Tootfinder

Unraveling Self-Similar Energy Transfer Dynamics: a Case Study for 1D Burgers System
Pritpal Matharu, Bartosz Protas, Tsuyoshi Yoneda
https://arxiv.org/abs/2507.12764

Unraveling Self-Similar Energy Transfer Dynamics: a Case Study for 1D Burgers System
In this work we consider the problem of constructing flow evolutions leading to a self-similar energy cascade consistent with Kolmogorov's statistical theory of turbulence. As a first step in this direction, we focus on the one-dimensional viscous Burgers equation as a toy model. Its solutions exhibiting self-similar behavior, in a precisely-defined sense, are found by framing this problems in terms of PDE-constrained optimization. The main physical parameters are the time window over which sel…

GenFlowRL: Shaping Rewards with Generative Object-Centric Flow in Visual Reinforcement Learning
Kelin Yu, Sheng Zhang, Harshit Soora, Furong Huang, Heng Huang, Pratap Tokekar, Ruohan Gao
https://arxiv.org/abs/2508.11049

GenFlowRL: Shaping Rewards with Generative Object-Centric Flow in Visual Reinforcement Learning
Recent advances have shown that video generation models can enhance robot learning by deriving effective robot actions through inverse dynamics. However, these methods heavily depend on the quality of generated data and struggle with fine-grained manipulation due to the lack of environment feedback. While video-based reinforcement learning improves policy robustness, it remains constrained by the uncertainty of video generation and the challenges of collecting large-scale robot datasets for tra…

DeltaHedge: A Multi-Agent Framework for Portfolio Options Optimization
Feliks Ba\'nka (Warsaw University of Technology, Faculty of Electronics,Information Technology), Jaros{\l}aw A. Chudziak (Warsaw University of Technology)
https://arxiv.org/abs/2509.12753

DeltaHedge: A Multi-Agent Framework for Portfolio Options Optimization
In volatile financial markets, balancing risk and return remains a significant challenge. Traditional approaches often focus solely on equity allocation, overlooking the strategic advantages of options trading for dynamic risk hedging. This work presents DeltaHedge, a multi-agent framework that integrates options trading with AI-driven portfolio management. By combining advanced reinforcement learning techniques with an ensembled options-based hedging strategy, DeltaHedge enhances risk-adjusted…

Testing and benchmarking emerging supercomputers via the MFC flow solver
Benjamin Wilfong, Anand Radhakrishnan, Henry A. Le Berre, Tanush Prathi, Stephen Abbott, Spencer H. Bryngelson
https://arxiv.org/abs/2509.13575

Testing and benchmarking emerging supercomputers via the MFC flow solver
Deploying new supercomputers requires testing and evaluation via application codes. Portable, user-friendly tools enable evaluation, and the Multicomponent Flow Code (MFC), a computational fluid dynamics (CFD) code, addresses this need. MFC is adorned with a toolchain that automates input generation, compilation, batch job submission, regression testing, and benchmarking. The toolchain design enables users to evaluate compiler-hardware combinations for correctness and performance with limited s…

Distributed Coherent Beamforming at 60 GHz Enabled by Optically-Established Coherence
Drake Silbernagel, Yu Rong, Isabella Lenz, Prithvi Hemanth, Carl Morgenstern, Owen Ma, Nolan Matthews, Nader Zaki, Kyle W. Martin, John D. Elgin, Jacob Holtom, Daniel W. Bliss, Kimberly Frey
https://arxiv.org/abs/2509.13984

Distributed Coherent Beamforming at 60 GHz Enabled by Optically-Established Coherence
We implement and experimentally demonstrate a 60 GHz distributed system leveraging an optical time synchronization system that provides precise time and frequency alignment between independent elements of the distributed mesh. Utilizing such accurate coherence, we perform receive beamforming with interference rejection and transmit nulling. In these configurations, the system achieves a coherent gain over an incoherent network of N nodes, significantly improving the relevant signal power ratios…

Dust trapping in protoplanetary discs after stellar flybys
Vasundhara R. Prasad, Cristiano Longarini, Cathie J. Clarke
https://arxiv.org/abs/2509.11909 https://

Dust trapping in protoplanetary discs after stellar flybys
Stellar flybys are likely to be common in young star-forming regions and could be responsible for substructures observed in protoplanetary discs. Using three-dimensional smoothed particle hydrodynamics simulations, we study dust trapping in discs perturbed by parabolic coplanar flybys. We find that spiral structures are induced in the gas and dust discs for both prograde and retrograde encounters. By tracking individual dust particles within the flyby-induced substructures, we determine that th…

Astro-MoE: Mixture of Experts for Multiband Astronomical Time Series
Martina C\'adiz-Leyton, Guillermo Cabrera-Vives, Pavlos Protopapas, Daniel Moreno-Cartagena, Ignacio Becker
https://arxiv.org/abs/2507.12611

Astro-MoE: Mixture of Experts for Multiband Astronomical Time Series
Multiband astronomical time series exhibit heterogeneous variability patterns, sampling cadences, and signal characteristics across bands. Standard transformers apply shared parameters to all bands, potentially limiting their ability to model this rich structure. In this work, we introduce Astro-MoE, a foundational transformer architecture that enables dynamic processing via a Mixture of Experts module. We validate our model on both simulated (ELAsTiCC-1) and real-world datasets (Pan-STARRS1).

ViScratch: Using Large Language Models and Gameplay Videos for Automated Feedback in Scratch
Yuan Si, Daming Li, Hanyuan Shi, Jialu Zhang
https://arxiv.org/abs/2509.11065 https:…

ViScratch: Using Large Language Models and Gameplay Videos for Automated Feedback in Scratch
Block-based programming environments such as Scratch are increasingly popular in programming education, in particular for young learners. While the use of blocks helps prevent syntax errors, semantic bugs remain common and difficult to debug. Existing tools for Scratch debugging rely heavily on predefined rules or user manual inputs, and crucially, they ignore the platform's inherently visual nature. We introduce ViScratch, the first multimodal feedback generation system for Scratch that leve…

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks
Sheng Xu, Lile Wang, Luis C. Ho, Renyue Cen, Shenzhen Xu
https://arxiv.org/abs/2509.11036

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks
The inner regions of protoplanetary disks are host to the sublimation of dust grains, a process traditionally modeled using equilibrium thermodynamics. We demonstrate through ab-initio density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations that silicate dust sublimation is inherently a non-equilibrium kinetic process. The binding energies and vibrational frequencies governing desorption, calculated for MgSiO3 and other compositions, reveal that sublimation timescales far exce…

Asymmetric radiation in binary systems: Implications for disk evolution and chemistry
Pedro P. Poblete, Nicol\'as Cuello, Antoine Alaguero, Daniel J. Price, Eleonora Bianchi, Christophe Pinte, Fran\c{c}ois Menard
https://arxiv.org/abs/2509.12898

Asymmetric radiation in binary systems: Implications for disk evolution and chemistry
Current models of binary systems often depend on simplified approach of the radiation field, which are unlikely to accurately capture the complexities of asymmetric environments. We investigate the dynamical and chemical implications of a 3D asymmetric radiation field that accounts for the optical properties of sub-structures present in a protoplanetary disk, as well as the inclusion of a secondary radiation source in binary systems. We conducted a series of 3D-SPH hydrodynamical simulations us…