Tootfinder

Promotion digraphs
Rebecca Patrias, Oliver Pechenik, Jessica Striker
https://arxiv.org/abs/2508.10969 https://arxiv.org/pdf/2508.10969

Promotion digraphs
Work of Gaetz, Pechenik, Pfannerer, Striker, and Swanson (2024) introduced promotion permutations for a rectangular standard Young tableau $T$. These promotion permutations encode important features of $T$ and its orbit under Schützenberger's promotion operator. Indeed, the promotion permutations uniquely determine the tableau $T$. We introduce more general promotion digraphs for both standard and increasing tableaux of arbitrary shape. For rectangular standard tableaux, this construction re…

Arbeidernes frigjŸring må være arbeidernes eget verk!
⭐ Les mer her: #Anarkisme #Syndikalisme

Refining Motion for Peak Performance: Identifying Optimal Gait Parameters for Energy-Efficient Quadrupedal Bounding
Yasser G. Alqaham, Jing Cheng, Zhenyu Gan
https://arxiv.org/abs/2507.12751

Refining Motion for Peak Performance: Identifying Optimal Gait Parameters for Energy-Efficient Quadrupedal Bounding
Energy efficiency is a critical factor in the performance and autonomy of quadrupedal robots. While previous research has focused on mechanical design and actuation improvements, the impact of gait parameters on energetics has been less explored. In this paper, we hypothesize that gait parameters, specifically duty factor, phase shift, and stride duration, are key determinants of energy consumption in quadrupedal locomotion. To test this hypothesis, we modeled the Unitree A1 quadrupedal robot a…

Learn to optimize for automatic proton PBS treatment planning for H&N cancers
Qingqing Wang, Liqiang Xiao, Chang Chang
https://arxiv.org/abs/2508.11085 https://

Learn to optimize for automatic proton PBS treatment planning for H&N cancers
Proton PBS treatment planning for H&N cancers involves numerous conflicting objectives, requiring significant effort from human planners to balance and satisfy multiple clinical goals during planning. To achieve this, experience-demanding objective parameter adjustment and computationally expensive inverse optimization are performed iteratively. Extensive efforts have been made to automatically adjust objective parameters, but the most time-consuming component, i.e., inverse optimization, still…

The NAACP intends to sue xAI over the natural gas turbines at its Memphis data center, which it claims are polluting nearby predominantly Black neighborhoods (Hiroko Tabuchi/New York Times)
https://www.nytimes.…

Elon Musk’s AI Company Faces Lawsuit Over Gas-Burning Turbines
The company, xAI, has installed several dozen turbines in Memphis without proper permits, the group said, polluting a nearby community.

Space of conformal boundary conditions from the view of higher Berry phase: Flow of Berry curvature in parametrized BCFTs
Xueda Wen
https://arxiv.org/abs/2507.12546

Space of conformal boundary conditions from the view of higher Berry phase: Flow of Berry curvature in parametrized BCFTs
In this work, we study the connection between two subjects: the space of conformal boundary conditions in boundary conformal field theories (BCFTs) and the space of gapped systems characterized by higher Berry phases. We explore this connection by analyzing multi-parameter spectral flow in Dirac fermion BCFTs with continuously parametrized conformal boundary conditions, which are introduced by coupling a CFT to a family of gapped systems. When the gapped systems belong to a nontrivial higher Be…

Generation and certification of pure phase entangled light
Rounak Chatterjee, Mayuresh Kanagal, Vikas S Bhat, Kiran Bajar, Sushil Mujumdar
https://arxiv.org/abs/2508.11418 https…

Generation and certification of pure phase entangled light
Biphoton systems exhibiting entanglement in position-momentum variables, known as spatial entanglement, are among the most intriguing and well-studied phenomena in quantum optics. A notable subset of these are phase entangled states, where entanglement manifests purely through correlations in the spatial phase of the wavefunction. While the generation of such states from biphotons via spontaneous parametric down-conversion has been explored, their physical implications and applications remain u…

A Framework for Nonstationary Gaussian Processes with Neural Network Parameters
Zachary James, Joseph Guinness
https://arxiv.org/abs/2507.12262 https://

A Framework for Nonstationary Gaussian Processes with Neural Network Parameters
Gaussian processes have become a popular tool for nonparametric regression because of their flexibility and uncertainty quantification. However, they often use stationary kernels, which limit the expressiveness of the model and may be unsuitable for many datasets. We propose a framework that uses nonstationary kernels whose parameters vary across the feature space, modeling these parameters as the output of a neural network that takes the features as input. The neural network and Gaussian proce…

This heatwave in the Nordic EU? Oh, obviously climate change, courtesy of capitalism warming up the planet like it’s one big corporate sauna.
But hey, don’t blame me, I’m just here trying to cool off while CEOs keep printing profits instead of fixing the planet!
#Capitalism #AntiCapitalism

Accelerating RF Power Amplifier Design via Intelligent Sampling and ML-Based Parameter Tuning
Abhishek Sriram, Neal Tuffy
https://arxiv.org/abs/2507.11928 …

Accelerating RF Power Amplifier Design via Intelligent Sampling and ML-Based Parameter Tuning
This paper presents a machine learning-accelerated optimization framework for RF power amplifier design that reduces simulation requirements by 65% while maintaining $\pm0.3$ to $\pm0.4$ dBm accuracy. The proposed method combines MaxMin Latin Hypercube Sampling with CatBoost gradient boosting to intelligently explore multidimensional parameter spaces. Instead of exhaustively simulating all parameter combinations to achieve target P2dB compression specifications, our approach strategically selec…