Tootfinder

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
R. Montal\`a, B. Font, P. Su\'arez, J. Rabault, O. Lehmkuhl, R. Vinuesa, I. Rodriguez
https://arxiv.org/abs/2509.10185

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
In this work, deep reinforcement learning (DRL) is applied to active flow control (AFC) over a threedimensional SD7003 wing at a Reynolds number of Re = 60,000 and angle of attack of AoA = 14 degrees. In the uncontrolled baseline case, the flow exhibits massive separation and a fully turbulent wake. Using a GPU-accelerated CFD solver and multi-agent training, DRL discovers control strategies that enhance lift (79%), reduce drag (65%), and improve aerodynamic efficiency (408%). Flow visualizatio…

Kumulativer Zubau der #Windenergieleistung in #Deutschland mit Stand vom 13.11.2025.
Summen der Inbetriebnahmen minus Stilllegungen pro Jahr.
Der Datenbestand enthält ggf. unplausible Datensätze.
👉 Zusatzlesestoff: Warum

Wie kann man #Fruchtfliegen mit einfachen Hausmitteln loswerden? 🍎🐜 Mit einer Mischung aus #Essig, Wasser und #Spülmittel in einem Glas kannst Du eine wirksame Falle bauen. Alternativ lässt …

Fruchtfliegen bekämpfen mit Hausmitteln
Im Handel gibt es diverse Fiegenfallen zu kaufen, die dann auch wieder nur Müll verursachen. Fruchtfliegen kann man aber auch mit Hausmitteln beikommen.

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
Julia Gastinger, Christian Meilicke, Heiner Stuckenschmidt
https://arxiv.org/abs/2509.09474 https…

CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting
We address the task of temporal knowledge graph (TKG) forecasting by introducing a fully explainable method based on temporal rules. Motivated by recent work proposing a strong baseline using recurrent facts, our approach learns four simple types of rules with a confidence function that considers both recency and frequency. Evaluated on nine datasets, our method matches or surpasses the performance of eight state-of-the-art models and two baselines, while providing fully interpretable predictio…

Pump-driven droplet electrohydrodynamics: deformation, pinch-off and recoalescence
Yuzhe Qin, Huaxiong Huang, Zilong Song, Shixin Xu
https://arxiv.org/abs/2509.09834 https://

Pump-driven droplet electrohydrodynamics: deformation, pinch-off and recoalescence
We investigate pump-driven droplet electrohydrodynamics with an emphasis on deformation, pinch-off, and recoalescence. A thermodynamically consistent phase-field framework is developed that couples Nernst--Planck--Poisson electrodiffusion with incompressible Navier--Stokes--Cahn--Hilliard flow, and incorporates interfacial ionic pumps as prescribed surface fluxes. In the pump-free baseline, applied fields merely polarise the droplet and deformation is negligible. By contrast, surface-localised …

When you’ve spent almost nine hours inside the vortex of Psytrance, you can bet it’s my favorite genre of all time, because once you’re hooked on 145 BPM the line between hearing and being the music completely disappears.
The bassline doesn’t just sit in the background, it takes command with ruthless precision, rewiring thought into rhythm and heartbeat into tempo, proving again and again that Psytrance isn’t just what I listen to, it’s the sound I belong to.
By the time the flow…

On the Propagation and Damping of Alfvenic Fluctuations in the Outer Solar Corona and Solar Wind
Nikos Sioulas, Marco Velli, Chen Shi, Trevor A. Bowen, Alfred Mallet, Andrea Verdini, B. D. G. Chandran, Anna Tenerani, Jean-Baptiste Dakeyo, Stuart D. Bale, Davin Larson, Jasper S. Halekas, Lorenzo Matteini, Victor R\'eville, C. H. K. Chen, Orlando M. Romeo, Mingzhe Liu, Roberto Livi, Ali Rahmati, P. L. Whittlesey

On the Propagation and Damping of Alfvenic Fluctuations in the Outer Solar Corona and Solar Wind
We analyze \textit{Parker Solar Probe} and \textit{Solar Orbiter} observations to investigate the propagation and dissipation of Alfvénic fluctuations from the outer corona to 1~AU. Conservation of wave-action flux provides the theoretical baseline for how fluctuation amplitudes scale with the Alfvén Mach number $M_a$, once solar-wind acceleration is accounted for. Departures from this scaling quantify the net balance between energy injection and dissipation. Fluctuation amplitudes follow wav…

Towards bridging the gap: Systematic sim-to-real transfer for diverse legged robots
Filip Bjelonic, Fabian Tischhauser, Marco Hutter
https://arxiv.org/abs/2509.06342 https://

Towards bridging the gap: Systematic sim-to-real transfer for diverse legged robots
Legged robots must achieve both robust locomotion and energy efficiency to be practical in real-world environments. Yet controllers trained in simulation often fail to transfer reliably, and most existing approaches neglect actuator-specific energy losses or depend on complex, hand-tuned reward formulations. We propose a framework that integrates sim-to-real reinforcement learning with a physics-grounded energy model for permanent magnet synchronous motors. The framework requires a minimal para…

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD
Javier Mari\~no Villadamigo, Rikkert Frederix, Tilman Plehn, Timea Vitos, Ramon Winterhalder
https://arxiv.org/abs/2509.07068

FASTColor -- Full-color Amplitude Surrogate Toolkit for QCD
High-multiplicity events remain a bottleneck for LHC simulations due to their computational cost. We present a ML-surrogate approach to accelerate matrix element reweighting from leading-color (LC) to full-color (FC) accuracy, building on recent advancements in LC event generation. Comparing a variety of modern network architectures for representative QCD processes, we achieve speed-up of around a factor two over the current LC-to-FC baseline. We also show how transformers learn and exploit und…

Leveraging Whisper Embeddings for Audio-based Lyrics Matching
Eleonora Mancini, Joan Serr\`a, Paolo Torroni, Yuki Mitsufuji
https://arxiv.org/abs/2510.08176 https://

Leveraging Whisper Embeddings for Audio-based Lyrics Matching
Audio-based lyrics matching can be an appealing alternative to other content-based retrieval approaches, but existing methods often suffer from limited reproducibility and inconsistent baselines. In this work, we introduce WEALY, a fully reproducible pipeline that leverages Whisper decoder embeddings for lyrics matching tasks. WEALY establishes robust and transparent baselines, while also exploring multimodal extensions that integrate textual and acoustic features. Through extensive experiments…