Tootfinder

Causal identification with $Y_0$
Charles Tapley Hoyt, Craig Bakker, Richard J. Callahan, Joseph Cottam, August George, Benjamin M. Gyori, Haley M. Hummel, Nathaniel Merrill, Sara Mohammad Taheri, Pruthvi Prakash Navada, Marc-Antoine Parent, Adam Rupe, Olga Vitek, Jeremy Zucker
https://arxiv.org/abs/2508.03167…

Causal identification with $Y_0$
We present the $Y_0$ Python package, which implements causal identification algorithms that apply interventional, counterfactual, and transportability queries to data from (randomized) controlled trials, observational studies, or mixtures thereof. $Y_0$ focuses on the qualitative investigation of causation, helping researchers determine whether a causal relationship can be estimated from available data before attempting to estimate how strong that relationship is. Furthermore, $Y_0$ provides gu…

Bayesian Surrogates for Risk-Aware Pre-Assessment of Aging Bridge Portfolios
Sophia V. Kuhn, Rafael Bischof, Marius Weber, Antoine Binggeli, Michael A. Kraus, Walter Kaufmann, Fernando P\'erez-Cruz
https://arxiv.org/abs/2509.25031

Bayesian Surrogates for Risk-Aware Pre-Assessment of Aging Bridge Portfolios
Aging infrastructure portfolios pose a critical resource allocation challenge: deciding which structures require intervention and which can safely remain in service. Structural assessments must balance the trade-off between cheaper, conservative analysis methods and accurate but costly simulations that do not scale portfolio-wide. We propose Bayesian neural network (BNN) surrogates for rapid structural pre-assessment of worldwide common bridge types, such as reinforced concrete frame bridges. T…

VLT/MUSE Detection of the AB Aurigae b Protoplanet with $H _{\rm \alpha}$ Spectroscopy
Thayne Currie, Jun Hashimoto, Yuhiko Aoyama, Ruobing Dong, Misato Fukagawa, Takayuki Muto, Erica Dykes, Mona El Morsy, Motohide Tamura
https://arxiv.org/abs/2508.18351

VLT/MUSE Detection of the AB Aurigae b Protoplanet with $H _{\rm α}$ Spectroscopy
We analyze high-contrast, medium-spectral-resolution $H_{\rm α}$ observations of the star AB Aurigae using the Very Large Telescope's Multi Unit Spectroscopic Explorer (MUSE). In multiple epochs, MUSE detects the AB Aur b protoplanet discovered from Subaru/SCExAO data in emission at wavelengths slightly blue-shifted from the $H_{\rm α}$ line center (i.e. at 6558.88--6560.13 Å; $\sim$ -100 km s$^{-1}$) and in absorption at redshifted wavelengths (6562.8--6565.1 Å; $\sim$ 75 km s$^{-1}$). AB …

A Morse complex for the homology of vanishing cycles
Aleksander Doan, Juan Mu\~noz-Ech\'aniz
https://arxiv.org/abs/2509.20685 https://arxiv.org/pdf/250…

A Morse complex for the homology of vanishing cycles
We construct Morse homology groups associated with any regular function on a smooth complex algebraic variety, allowing singular and non-compact critical loci. These groups are generated by critical points of a certain large pertubation of the function, built from a normal crossing compactification of the variety. They are canonically isomorphic to the homology of vanishing cycles and -- in the absence of bifurcations at infinity -- recover the hypercohomology of the perverse sheaf of vanishing…

Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspection
Richard Kuhlmann, Jakob Wolfram, Boyang Sun, Jiaxu Xing, Davide Scaramuzza, Marc Pollefeys, Cesar Cadena
https://arxiv.org/abs/2509.17877

Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspection
Autonomous inspection is a central problem in robotics, with applications ranging from industrial monitoring to search-and-rescue. Traditionally, inspection has often been reduced to navigation tasks, where the objective is to reach a predefined location while avoiding obstacles. However, this formulation captures only part of the real inspection problem. In real-world environments, the inspection targets may become visible well before their exact coordinates are reached, making further movemen…

Poset-enriched pretoposes and compact ordered spaces
J\'er\'emie Marqu\`es, Luca Reggio
https://arxiv.org/abs/2508.09944 https://arxiv.org/pdf/2508…

Poset-enriched pretoposes and compact ordered spaces
We provide a characterisation of the category $\mathsf{KOrd}$ of Nachbin's compact ordered spaces as a poset-enriched category. Up to equivalence, $\mathsf{KOrd}$ is the only non-degenerate poset-enriched pretopos whose terminal object is a (discrete) generator and in which every object is covered by an order-filtral object. Order-filtral objects satisfy an appropriate form of compactness and separation. Throughout, we make extensive use of the internal language of poset-enriched pretoposes.

Very-low-field MRI scanners: from the ideal to the real permanent magnet array
Umberto Zanovello, Alessandro Arduino, Vittorio Basso, Luca Zilberti, Alessandro Sola, Andrea Agosto, Luca Toso, Oriano Bottauscio
https://arxiv.org/abs/2509.11762

Very-low-field MRI scanners: from the ideal to the real permanent magnet array
Very-low-field MRIs are becoming increasingly popular due to their portability and adaptability to different environments. They are being successfully used for various clinical applications, leading to a paradigm shift in the way imaging care is typically performed. The development of low-cost MRI scanner prototypes began a few years ago, with some interesting and promising open-source projects emerging in both hardware and software design. Using permanent magnets (PMs) to generate the static m…

Motion-Based User Identification across XR and Metaverse Applications by Deep Classification and Similarity Learning
Lukas Schach, Christian Rack, Ryan P. McMahan, Marc Erich Latoschik
https://arxiv.org/abs/2509.08539

Motion-Based User Identification across XR and Metaverse Applications by Deep Classification and Similarity Learning
This paper examines the generalization capacity of two state-of-the-art classification and similarity learning models in reliably identifying users based on their motions in various Extended Reality (XR) applications. We developed a novel dataset containing a wide range of motion data from 49 users in five different XR applications: four XR games with distinct tasks and action patterns, and an additional social XR application with no predefined task sets. The dataset is used to evaluate the per…

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
Lesly Miculicich, Mihir Parmar, Hamid Palangi, Krishnamurthy Dj Dvijotham, Mirko Montanari, Tomas Pfister, Long T. Le
https://arxiv.org/abs/2510.05156

VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation
The deployment of autonomous AI agents in sensitive domains, such as healthcare, introduces critical risks to safety, security, and privacy. These agents may deviate from user objectives, violate data handling policies, or be compromised by adversarial attacks. Mitigating these dangers necessitates a mechanism to formally guarantee that an agent's actions adhere to predefined safety constraints, a challenge that existing systems do not fully address. We introduce VeriGuard, a novel framework th…

Understanding JWST water spectra: what can thermochemical models tell us about the (cold) water in protoplanetary disks?
Marissa Vlasblom, Milou Temmink, Andrew D. Sellek, Ewine F. van Dishoeck
https://arxiv.org/abs/2509.06494

Understanding JWST water spectra: what can thermochemical models tell us about the (cold) water in protoplanetary disks?
(Abridged) Rotational H$_2$O spectra as observed with JWST/MIRI provide a good probe of the temperature and column density structure of the inner disk. H$_2$O emission can also be influenced by dynamical processes, such as dust grains drifting inwards and their icy mantles sublimating once they cross the snowlines, thus enriching the inner regions in H$_2$O vapor. Recent work has found that this process may leave an imprint in the H$_2$O spectrum in the form of excess flux in the cold H$_2$O li…