning models and their integration into practical AI chat bots has led to breakthroughs in solving advanced math, deep search, and extractive question answering problems that requires a complex and multi-step thought process. Yet, a complete understanding of why these models hallucinate more than general purpose language models is missing. In this investigative study, we systematicallyexplore reasoning failures of contemporary language models on multi-hop question answering…

Lanthanide Impact on the Infra-Red Spectra of Nebular Phase Kilonovae
Quentin Pognan, Kyohei Kawaguchi, Shinya Wanajo, Sho Fujibayashi, Anders Jerkstrand
https://arxiv.org/abs/2510.12413

Lanthanide Impact on the Infra-Red Spectra of Nebular Phase Kilonovae
Nebular phase kilonovae (KNe) have significant infra-red (IR) emission thought to be mostly forbidden emission lines from rapid neutron capture (r-process) species in neutron star merger ejecta. Lanthanide elements in particular have complex atomic structures with many IR transitions. Using non-local thermodynamic equilibrium (NLTE) radiative transfer simulations, we explore the impact of lanthanides on the IR spectra of KNe in the nebular phase, exploring a parameter space of ejecta mass and l…

Infrared spectral signatures of light r-process elements in kilonovae
Anders Jerkstrand, Quentin Pognan, Smaranika Banerjee, Nicholas Sterling, Jon Grumer, Niamh Ferguson, Keith Butler, James Gillanders, Stephen Smartt, Kyohei Kawaguchi, Blanka Vilagos
https://arxiv.org/abs/2510.12410

Infrared spectral signatures of light r-process elements in kilonovae
A central question regarding neutron star mergers is whether they are able to produce all the r-process elements, from first to third peak. The high abundances of first-peak elements (atomic number $Z \sim 31-40$) in the solar composition means they may dominate the ejecta mass in kilonovae. We here study theoretical infrared signatures of such light elements with spectral synthesis modelling. By combining state-of-the-art NLTE physics with new radiative and collisional data for these elements,…

Probing ultrafast heating and ionization dynamics in solid density plasmas with time-resolved resonant X-ray absorption and emission
Lingen Huang, Mikhail Mishchenko, Michal \v{S}m\'id, Oliver Humphries, Thomas R. Preston, Xiayun Pan, Long Yang, Johannes Hagemann, Thea Engler, Yangzhe Cui, Thomas Kluge, Carsten Baehtz, Erik Brambrink, Alejandro Laso Garcia, Sebastian G\"ode, Christian Gutt, Mohamed Hassan, Hauke H\"oppner, Michaela Kozlova, Josefine Metzkes-Ng, Masruri Ma…

Probing ultrafast heating and ionization dynamics in solid density plasmas with time-resolved resonant X-ray absorption and emission
Heating and ionization are among the most fundamental processes in ultra-short, relativistic laser-solid interactions. However, capturing their spatiotemporal evolution experimentally is challenging due to the inherently transient and non-local thermodynamic equilibrium (NLTE) nature. Here, time-resolved resonant X-ray emission spectroscopy, in conjunction with simultaneous X-ray absorption imaging, is employed to investigate such complex dynamics in a thin copper wire driven by an optical high…

Deep learning-driven adaptive optics for laser wavefront correction
Jikai Wang, Sven Burckhard, Sonam Smitha Ravi, Dominik Bauer, Volker Rominger, Stefan Nolte, Daniel Flamm
https://arxiv.org/abs/2509.10662

Deep learning-driven adaptive optics for laser wavefront correction
{We report on an intensity-only and deep-learning based method for laser beam characterization that allows to predict the underlying optical field within milliseconds. A simple near-field / far-field camera setup enables online control of an adaptive optics to optimize beam quality. The robustness and precision of the method is enhanced by applying the concept of phase diversity based on spiral phase plates.