Tootfinder

Quantitative Mapping of the Loeb Scale
Oem Trivedi, Abraham Loeb
https://arxiv.org/abs/2509.06253 https://arxiv.org/pdf/2509.06253

Quantitative Mapping of the Loeb Scale
The recent discovery of a third interstellar object (ISO) 3I/ATLAS, following 1I/`Oumuamua and 2I/Borisov, has raised questions about the nature and origin of these enigmatic objects. With the Vera C. Rubin Observatory expected to discover dozens of new ISOs over the next decade, it is timely to use a classification scheme for their nature in the context of the recently proposed Loeb scale. Here, we provide a formalism for ranking ISOs quantitatively on the Loeb Scale in analogy to Sagan's form…

UDON: Uncertainty-weighted Distributed Optimization for Multi-Robot Neural Implicit Mapping under Extreme Communication Constraints
Hongrui Zhao, Xunlan Zhou, Boris Ivanovic, Negar Mehr
https://arxiv.org/abs/2509.12702

UDON: Uncertainty-weighted Distributed Optimization for Multi-Robot Neural Implicit Mapping under Extreme Communication Constraints
Multi-robot mapping with neural implicit representations enables the compact reconstruction of complex environments. However, it demands robustness against communication challenges like packet loss and limited bandwidth. While prior works have introduced various mechanisms to mitigate communication disruptions, performance degradation still occurs under extremely low communication success rates. This paper presents UDON, a real-time multi-agent neural implicit mapping framework that introduces …

CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps
Franz Hanke, Antonia Bieringer, Olaf Wysocki, Boris Jutzi
https://arxiv.org/abs/2508.15672 https://

CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps
Detailed 3D building models are crucial for urban planning, digital twins, and disaster management applications. While Level of Detail 1 (LoD)1 and LoD2 building models are widely available, they lack detailed facade elements essential for advanced urban analysis. In contrast, LoD3 models address this limitation by incorporating facade elements such as windows, doors, and underpasses. However, their generation has traditionally required manual modeling, making large-scale adoption challenging. …

Compact R-Continuity with Applications to Solving Inclusions and Convergence of Algorithms
Ba Khiet Le, Boris S. Mordukhovich, Michel A. Thera
https://arxiv.org/abs/2509.01872 h…

Compact R-Continuity with Applications to Solving Inclusions and Convergence of Algorithms
This paper investigates the notion of compact R-continuity and its specifications for set-valued mappings between Banach spaces. We reveal several important properties of compact R-continuity in general settings and show that in finite dimensions, this notion is supported by the classical Łojasiewicz inequality for analytic functions. An application of compact R-continuity and the obtained results {is} given to convergence analysis for a broad class of descent algorithms in nonsmooth optimizat…

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination
David Nunez, Francesc Wilhelmi, Maksymilian Wojnar, Katarzyna Kosek-Szott, Szymon Szott, Boris Bellalta
https://arxiv.org/abs/2507.19377

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination
Multi-access point coordination (MAPC) is a key feature of IEEE 802.11bn, with a potential impact on future Wi-Fi networks. MAPC enables joint scheduling decisions across multiple access points (APs) to improve throughput, latency, and reliability in dense Wi-Fi deployments. However, implementing efficient scheduling policies under diverse traffic and interference conditions in overlapping basic service sets (OBSSs) remains a complex task. This paper presents a method to minimize the network-wi…

CMB component-separated power spectrum estimation by Spectral Internal Linear Combination (SpILC)
Jack Y. L. Kwok, William R. Coulton, Niall MacCrann, Fiona McCarthy, Blake D. Sherwin, Boris Bolliet
https://arxiv.org/abs/2509.10604

CMB component-separated power spectrum estimation by Spectral Internal Linear Combination (SpILC)
Component separation methods mitigate the cross-contamination between different extragalactic and galactic contributions to cosmic microwave background (CMB) data. This is often done by linearly combining CMB maps from different frequency channels using internal linear combination (ILC) methods. We demonstrate that deriving power spectrum estimators directly by linearly combining auto- and cross-spectra instead of maps allows us to obtain a different constrained-optimization problem that allows…

Rigidity of strong and weak foliations
Boris Kalinin, Victoria Sadovskaya
https://arxiv.org/abs/2509.13986 https://arxiv.org/pdf/2509.13986

Rigidity of strong and weak foliations
We consider a perturbation $f$ of a hyperbolic toral automorphism $L$. We study rigidity related to exceptional properties of the strong and weak stable foliations for $f$. If the strong foliation is mapped to the linear one by the conjugacy $h$ between $f$ and $L$, we obtain smoothness of $h$ along the weak foliation and regularity of the joint foliation of the strong and unstable foliations. We also establish a similar global result. If the weak foliation is sufficiently regular, we obtain sm…