Tootfinder

On the vanishing order of Jacobi forms at infinity
Jialin Li, Haowu Wang
https://arxiv.org/abs/2506.16083 https://arxiv.org/pdf/2506.…

On the vanishing order of Jacobi forms at infinity
In this paper, we establish two types of upper bounds on the vanishing order of Jacobi forms at infinity. The first type is for classical Jacobi forms, which is optimal in a certain sense. The second type is for Jacobi forms of lattice index. Based on this bound, we obtain a lower bound on the slope of orthogonal modular forms, and we prove that the module of symmetric formal Fourier--Jacobi series on $\mathrm{O}(m,2)$ has finite rank.

Fair Contracts in Principal-Agent Games with Heterogeneous Types
Jakub T{\l}uczek, Victor Villin, Christos Dimitrakakis
https://arxiv.org/abs/2506.15887 ht…

Fair Contracts in Principal-Agent Games with Heterogeneous Types
Fairness is desirable yet challenging to achieve within multi-agent systems, especially when agents differ in latent traits that affect their abilities. This hidden heterogeneity often leads to unequal distributions of wealth, even when agents operate under the same rules. Motivated by real-world examples, we propose a framework based on repeated principal-agent games, where a principal, who also can be seen as a player of the game, learns to offer adaptive contracts to agents. By leveraging a …

An illustration of formal moduli problems with differential graded Lie algebras
Ethan Eugene Wynner
https://arxiv.org/abs/2506.12977 https://

An illustration of formal moduli problems with differential graded Lie algebras
This article provides an exposition to the topic of formal moduli problems, emphasizing its connections with differential graded Lie algebras, and mainly following from Jacob Lurie's DAG X: Formal Moduli Problems. As such, this paper should not be viewed as a presentation of original work, but rather a concise introduction to the subject in the form of a set of organized notes. I hoped to make this paper feel welcoming and insightful for the non-expert enjoyer of derived algebraic geometry, lik…

Automatic detection of overshooting tops and their properties from visible satellite channels
Ane\v{z}ka Dole\v{z}alov\'a (Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University), Jakub Seidl (Czech Hydrometeorological Institute), Jind\v{r}ich \v{S}\v{t}\'astka (Czech Hydrometeorological Institute), J\'an Ka\v{n}\'ak (Slovak Hydrometeorological Institute)

Automatic detection of overshooting tops and their properties from visible satellite channels
Overshooting tops (OTs) are critical indicators of convective storm intensity and are widely utilized in meteorological analyses. This study presents an automated algorithm for OT detection and OT height estimation using convolutional neural networks applied to visible satellite imagery. The models are trained and validated on an extensive OT dataset comprising approximately 10,000 manually detected cases over Europe. The OTs were identified from high-resolution visible (HRV) channel of the SEV…

An Ontology for Representing Curriculum and Learning Material
Antrea Christou, Chris Davis Jaldi, Joseph Zalewski, Hande K\"u\c{c}\"uk McGinty, Pascal Hitzler, Cogan Shimizu
https://arxiv.org/abs/2506.05751

An Ontology for Representing Curriculum and Learning Material
Educational, learning, and training materials have become extremely commonplace across the Internet. Yet, they frequently remain disconnected from each other, fall into platform silos, and so on. One way to overcome this is to provide a mechanism to integrate the material and provide cross-links across topics. In this paper, we present the Curriculum KG Ontology, which we use as a framework for the dense interlinking of educational materials, by first starting with organizational and broad pe…

Metallization of leaf-derived lignocellulose scaffolds for high performance flexible electronics and oligodynamic disinfection
Rakesh Rajendran Nair, Mihai Nita-Lazar, Valeriu Robert Badescu, Cristina Iftode, Jakob Wolansky, Tobias Antrack, Hans Kleemann, Karl Leo
https://arxiv.org/abs/2506.11640…

Metallization of leaf-derived lignocellulose scaffolds for high performance flexible electronics and oligodynamic disinfection
Vascular tubules in natural leaves form quasi-fractal networks that can be metallized. Traditional metallization techniques for these lignocellulose structures are complex, involving metal sputtering, nanoparticle solutions, or multiple chemical pretreatments. Here we present a novel, facile, and reliable method for metallizing leaf-derived lignocellulose scaffolds using silver microparticles. The method achieves properties on-par with the state-of-the-art, such as broadband optical transmittan…

Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters
Elvis Rodrigues, Jacob Goldverg, Tevfik Kosar
https://arxiv.org/abs/2506.04117 http…

Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters
Inter-datacenter communication is a significant part of cloud operations and produces a substantial amount of carbon emissions for cloud data centers, where the environmental impact has already been a pressing issue. In this paper, we present a novel carbon-aware temporal data transfer scheduling framework, called LinTS, which promises to significantly reduce the carbon emission of data transfers between cloud data centers. LinTS produces a competitive transfer schedule and makes scaling decisi…

ChemReservoir -- An Open-Source Framework for Chemically-Inspired Reservoir Computing
Mehmet Aziz Yirik, Jakob Lykke Andersen, Rolf Fagerberg, Daniel Merkle
https://arxiv.org/abs/2506.04249

ChemReservoir -- An Open-Source Framework for Chemically-Inspired Reservoir Computing
Reservoir computing is a type of a recurrent neural network, mapping the inputs into higher dimensional space using fixed and nonlinear dynamical systems, called reservoirs. In the literature, there are various types of reservoirs ranging from in-silico to in-vitro. In cheminformatics, previous studies contributed to the field by developing simulation-based chemically inspired in-silico reservoir models. Yahiro used a DNA-based chemical reaction network as its reservoir and Nguyen developed a D…

High-throughput viscometry via machine-learning from videos of inverted vials
Ignacio Arretche, Mohammad Tanver Hossain, Ramdas Tiwari, Abbie Kim, Mya G. Mills, Connor D. Armstrong, Jacob J. Lessard, Sameh H. Tawfick, Randy H. Ewoldt
https://arxiv.org/abs/2506.02034

High-throughput viscometry via machine-learning from videos of inverted vials
Although the inverted vial test has been widely used as a qualitative method for estimating fluid viscosity, quantitative rheological characterization has remained limited due to its complex, uncontrolled flow - driven by gravity, surface tension, inertia, and initial conditions. Here, we present a computer vision (CV) viscometer that automates the inverted vial test and enables quantitative viscosity inference across nearly five orders of magnitude (0.01-1000 Pas), without requiring direct vel…

Retweets, Receipts, and Resistance: Discourse, Sentiment, and Credibility in Public Health Crisis Twitter
Tawfiq Ammari, Anna Gutowska, Jacob Ziff, Casey Randazzo, Harihan Subramonyam
https://arxiv.org/abs/2505.22032

Retweets, Receipts, and Resistance: Discourse, Sentiment, and Credibility in Public Health Crisis Twitter
As the COVID-19 pandemic evolved, the Centers for Disease Control and Prevention (CDC) used Twitter to disseminate safety guidance and updates, reaching millions of users. This study analyzes two years of tweets from, to, and about the CDC using a mixed methods approach to examine discourse characteristics, credibility, and user engagement. We found that the CDCs communication remained largely one directional and did not foster reciprocal interaction, while discussions around COVID19 were deepl…