Tootfinder

Numerical investigation of engine position effects on contrail formation and evolution in the near-field of a realistic aircraft configuration
R\'emy Annunziata (ETS), Nicolas Bonne (ETS), Fran\c{c}ois Garnier (ETS)
https://arxiv.org/abs/2508.02706

Numerical investigation of engine position effects on contrail formation and evolution in the near-field of a realistic aircraft configuration
The present study investigates the impact of engine position on contrail formation and near-field evolution in a realistic three-dimensional aircraft configuration. Detailed numerical simulations are conducted using a Reynolds-Averaged Navier-Stokes (RANS) approach coupled with mesh adaptation techniques. A Eulerian microphysical model is used to characterize contrail ice crystal properties and their evolution under varying dilution conditions. The setup is based on a Boeing 777-like geometry, …

This https://arxiv.org/abs/2403.06708 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Tikhonov Regularization for Stochastic Non-Smooth Convex Optimization in Hilbert Spaces
To solve convex optimization problems with a noisy gradient input, we analyze the global behavior of subgradient-like flows under stochastic errors. The objective function is composite, being equal to the sum of two convex functions, one being differentiable and the other potentially non-smooth. We then use stochastic differential inclusions where the drift term is minus the subgradient of the objective function, and the diffusion term is either bounded or square-integrable. In this context, un…

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems
Jiayi Chen, Junyi Ye, Guiling Wang
https://arxiv.org/abs/2506.04565 https:…

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems
Compound Al Systems (CAIS) is an emerging paradigm that integrates large language models (LLMs) with external components, such as retrievers, agents, tools, and orchestrators, to overcome the limitations of standalone models in tasks requiring memory, reasoning, real-time grounding, and multimodal understanding. These systems enable more capable and context-aware behaviors by composing multiple specialized modules into cohesive workflows. Despite growing adoption in both academia and industry, …

Exploring listeners' perceptions of AI-generated and human-composed music for functional emotional applications
Kimaya Lecamwasam, Tishya Ray Chaudhuri
https://arxiv.org/abs/2506.02856

Exploring listeners' perceptions of AI-generated and human-composed music for functional emotional applications
This work investigates how listeners perceive and evaluate AI-generated as compared to human-composed music in the context of emotional resonance and regulation. Across a mixed-methods design, participants were exposed to both AI and human music under various labeling conditions (music correctly labeled as AI- or human-origin, music incorrectly labeled as AI- or human-origin, and unlabeled music) and emotion cases (Calm and Upbeat), and were asked to rate preference, efficacy of target emotion …

This https://arxiv.org/abs/2501.00325 has been replaced.
initial toot: https://mastoxiv.page/@a…

Deeper insight into the terahertz response of conventional superconductors under magnetic field
We investigate the terahertz conductivity of conventional superconductors in Voigt and Faraday magneto-optical configurations. First, we review theoretical approaches describing the fundamental processes of suppression of superconductivity in magnetic field and how the in-gap states are filled. In the Voigt geometry, thin superconducting films are fully penetrated by the magnetic field which interacts with the spin, thus modifying the magnitudes of the optical gap and of the density of the cond…

This https://arxiv.org/abs/2503.01600 has been replaced.
initial toot: https://mastoxiv.page/@a…

Is Triboelectricity Confusing, Confused or Complex?
In this report, we look at the fundamental physics of triboelectricity, charge transfer due to contact and sliding. While much of the report focuses upon recent advances such as the incorporation of flexoelectric contributions, we also include older work, some from centuries ago, which only now can be understood in a general sense. Basic concepts and theories ranging from elements of tribology and contact mechanics through semiconductor built-in potentials, electromechanical terms, mechanochemi…

This https://arxiv.org/abs/2505.04316 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

On local fields invariant under the action of topological defects
In the context of rational conformal field theories (RCFT) we look into the problem of constructing and classifying pairs consisting of a local operator and a topological defect which commutes or anticommutes with it. We discuss the bulk and boundary versions of the problem. In the latter one considers a conformal boundary condition, a boundary operator on it and a junction with a topological defect. In the case of the charge conjugation modular invariant commuting configurations in each proble…

Effective Explanations for Belief-Desire-Intention Robots: When and What to Explain
Cong Wang, Roberto Calandra, Verena Kl\"os
https://arxiv.org/abs/2507.02016

Effective Explanations for Belief-Desire-Intention Robots: When and What to Explain
When robots perform complex and context-dependent tasks in our daily lives, deviations from expectations can confuse users. Explanations of the robot's reasoning process can help users to understand the robot intentions. However, when to provide explanations and what they contain are important to avoid user annoyance. We have investigated user preferences for explanation demand and content for a robot that helps with daily cleaning tasks in a kitchen. Our results show that users want explanatio…

LCQNN: Linear Combination of Quantum Neural Networks
Hongshun Yao, Xia Liu, Mingrui Jing, Xin Wang
https://arxiv.org/abs/2507.02832 https://

LCQNN: Linear Combination of Quantum Neural Networks
Quantum neural networks combine quantum computing with advanced data-driven methods, offering promising applications in quantum machine learning. However, the optimal paradigm of quantum neural networks in the context trainability and expressivity remains an open question. To overcome this issue, we first introduce a framework called Linear Combination of Quantum Neural Networks (LCQNN), which leverages the linear combination of unitaries concept to coordinate the composition of QNNs, thereby b…

Ultralow Lattice Thermal Conductivity Induced by Quasi-Chain Configuration in Rb2Se3
Tiantian Jia, Yongsen Tang, Yongsheng Zhang
https://arxiv.org/abs/2507.21634 https://…

Ultralow Lattice Thermal Conductivity Induced by Quasi-Chain Configuration in Rb2Se3
Alkali metal-based compounds have garnered significant attention due to their exceptionally low lattice thermal conductivity, which is crucial for applications in thermoelectric energy conversion and thermal barrier coatings. However, the fundamental mechanisms underlying such ultralow lattice thermal conductivity remain poorly understood. In this study, we investigate the intrinsic origins of the ultralow lattice thermal conductivity in the alkali metal-based ionic compound Rb2Se3, which exhib…