Tootfinder

We have a game when we cook something nice of estimating what it would cost if eating out (not that our sometimes wonderful creations would be available).
So we keep finding (on occasional forays out) our prices are too low. E.g. City centre, for 2: 2 plates of indifferent ravioli, a bowl of olives and 2 glasses of wine pre-theatre came to more than £80!
Dining out ‘under pressure’ as Britons cut back due to price rises, says YouGov | Hospitality industry | The Guardian

Dynamics of Interacting Murnaghan-Equation-of-State Fluids with Global Monopole and Nonlinear Power-Yang-Mills Hair in Critical-Dimension AdS Black Holes
Yassine Sekhmani, Sunil Kumar Maurya, Javlon Rayimbaev, Mohamed Altanji, Inomjon Ibragimov, Alexandre Landry, Sokhibjan Muminov
https://arxiv.org/abs/2509.16728

Dynamics of Interacting Murnaghan-Equation-of-State Fluids with Global Monopole and Nonlinear Power-Yang-Mills Hair in Critical-Dimension AdS Black Holes
We construct and analyze a novel family of exact higher-dimensional black hole solutions in Einstein-Power-Yang-Mills gravity minimally coupled to a scalar field multiplet supporting a global monopole and a surrounding anisotropic ''scalar gas'' whose stress-energy obeys a generalized Murnaghan equation of state. By adopting the Wu-Yang magnetic ansatz for the non-Abelian sector and enforcing the physically motivated radial condition $p_r=-ρ$, the field equations admit closed-form expressions …

Computing the soft anomalous dimension with massless particles using the method of regions
Einan Gardi, Zehao Zhu
https://arxiv.org/abs/2509.18017 https://…

Computing the soft anomalous dimension with massless particles using the method of regions
It is well known that soft singularities of massless amplitudes are significantly simpler than those of massive ones. However, the computation of the soft anomalous dimension (AD) using Wilson-lines correctors is only straightforward in the massive case, thanks to the multiplicative renormalizability of correlators of non-lightlike Wilson lines. Instead, correlators involving lightlike lines, develop higher-order poles in dimensional regularization due to collinear singularities, on top of thei…

The Su-Schrieffer-Heeger model on a one-dimensional lattice: Analytical wave functions of topological edge states
Weibo Xu
https://arxiv.org/abs/2509.16708 https://

The Su-Schrieffer-Heeger model on a one-dimensional lattice: Analytical wave functions of topological edge states
The one-dimensional Su-Schrieffer-Heeger (SSH) model is a prototype model in the field of topological condensed matter physics, and the existence and characteristics of its topological edge states are crucial for revealing the topological essence of low-dimensional systems. This paper focuses on the analytical wave functions of topological edge states in the SSH model, systematically sorting out the fundamentals of model construction. Based on the tight-binding approximation, it derives the mat…

Shift Parallelism: Low-Latency, High-Throughput LLM Inference for Dynamic Workloads
Mert Hidayetoglu, Aurick Qiao, Michael Wyatt, Jeff Rasley, Yuxiong He, Samyam Rajbhandari
https://arxiv.org/abs/2509.16495

Shift Parallelism: Low-Latency, High-Throughput LLM Inference for Dynamic Workloads
Efficient parallelism is necessary for achieving low-latency, high-throughput inference with large language models (LLMs). Tensor parallelism (TP) is the state-of-the-art method for reducing LLM response latency, however GPU communications reduces combined token throughput. On the other hand, data parallelism (DP) obtains a higher throughput yet is slow in response latency. Best of both worlds does not exist, and it is not possible to combine TP and DP because of the KV cache variance across th…

MEF: A Systematic Evaluation Framework for Text-to-Image Models
Xiaojing Dong, Weilin Huang, Liang Li, Yiying Li, Shu Liu, Tongtong Ou, Shuang Ouyang, Yu Tian, Fengxuan Zhao
https://arxiv.org/abs/2509.17907

MEF: A Systematic Evaluation Framework for Text-to-Image Models
Rapid advances in text-to-image (T2I) generation have raised higher requirements for evaluation methodologies. Existing benchmarks center on objective capabilities and dimensions, but lack an application-scenario perspective, limiting external validity. Moreover, current evaluations typically rely on either ELO for overall ranking or MOS for dimension-specific scoring, yet both methods have inherent shortcomings and limited interpretability. Therefore, we introduce the Magic Evaluation Framewor…

Detection of long-range coherence in driven hot atomic vapors by spin noise spectroscopy
Rupak Bag, Sayari Majumder, Saptarishi Chaudhuri, Dibyendu Roy
https://arxiv.org/abs/2509.18036

Detection of long-range coherence in driven hot atomic vapors by spin noise spectroscopy
We study intriguing dynamical features of hot Rubidium atoms driven by two light fields. The fields resonantly drive multiple Zeeman states within two hyperfine levels, yielding a cascaded-$Λ$ like structure in the frequency space. A non-Hermitian Floquet tight-binding lattice with imaginary hopping between the nearest states effectively describes the coherence dynamics between Zeeman states within the ground hyperfine manifold. By performing spin noise spectroscopy, we observe higher harmonic…

Graphical Perception of Icon Arrays versus Bar Charts for Value Comparisons in Health Risk Communication
Jade Kandel, Jiayi Liu, Arran Zeyu Wang, Chin Tseng, Danielle Szafir
https://arxiv.org/abs/2509.16465

Graphical Perception of Icon Arrays versus Bar Charts for Value Comparisons in Health Risk Communication
Visualizations support critical decision making in domains like health risk communication. This is particularly important for those at higher health risks and their care providers, allowing for better risk interpretation which may lead to more informed decisions. However, the kinds of visualizations used to represent data may impart biases that influence data interpretation and decision making. Both continuous representations using bar charts and discrete representations using icon arrays are p…

Discrete Heat Kernels on Simplicial Complexes and Its Application to Functional Brain Networks
Sixtus Dakurah
https://arxiv.org/abs/2509.16908 https://arxi…

Discrete Heat Kernels on Simplicial Complexes and Its Application to Functional Brain Networks
Networks constitute fundamental organizational structures across biological systems, although conventional graph-theoretic analyses capture exclusively pairwise interactions, thereby omitting the intricate higher-order relationships that characterize network complexity. This work proposes a unified framework for heat kernel smoothing on simplicial complexes, extending classical signal processing methodologies from vertices and edges to cycles and higher-dimensional structures. Through Hodge Lap…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[6/12]:
- Localized Graph-Based Neural Dynamics Models for Terrain Manipulation
Chaoqi Liu, Yunzhu Li, Kris Hauser