Tootfinder

Today, the culturally set goal (via capitalism) for every human is to maximize their accumulation of capital. This goal is killing us all. If you could, somehow, set a different goal, what would it be?
This is perhaps a bit of a #SolarPunk question.

Behavior of passive polymeric tracers of different topologies in a dilute bath of active Brownian particles
Ramanand Singh Yadav, Ralf Metzler, Rajarshi Chakrabarti
https://arxiv.org/abs/2510.11337

Behavior of passive polymeric tracers of different topologies in a dilute bath of active Brownian particles
Using computer simulations in two dimensions we investigate the dynamics and structure of passive polymeric tracer with different topologies immersed in a low-density active particle bath. One of the key observations is that polymer exhibit faster dynamics compared to passive colloidal particles at high activity, for the same particle density, in both linear and star polymer topologies. This enhanced motion is attributed to the accumulation of active particles, which induces prolonged and persi…

Nonequilibrium spin-splitter effect in altermagnet superconductor hybrids
Tim Kokkeler, Tero T. Heikkil\"a, F. Sebastian Bergeret
https://arxiv.org/abs/2510.11355 https://

Nonequilibrium spin-splitter effect in altermagnet superconductor hybrids
We study the nonequilibrium spin-splitter effect in superconducting altermagnets and superconductor altermagnet hybrids by computing the alternating spin current and edge the spin density in the presence of an alternating electric field. We show that while in the normal state the effect is not sensitive to the field frequency, in the superconducting state, there is a strong effect for frequencies on the scale of $Δ_0$ or lower. We contrast the effect to the spin accumulation induced by the spi…

Confinement reduces surface accumulation of swimming bacteria
Da Wei, Shiyuan Hu, Tangmiao Tang, Yaochen Yang, Fanlong Meng, Yi Peng
https://arxiv.org/abs/2510.08092 https://

Confinement reduces surface accumulation of swimming bacteria
Many swimming bacteria naturally inhabit confined environments, yet how confinement influences their swimming behaviors remains unclear. Here, we combine experiments, continuum modeling and particle-based simulations to investigate near-surface bacterial swimming in dilute suspensions under varying confinement. Confinement reduces near-surface accumulation and facilitates bacterial escape. These effects are quantitatively captured by models incorporating the force quadrupole, a higher-order hyd…

Defect-driven incoherent skin localization
Emmanouil T. Kokkinakis, Konstantinos G. Makris, Eleftherios N. Economou
https://arxiv.org/abs/2510.10298 https://

Defect-driven incoherent skin localization
The process of dephasing during wave evolution has traditionally been viewed as an obstacle to localization, leading to diffusion even in strongly disordered Hermitian lattices. In contrast, here we demonstrate how the interplay of dephasing with non-Hermitian defects can be harnessed to engineer wave localization. Specifically, we identify a novel dynamical localization phenomenon characterized by wavefunction accumulation at the lattice's boundary due solely to dephasing, despite globally rec…

Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
Evgenii Opryshko, Junwei Quan, Claas Voelcker, Yilun Du, Igor Gilitschenski
https://arxiv.org/abs/2510.07257 h…

Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
Offline goal-conditioned reinforcement learning (GCRL) trains policies that reach user-specified goals at test time, providing a simple, unsupervised, domain-agnostic way to extract diverse behaviors from unlabeled, reward-free datasets. Nonetheless, long-horizon decision making remains difficult for GCRL agents due to temporal credit assignment and error accumulation, and the offline setting amplifies these effects. To alleviate this issue, we introduce Test-Time Graph Search (TTGS), a lightwe…

SatFusion: A Unified Framework for Enhancing Satellite IoT Images via Multi-Temporal and Multi-Source Data Fusion
Yufei Tong, Guanjie Cheng, Peihan Wu, Yicheng Zhu, Kexu Lu, Feiyi Chen, Meng Xi, Junqin Huang, Shuiguang Deng
https://arxiv.org/abs/2510.07905

SatFusion: A Unified Framework for Enhancing Satellite IoT Images via Multi-Temporal and Multi-Source Data Fusion
With the rapid advancement of the digital society, the proliferation of satellites in the Satellite Internet of Things (Sat-IoT) has led to the continuous accumulation of large-scale multi-temporal and multi-source images across diverse application scenarios. However, existing methods fail to fully exploit the complementary information embedded in both temporal and source dimensions. For example, Multi-Image Super-Resolution (MISR) enhances reconstruction quality by leveraging temporal compleme…

RLinf-VLA: A Unified and Efficient Framework for VLA RL Training
Hongzhi Zang, Mingjie Wei, Si Xu, Yongji Wu, Zhen Guo, Yuanqing Wang, Hao Lin, Liangzhi Shi, Yuqing Xie, Zhexuan Xu, Zhihao Liu, Kang Chen, Wenhao Tang, Quanlu Zhang, Weinan Zhang, Chao Yu, Yu Wang
https://arxiv.org/abs/2510.06710

RLinf-VLA: A Unified and Efficient Framework for VLA+RL Training
Recent progress in vision and language foundation models has significantly advanced multimodal understanding, reasoning, and generation, inspiring a surge of interest in extending such capabilities to embodied settings through vision-language-action (VLA) models. Yet, most VLA models are still trained with supervised fine-tuning (SFT), which struggles to generalize under distribution shifts due to error accumulation. Reinforcement learning (RL) offers a promising alternative by directly optimiz…

Satellite Navigation and Control using Physics-Informed Artificial Potential Field and Sliding Mode Controller
Rakesh Kumar Sahoo, Paridhi Choudhary, Manoranjan Sinha
https://arxiv.org/abs/2510.08184

Satellite Navigation and Control using Physics-Informed Artificial Potential Field and Sliding Mode Controller
Increase in the number of space exploration missions has led to the accumulation of space debris, posing risk of collision with the operational satellites. Addressing this challenge is crucial for the sustainability of space operations. To plan a safe trajectory in the presence of moving space debris, an integrated approach of artificial potential field and sliding mode controller is proposed and implemented in this paper. The relative 6-DOF kinematics and dynamics of the spacecraft is modelled…

Entropy and diffusion characterize mutation accumulation and biological information loss
Stephan Baehr, Hans Baehr
https://arxiv.org/abs/2510.07265 https://

Entropy and diffusion characterize mutation accumulation and biological information loss
Aging is a universal consequence of life, yet researchers have identified no universal theme. This manuscript considers aging from the perspective of entropy, wherein things fall apart. We first examine biological information change as a mutational distance, analogous to physical distance. In this model, informational change over time is fitted to an advection-diffusion equation, a normal distribution with a time component. The solution of the advection-diffusion equation provides a means of me…

My artist's statement on my work with AI is out. I completely rethought what I am doing. This has been a worthwhile journey, for me, and I hope, for you if you read it.
https://varnelis.net/works_and_projects/stochastic-histories/

Stochastic Histories - varnelis.net
stochastic histories /stəˈkæstɪk ˈhɪstəriz/ n. pl. [from Gk. stokhastikos “capable of guessing,” from stokhazesthai “to aim at, guess at” + L. historia “narrative, account”] 1. Fabricated historical narratives generated through iterative probabilistic sampling with artificial-intelligence systems, producing documentation that appears authentic through the accumulation of plausible details. 2. A mode of artistic practice that exploits ...

Rolling Forcing: Autoregressive Long Video Diffusion in Real Time
Kunhao Liu, Wenbo Hu, Jiale Xu, Ying Shan, Shijian Lu
https://arxiv.org/abs/2509.25161 https://

Rolling Forcing: Autoregressive Long Video Diffusion in Real Time
Streaming video generation, as one fundamental component in interactive world models and neural game engines, aims to generate high-quality, low-latency, and temporally coherent long video streams. However, most existing work suffers from severe error accumulation that often significantly degrades the generated stream videos over long horizons. We design Rolling Forcing, a novel video generation technique that enables streaming long videos with minimal error accumulation. Rolling Forcing comes …

RIGEL: Feedback regulated cloud-scale star formation efficiency in a simulated dwarf galaxy merger
Yunwei Deng, Hui Li, Federico Marinacci, Yang Ni, Boyuan Liu, Aaron Smith, Rahul Kannan, Greg L. Bryan
https://arxiv.org/abs/2510.07368

RIGEL: Feedback regulated cloud-scale star formation efficiency in a simulated dwarf galaxy merger
Major mergers of galaxies are likely to trigger bursty star formation activities. The accumulation of dense gas and the boost of star formation efficiency (SFE) are considered to be the two main drivers of the starbursts. However, it is still unclear how each process operates on the scale of individual star-forming clouds. Here, we present a high-resolution (2 Msun) RHD simulation of a gas-rich dwarf galaxy merger using the RIGEL model to investigate how mergers affect the properties of the str…

Effect of Stokes number on erosion on Pelton buckets for sediment-laden flows
Aron Dagur Beck, Elena Vagnoni
https://arxiv.org/abs/2510.08036 https://arxiv…

Effect of Stokes number on erosion on Pelton buckets for sediment-laden flows
With increased glacial melting and the need to maintain sediment continuity for ecosystem health, sediment-laden flows through hydropower plants are becoming increasingly problematic, particularly due to erosion on runner blades and buckets. A widely used mitigation strategy is the use of filters to protect Pelton turbines. However, these filters lead to rapid sediment accumulation in reservoirs, which must be drained frequently to maintain storage capacity. The high cost of such drainage opera…

Intrinsic spin accumulation in magnetic spin Hall effect
Atsuo Shitade
https://arxiv.org/abs/2509.24719 https://arxiv.org/pdf/2509.24719

Intrinsic spin accumulation in magnetic spin Hall effect
The magnetic spin Hall effect is a time-reversal-odd phenomenon in which spin current is induced by the charge current. In the presence of a spin-orbit coupling and/or noncolinear magnetism, however, spin current is not uniquely defined. Instead, we study an intrinsic response of spin to an electric field gradient that describes the spin accumulation at the boundaries of magnetic systems. We derive a generic formula expressed by Bloch wave functions and apply it to a minimal model for represent…

Une hausse de température de 10 degrés lors d’une vague de chaleur extrême participe en moyenne Š « doubler le taux de dégradation du plastique » accélérant ainsi l'accumulation des petits fragments dans les chaînes alimentaires.
#Plastique #climat

Nombres de Pisot, nombres de Salem et la conjecture de Lehmer
Mohamed Amara
https://arxiv.org/abs/2509.21402 https://arxiv.org/pdf/2509.21402

Nombres de Pisot, nombres de Salem et la conjecture de Lehmer
We investigate the relationship between the set S of Pisot numbers and the set T of Salem numbers. Salem first established that: " every Pisot number is an accumulation point of the set T ". Building on Boyd's method, we show that every accumulation point of T belongs to S. Together, these results imply that the union S U T forms a closed subset of the real half-line ]1,+infinity[. Consequently, this settles Boyd's conjecture while disproving Lehmer's conjecture.

but but the tariffs! 🙃
https://journa.host/@samlitzinger/115420385933741234

How Kamada doesn’t have a yellow card is a real mystery to me. If not for hacking away then for accumulation.
#LFC

Probing quantum advantage for solving the Fermi-Hubbard model with entropy benchmarking
Pauline Besserve, Ra\'ul Garc\'ia-Patr\'on
https://arxiv.org/abs/2510.00930 h…

Probing quantum advantage for solving the Fermi-Hubbard model with entropy benchmarking
We developed a practical quantum advantage benchmarking framework that connects the accumulation of entropy in a quantum processing unit and the degradation of the solution to a target optimization problem. The benchmark is based on approximating from below the Gibbs states boundary in the energy-entropy space for the application of interest. We believe the proposed benchmarking technique creates a powerful bridge between hardware benchmarking and application benchmarking, while remaining hardw…

US hits $38 trillion in debt, after the fastest accumulation of $1 trillion outside of the pandemic (Fatima Hussein/Associated Press)
https://apnews.com/article/trump-treasury-debt-ceiling-bessent-09575f13ca95c2f1beb38234b2cbe85b
http://www.memeorandum.com/251022/p160#a251022p160

My latest essay, I will offiicially release it tomorrow morning, but in the meantime, here it is!
https://varnelis.net/works_and_projects/stochastic-histories/

Stochastic Histories - varnelis.net
stochastic histories /stəˈkæstɪk ˈhɪstəriz/ n. pl. [from Gk. stokhastikos “capable of guessing,” from stokhazesthai “to aim at, guess at” + L. historia “narrative, account”] 1. Fabricated historical narratives generated through iterative probabilistic sampling with artificial-intelligence systems, producing documentation that appears authentic through the accumulation of plausible details. 2. A mode of artistic practice that exploits ...

Earthquake modelling via Brownian motions on networks
Fausto Colantoni, Mirko D'Ovidio, Flavia Tavani
https://arxiv.org/abs/2509.21851 https://arxiv.or…

Earthquake modelling via Brownian motions on networks
We provide a general model for Brownian motions on metric graphs with interactions. In a general setting, for (sticky) Brownian propagations on edges, our model provides a characterization of lifetimes and holding times on vertices in terms of (jumping) Brownian accumulation of energy associated with that vertices. Propagation and accumulation are given by drifted Brownian motions subjected to non-local (also dynamic) boundary conditions. As the continuous (sticky) process approaches a vertex, …

Copula-Based Clustering of Financial Time Series via Evidence Accumulation
Andrea Mecchina, Roberta Pappad\`a, Nicola Torelli
https://arxiv.org/abs/2510.05960 https://

Copula-Based Clustering of Financial Time Series via Evidence Accumulation
Understanding the dependence structure of asset returns is fundamental in risk assessment and is particularly relevant in a portfolio diversification strategy. We propose a clustering approach where evidence accumulated in a multiplicity of classifications is achieved using classical hierarchical procedures and multiple copula-based dissimilarity measures. Assets that are grouped in the same cluster are such that their stochastic behavior is similar during risky scenarios, and riskaverse invest…

Cation accumulation drives the preferential partitioning of DNA in an aqueous two-phase system
Hiroki Sakuta, Yuki Akamine, Akari Kamo, Hao Gong, Norikazu Ichihashi, Arash Nikoubashman, Miho Yanagisawa
https://arxiv.org/abs/2509.24641

Cation accumulation drives the preferential partitioning of DNA in an aqueous two-phase system
Mixtures of polyethylene glycol (PEG) and dextran (Dex) represent a widely used class of aqueous two-phase systems (ATPS), with applications ranging from the purification of various biomolecules such as nucleic acids to the synthesis of protocells. A key feature underlying these applications is the selective accumulation of biomolecules within Dex-rich droplets in an aqueous PEG phase, but the physical origin of this partitioning remains unclear. Depletion interactions were long assumed to be t…

Was watching a talk by Sarah Wilson at TEDxSydney: "How to respond to a societal collapse"
Takeaway: If you're looking for an alternate word for "clusterfuck" (like if you're doing an RCA for US-EAST-1) I'm here to share that with you.
#ClusterFuck #Metacrisis

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Wenliang Li, Rui Yan, Xu Zhang, Li Chen, Hongji Zhu, Jing Zhao, Junjun Li, Mengru Li, Wei Cao, Zihang Jiang, Wei Wei, Kun Zhang, Shaohua Kevin Zhou
https://arxiv.org/abs/2509.20067

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Large language models (LLMs) have demonstrated notable potential in medical applications, yet they face substantial challenges in handling complex real-world clinical diagnoses using conventional prompting methods. Current prompt engineering and multi-agent approaches typically optimize isolated inferences, neglecting the accumulation of reusable clinical experience. To address this, this study proposes a novel Multi-Agent Clinical Diagnosis (MACD) framework, which allows LLMs to self-learn cli…

Impact of Evaporation Barriers on Solar-Captured Dark Matter Distributions and Evaporation Mass
Xuan Wen
https://arxiv.org/abs/2509.26192 https://arxiv.org…

Impact of Evaporation Barriers on Solar-Captured Dark Matter Distributions and Evaporation Mass
Dark matter (DM) particles traversing the Sun can lose energy through elastic scattering with solar nuclei and become gravitationally captured. For DM with masses below a few GeV, however, evaporation caused by collisions with hot nuclei efficiently ejects particles, preventing their long-term accumulation. This defines a minimum mass threshold, typically around a few GeV, below which the Sun cannot retain DM. In this work, we investigate how an additional evaporation barrier - arising either f…

Spin and Orbital Edelstein effect in gated monolayer transition metal dichalcogenides
Tapesh Gautam, S. Satpathy
https://arxiv.org/abs/2509.25634 https://a…

Spin and Orbital Edelstein effect in gated monolayer transition metal dichalcogenides
The Edelstein effect consists of the non-equilibrium accumulation of magnetization in response to an applied electric field in systems with broken inversion symmetry. While the spin Edelstein effect (SEE), originating from spin moments, is well established, its orbital counterpart, where magnetization arises from orbital moment, has only recently begun to attract attention. In this work, we investigate the orbital Edelstein effect (OEE) in gated monolayer transition-metal dichalcogenides (TMDs)…

Pack and Force Your Memory: Long-form and Consistent Video Generation
Xiaofei Wu, Guozhen Zhang, Zhiyong Xu, Yuan Zhou, Qinglin Lu, Xuming He
https://arxiv.org/abs/2510.01784 ht…

Pack and Force Your Memory: Long-form and Consistent Video Generation
Long-form video generation presents a dual challenge: models must capture long-range dependencies while preventing the error accumulation inherent in autoregressive decoding. To address these challenges, we make two contributions. First, for dynamic context modeling, we propose MemoryPack, a learnable context-retrieval mechanism that leverages both textual and image information as global guidance to jointly model short- and long-term dependencies, achieving minute-level temporal consistency. Th…

LLM Cache Bandit Revisited: Addressing Query Heterogeneity for Cost-Effective LLM Inference
Hantao Yang, Hong Xie, Defu Lian, Enhong Chen
https://arxiv.org/abs/2509.15515 https:…

LLM Cache Bandit Revisited: Addressing Query Heterogeneity for Cost-Effective LLM Inference
This paper revisits the LLM cache bandit problem, with a special focus on addressing the query heterogeneity for cost-effective LLM inference. Previous works often assume uniform query sizes. Heterogeneous query sizes introduce a combinatorial structure for cache selection, making the cache replacement process more computationally and statistically challenging. We treat optimal cache selection as a knapsack problem and employ an accumulation-based strategy to effectively balance computational o…

In-Context Learning can Perform Continual Learning Like Humans
Liuwang Kang, Fan Wang, Shaoshan Liu, Hung-Chyun Chou, Chuan Lin, Ning Ding
https://arxiv.org/abs/2509.22764 https…

In-Context Learning can Perform Continual Learning Like Humans
Large language models (LLMs) can adapt to new tasks via in-context learning (ICL) without parameter updates, making them powerful learning engines for fast adaptation. While extensive research has examined ICL as a few-shot learner, whether it can achieve long-term retention and cross-task knowledge accumulation when multitasks arrive sequentially remains underexplored. Motivated by human memory studies, we investigate the retention characteristics of ICL in multitask settings and extend it to …

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- JugglePAC: A Pipelined Accumulation Circuit
Ahmad Houraniah, H. Fatih Ugurdag, Furkan Aydin

CodeCureAgent: Automatic Classification and Repair of Static Analysis Warnings
Pascal Joos, Islem Bouzenia, Michael Pradel
https://arxiv.org/abs/2509.11787 https://

CodeCureAgent: Automatic Classification and Repair of Static Analysis Warnings
Static analysis tools are widely used to detect bugs, vulnerabilities, and code smells. Traditionally, developers must resolve these warnings manually. Because this process is tedious, developers sometimes ignore warnings, leading to an accumulation of warnings and a degradation of code quality. This paper presents CodeCureAgent, an approach that harnesses LLM-based agents to automatically analyze, classify, and repair static analysis warnings. Unlike previous work, our method does not follow a…

Multi-modal Liver Segmentation and Fibrosis Staging Using Real-world MRI Images
Yang Zhou, Kunhao Yuan, Ye Wei, Jishizhan Chen
https://arxiv.org/abs/2509.26061 https://

Multi-modal Liver Segmentation and Fibrosis Staging Using Real-world MRI Images
Liver fibrosis represents the accumulation of excessive extracellular matrix caused by sustained hepatic injury. It disrupts normal lobular architecture and function, increasing the chances of cirrhosis and liver failure. Precise staging of fibrosis for early diagnosis and intervention is often invasive, which carries risks and complications. To address this challenge, recent advances in artificial intelligence-based liver segmentation and fibrosis staging offer a non-invasive alternative. As a…

DRCP: Diffusion on Reinforced Cooperative Perception for Perceiving Beyond Limits
Lantao Li, Kang Yang, Rui Song, Chen Sun
https://arxiv.org/abs/2509.24903 https://

DRCP: Diffusion on Reinforced Cooperative Perception for Perceiving Beyond Limits
Cooperative perception enabled by Vehicle-to-Everything communication has shown great promise in enhancing situational awareness for autonomous vehicles and other mobile robotic platforms. Despite recent advances in perception backbones and multi-agent fusion, real-world deployments remain challenged by hard detection cases, exemplified by partial detections and noise accumulation which limit downstream detection accuracy. This work presents Diffusion on Reinforced Cooperative Perception (DRCP)…

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Wenliang Li, Rui Yan, Xu Zhang, Li Chen, Hongji Zhu, Jing Zhao, Junjun Li, Mengru Li, Wei Cao, Zihang Jiang, Wei Wei, Kun Zhang, Shaohua Kevin Zhou
https://arxiv.org/abs/2509.20067

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Large language models (LLMs) have demonstrated notable potential in medical applications, yet they face substantial challenges in handling complex real-world clinical diagnoses using conventional prompting methods. Current prompt engineering and multi-agent approaches typically optimize isolated inferences, neglecting the accumulation of reusable clinical experience. To address this, this study proposes a novel Multi-Agent Clinical Diagnosis (MACD) framework, which allows LLMs to self-learn cli…

RepCaM : Exploring Transparent Visual Prompt With Inference-Time Re-Parameterization for Neural Video Delivery
Rongyu Zhang, Xize Duan, Jiaming Liu, Li Du, Yuan Du, Dan Wang, Shanghang Zhang, Fangxin Wang
https://arxiv.org/abs/2509.14002

RepCaM++: Exploring Transparent Visual Prompt With Inference-Time Re-Parameterization for Neural Video Delivery
Recently, content-aware methods have been employed to reduce bandwidth and enhance the quality of Internet video delivery. These methods involve training distinct content-aware super-resolution (SR) models for each video chunk on the server, subsequently streaming the low-resolution (LR) video chunks with the SR models to the client. Prior research has incorporated additional partial parameters to customize the models for individual video chunks. However, this leads to parameter accumulation an…

Bistability and Noise-Induced Evasion in Tumor-Immune Dynamics with Antigen Accumulation and Immune Escape
Mengfan Tan, Shaoqing Chen, Chunjin Wei, Da Zhou
https://arxiv.org/abs/2509.11048

Bistability and Noise-Induced Evasion in Tumor-Immune Dynamics with Antigen Accumulation and Immune Escape
Tumor-immune interactions are shaped by both antigenic heterogeneity and stochastic perturbations in the tumor microenvironment, yet the mathematical mechanisms underlying immune phase transitions remain poorly understood. We propose a four-compartment dynamical model that incorporates antigen accumulation and immune escape mutations. Bifurcation analysis reveals bistability between immune surveillance and immune escape states, providing a mechanistic explanation for heterogeneous immune outcom…

Improving Virtual Contrast Enhancement using Longitudinal Data
Pierre Fayolle, Alexandre B\^one, No\"elie Debs, Pihlippe Robert, Pascal Bourdon, Remy Guillevin, David Helbert
https://arxiv.org/abs/2510.00418

Improving Virtual Contrast Enhancement using Longitudinal Data
Gadolinium-based contrast agents (GBCAs) are widely used in magnetic resonance imaging (MRI) to enhance lesion detection and characterisation, particularly in the field of neuro-oncology. Nevertheless, concerns regarding gadolinium retention and accumulation in brain and body tissues, most notably for diseases that require close monitoring and frequent GBCA injection, have led to the need for strategies to reduce dosage. In this study, a deep learning framework is proposed for the virtual contr…

Differential-Integral Neural Operator for Long-Term Turbulence Forecasting
Hao Wu, Yuan Gao, Fan Xu, Fan Zhang, Qingsong Wen, Kun Wang, Xiaomeng Huang, Xian Wu
https://arxiv.org/abs/2509.21196

Differential-Integral Neural Operator for Long-Term Turbulence Forecasting
Accurately forecasting the long-term evolution of turbulence represents a grand challenge in scientific computing and is crucial for applications ranging from climate modeling to aerospace engineering. Existing deep learning methods, particularly neural operators, often fail in long-term autoregressive predictions, suffering from catastrophic error accumulation and a loss of physical fidelity. This failure stems from their inability to simultaneously capture the distinct mathematical structures…

Multi-Agent Amodal Completion: Direct Synthesis with Fine-Grained Semantic Guidance
Hongxing Fan, Lipeng Wang, Haohua Chen, Zehuan Huang, Jiangtao Wu, Lu Sheng
https://arxiv.org/abs/2509.17757

Multi-Agent Amodal Completion: Direct Synthesis with Fine-Grained Semantic Guidance
Amodal completion, generating invisible parts of occluded objects, is vital for applications like image editing and AR. Prior methods face challenges with data needs, generalization, or error accumulation in progressive pipelines. We propose a Collaborative Multi-Agent Reasoning Framework based on upfront collaborative reasoning to overcome these issues. Our framework uses multiple agents to collaboratively analyze occlusion relationships and determine necessary boundary expansion, yielding a p…

RobotDancing: Residual-Action Reinforcement Learning Enables Robust Long-Horizon Humanoid Motion Tracking
Zhenguo Sun, Yibo Peng, Yuan Meng, Xukun Li, Bo-Sheng Huang, Zhenshan Bing, Xinlong Wang, Alois Knoll
https://arxiv.org/abs/2509.20717

RobotDancing: Residual-Action Reinforcement Learning Enables Robust Long-Horizon Humanoid Motion Tracking
Long-horizon, high-dynamic motion tracking on humanoids remains brittle because absolute joint commands cannot compensate model-plant mismatch, leading to error accumulation. We propose RobotDancing, a simple, scalable framework that predicts residual joint targets to explicitly correct dynamics discrepancies. The pipeline is end-to-end--training, sim-to-sim validation, and zero-shot sim-to-real--and uses a single-stage reinforcement learning (RL) setup with a unified observation, reward, and h…

Demonstration of a Logical Architecture Uniting Motion and In-Place Entanglement: Shor's Algorithm, Constant-Depth CNOT Ladder, and Many-Hypercube Code
Rich Rines, Benjamin Hall, Mariesa H. Teo, Joshua Viszlai, Daniel C. Cole, David Mason, Cameron Barker, Matt J. Bedalov, Matt Blakely, Tobias Bothwell, Caitlin Carnahan, Frederic T. Chong, Samuel Y. Eubanks, Brian Fields, Matthew Gillette, Palash Goiporia, Pranav Gokhale, Garrett T. Hickman, Marin Iliev, Eric B. Jones, Ryan A. Jones…

Demonstration of a Logical Architecture Uniting Motion and In-Place Entanglement: Shor's Algorithm, Constant-Depth CNOT Ladder, and Many-Hypercube Code
Logical qubits are considered an essential component for achieving utility-scale quantum computation. Multiple recent demonstrations of logical qubits on neutral atoms have relied on coherent qubit motion into entangling zones. However, this architecture requires motion prior to every entangling gate, incurring significant cost in wall clock runtime and motion-related error accumulation. We propose and experimentally realize an alternative architecture which unites qubit motion and in-place ent…

Why and when merging surface nanobubbles jump
Yixin Zhang, Xiangyu Zhang, Detlef Lohse
https://arxiv.org/abs/2509.22934 https://arxiv.org/pdf/2509.22934

Why and when merging surface nanobubbles jump
Gas bubble accumulation on substrates reduces the efficiency of many physicochemical processes, such as water electrolysis. For microbubbles, where buoyancy is negligible, coalescence-induced jumping driven by the release of surface energy provides an efficient pathway for their early detachment. At the nanoscale, however, gas compressibility breaks volume conservation during coalescence, suppressing surface energy release and seemingly disabling this detachment route. Using molecular dynamics …

Good Morning #Canada
I'm relaxing in front of a fireplace with some freshly brewed coffee and watching the Weather Network map animation loop endlessly showing the forecasted snow that will hit us in the next 24 hours. It's hypnotic and distracts you from thinking about the 25-30cm expected accumulation. If you love snow, Canada is the place to be. In fact, almost two-thirds (65%) of Canada's land mass has annual snow cover for more than six months of the year. I read that on the internet, so it's true. I'll be one of the 24% of Canadians who own a #SnowBlower throwing the white stuff everywhere, including back into my face. About half of Canadian households on the east coast own a Snow Blower versus 7% in British Columbia. Apparently, 51% of residents in Barrie use snow clearing machines, which is a statistic I should have paid attention to when we decided to move into this area.
#CanadaIsAwesome #Snowmageddon
https://www.statcan.gc.ca/o1/en/plus/2626-blowing-snow

The Growth of Dust in Galaxies in the First Billion Years with Applications to Blue Monsters
Desika Narayanan, Paul Torrey, Daniel Stark, John Chisholm, Steven Finkelstein, Alex Garcia, Jessica Kelley-Derzon, Federico Marinacci, Laura Sales, Ethan Savitch, Mark Vogelsberger, Dhruv Zimmerman
https://arxiv.org/abs/2509.18266

Decoding Plastic Toxicity: An Intelligent Framework for Conflict-Aware Relational Metapath Extraction from Scientific Abstracts
Sudeshna Jana, Manjira Sinha, Tirthankar Dasgupta
https://arxiv.org/abs/2509.11330

Decoding Plastic Toxicity: An Intelligent Framework for Conflict-Aware Relational Metapath Extraction from Scientific Abstracts
The widespread use of plastics and their persistence in the environment have led to the accumulation of micro- and nano-plastics across air, water, and soil, posing serious health risks including respiratory, gastrointestinal, and neurological disorders. We propose a novel framework that leverages large language models to extract relational metapaths, multi-hop semantic chains linking pollutant sources to health impacts, from scientific abstracts. Our system identifies and connects entities acr…

A geometric model of synthetic filtrations via context-dependent time
Takanori Adachi
https://arxiv.org/abs/2509.12919 https://arxiv.org/pdf/2509.12919

A geometric model of synthetic filtrations via context-dependent time
Classical filtrations in probability theory formalize the accumulation of information along a linear time axis: the past is unique and the present evolves into an uncertain future. In many contexts, however, information is neither linear nor uniquely determined by a single history. In this paper we propose a geometric model of synthetic filtrations, where the present may be formed by synthesizing multiple possible pasts. To achieve this, we introduce a new category Σ, an extension of the simpl…