Tootfinder

Maxwell construction for a nonreciprocal Cahn-Hilliard model
Daniel Greve, Giorgio Lovato, Tobias Frohoff-H\"ulsmann, Uwe Thiele
https://arxiv.org/abs/2402.08634

Maxwell construction for a nonreciprocal Cahn-Hilliard model
We consider a class of continuum models with a spurious gradient dynamics structure that form a bridge between passive and active systems: They formally maintain variational properties similar to passive systems, but describe certain active systems with sustained out-of-equilibrium dynamics as, e.g., oscillatory instabilities. After introducing the general class of systems, we focus on the example of a nonreciprocal Cahn-Hilliard (NRCH) model, present a Maxwell construction for coexisting state…

Accounting for the Quantum Capacitance of Graphite in Constant Potential Molecular Dynamics Simulations
Kateryna Goloviznina, Johann Fleischhaker, Tobias Binninger, Benjamin Rotenberg, Heigo Ers, Vladislav Ivanistsev, Robert Meissner, Alessandra Serva, Mathieu Salanne
https://arxiv.org/abs/2404.07848

Accounting for the Quantum Capacitance of Graphite in Constant Potential Molecular Dynamics Simulations
Molecular dynamics simulations at a constant electric potential are an essential tool to study electrochemical processes, providing microscopic information on the structural, thermodynamic, and dynamical properties. Despite the numerous advances in the simulation of electrodes, they fail to accurately represent the electronic structure of materials such as graphite. In this work, we introduce a simple parameterization method that allows to tune the metallicity of the electrode based on a quantu…

Update: Death toll of Russian attack against Odesa rises to 4: https://benborges.xyz/2024/03/02/update-death-toll.html

Causality and extremes
Val\'erie Chavez-Demoulin, Linda Mhalla
https://arxiv.org/abs/2403.05331 https://arxiv.org/pdf/2403.05331<…

Causality and extremes
In this work, we summarize the state-of-the-art methods in causal inference for extremes. In a non-exhaustive way, we start by describing an extremal approach to quantile treatment effect where the treatment has an impact on the tail of the outcome. Then, we delve into two primary causal structures for extremes, offering in-depth insights into their identifiability. Additionally, we discuss causal structure learning in relation to these two models as well as in a model-agnostic framework. To il…

Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms
Per Kristian Lehre, Shishen Lin
https://arxiv.org/abs/2405.04480 https:/…

Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms
Runtime analysis, as a branch of the theory of AI, studies how the number of iterations algorithms take before finding a solution (its runtime) depends on the design of the algorithm and the problem structure. Drift analysis is a state-of-the-art tool for estimating the runtime of randomised algorithms, such as evolutionary and bandit algorithms. Drift refers roughly to the expected progress towards the optimum per iteration. This paper considers the problem of deriving concentration tail-bound…

Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs
Enzo Battistella, Sean English, Robert Green, Cliff Joslyn, Evgeniya Lagoda, Van Magnan, Audun Myers, Evan D. Nash, Michael Robinson
https://arxiv.org/abs/2405.04559

Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs
Hypergraphs have been a recent focus of study in mathematical data science as a tool to understand complex networks with high-order connections. One question of particular relevance is how to leverage information carried in hypergraph attributions when doing walk-based techniques. In this work, we focus on a new generalization of a walk in a network that recovers previous approaches and allows for a description of permissible walks in hypergraphs. Permissible walk graphs are constructed by inte…

A Sparse Tensor Generator with Efficient Feature Extraction
Tugba Torun, Eren Yenigul, Ameer Taweel, Didem Unat
https://arxiv.org/abs/2405.04944 https://…

A Sparse Tensor Generator with Efficient Feature Extraction
Sparse tensor operations are gaining attention in emerging applications such as social networks, deep learning, diagnosis, crime, and review analysis. However, a major obstacle for research in sparse tensor operations is the deficiency of a broad-scale sparse tensor dataset. Another challenge in sparse tensor operations is examining the sparse tensor features, which are not only important for revealing its nonzero pattern but also have a significant impact on determining the best-suited storage…

Update: Death toll of Russian attack against Odesa rises to 5: https://benborges.xyz/2024/03/02/155600.html

Species of structure and physical dimensions
Heinz-J\"urgen Schmidt
https://arxiv.org/abs/2404.19305 https://arxiv.org/pdf/2404.…

Species of structure and physical dimensions
This study addresses the often underestimated importance of physical dimensions and units in the formal reconstruction of physical theories, focusing on structuralist approaches that use the concept of ``species of structure" as a meta-mathematical tool. We are pursuing an approach that goes back to a suggestion by T.~Tao. It involves the representation of fundamental physical quantities by one-dimensional real ordered vector spaces, while derived quantities are formulated using concepts from l…

Update: Death toll of Russian attack against Odesa rises to 7: https://benborges.xyz/2024/03/02/174205.html