Tootfinder

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics
Yi Yang, Kei Ikemura, Qingwen Zhang, Xiaomeng Zhu, Ci Li, Nazre Batool, Sina Sharif Mansouri, John Folkesson
https://arxiv.org/abs/2508.13979

AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics
Recent multi-task learning studies suggest that linear scalarization, when using well-chosen fixed task weights, can achieve comparable to or even better performance than complex multi-task optimization (MTO) methods. It remains unclear why certain weights yield optimal performance and how to determine these weights without relying on exhaustive hyperparameter search. This paper establishes a direct connection between linear scalarization and MTO methods, revealing through extensive experiments…

Stability of graphene hyperbolic pseudospheres under harsh conditions
T. P. C. Klaver, R. Gabbrielli, V. Tynianska, A. Iorio, D. Legut
https://arxiv.org/abs/2510.04699 https://

Stability of graphene hyperbolic pseudospheres under harsh conditions
We demonstrate the high stability of simulated graphene hyperbolic pseudospheres under large externally imposed deformations and high temperature annealing. Hyperbolic pseudospheres are produced in a two-step Molecular Dynamics simulation process. First, carbon atoms are forced down a thin three-dimensional volume of a chosen shape. During this extrusion process the carbon atoms form a precursor to graphene that is unrealistically less stable than graphite or diamond. Then the unstable carbon s…

Reservoir computing with large valid prediction time for the Lorenz system
Lauren A Hurley, Sean E Shaheen
https://arxiv.org/abs/2508.06730 https://arxiv.o…

Reservoir computing with large valid prediction time for the Lorenz system
We study the dependence of the Valid Prediction Time (VPT) of Reservoir Computers (RCs) on hyperparameters including the regularization coefficient, reservoir size, and spectral radius. Under carefully chosen conditions, the RC can achieve approximately 70% of a benchmark performance, based on the output of a single prediction step used as initial conditions for the Lorenz equations. We report high VPT values (>30 Lyapunov times), as we are predicting a noiseless system where overfitting can be…

Conformal dimension bounds, Pontryagin sphere boundaries, and algebraic fibering of right-angled Coxeter groups
Christopher H. Cashen, Pallavi Dani, Kevin Schreve, Emily Stark
https://arxiv.org/abs/2510.03430

Conformal dimension bounds, Pontryagin sphere boundaries, and algebraic fibering of right-angled Coxeter groups
We introduce a graph-theoretic condition, called $(n,m)$--branching, that ensures a combinatorial round tree with controlled branching parameters can be quasi-isometrically embedded in the Davis complex of the right-angled Coxeter group defined by the graph. This construction yields a lower bound on the conformal dimension of the boundary of such a hyperbolic group. We exhibit numerous families of graphs with this property, including many 1-dimensional spherical buildings. We prove an embeddi…

Emergent statistical mechanics in holographic random tensor networks
Shozab Qasim, Jens Eisert, Alexander Jahn
https://arxiv.org/abs/2508.16570 https://arx…

Emergent statistical mechanics in holographic random tensor networks
Recent years have enjoyed substantial progress in capturing properties of complex quantum systems by means of random tensor networks (RTNs), which form ensembles of quantum states that depend only on the tensor network geometry and bond dimensions. Of particular interest are RTNs on hyperbolic geometries, with local tensors typically chosen from the unitary Haar measure, that model critical boundary states of holographic bulk-boundary dualities. In this work, we elevate static pictures of ensem…

Universal $L_2$-approximation using median lattice algorithms
Zexin Pan, Takashi Goda, Peter Kritzer
https://arxiv.org/abs/2509.24582 https://arxiv.org/pdf…

Universal $L_2$-approximation using median lattice algorithms
We study the problem of multivariate $L_2$-approximation of functions in a weighted Korobov space using a median lattice-based algorithm recently proposed by the authors. In the original work, the algorithm requires knowledge of the smoothness and weights of the Korobov space to construct the hyperbolic cross index set, where each coefficient is estimated via the median of approximations obtained from randomly shifted, randomly chosen rank-1 lattice rules. In this paper, we introduce a \emph{un…

A meshless method for computational electromagnetics with improved dispersion properties
Andrej Kolar-Po\v{z}un, Gregor Kosec
https://arxiv.org/abs/2508.18205 https://

A meshless method for computational electromagnetics with improved dispersion properties
The finite difference time domain method is one of the most popular methods in computational electromagnetics. This work considers two possible ways of generalising it to a meshless setting by employing local radial basis function interpolation. The resulting methods turn out to be unstable, but can be stabilised by adding properly chosen hyperviscosity terms to the update equations. We demonstrate that the proposed meshless methods are convergent and can enjoy a decreased dispersion anisotropy…

First-order theory of torsion-free Tarski monsters
R\'emi Coulon, Francesco Fournier-Facio, Meng-Che "Turbo" Ho
https://arxiv.org/abs/2508.21244 https://

First-order theory of torsion-free Tarski monsters
We develop methods to control the first-order theory of groups arising as certain direct limits of torsion-free hyperbolic groups. We apply this to construct simple torsion-free Tarski monsters (non-abelian groups whose non-trivial, proper subgroups are infinite cyclic) with the same positive theory as the free group, answering several questions of Casals-Ruiz, Garreta, and de la Nuez González. Moreover, these groups may be chosen so that every non-trivial conjugacy-invariant norm is stably bo…