Tootfinder

Efficient Learning-based Graph Simulation for Temporal Graphs
Sheng Xiang, Chenhao Xu, Dawei Cheng, Xiaoyang Wang, Ying Zhang
https://arxiv.org/abs/2510.05569 https://

Efficient Learning-based Graph Simulation for Temporal Graphs
Graph simulation has recently received a surge of attention in graph processing and analytics. In real-life applications, e.g. social science, biology, and chemistry, many graphs are composed of a series of evolving graphs (i.e., temporal graphs). While most of the existing graph generators focus on static graphs, the temporal information of the graphs is ignored. In this paper, we focus on simulating temporal graphs, which aim to reproduce the structural and temporal properties of the observed…

Hybrid quantum-classical analog simulation of two-dimensional Fermi-Hubbard models with neutral atoms
Sergi Juli\`a-Farr\'e, Antoine Michel, Christophe Domain, Joseph Mikael, Jacques-Charles Lafoucriere, Joseph Vovrosh, Ahmed Chahlaoui, Dorian Claveau, Guillaume Villaret, Julius de Hond, Lo\"ic Henriet, Antoine Browaeys, Thomas Ayral, Alexandre Dauphin

Hybrid quantum-classical analog simulation of two-dimensional Fermi-Hubbard models with neutral atoms
We experimentally study the two-dimensional Fermi-Hubbard model using a Rydberg-based quantum processing unit in the analog mode. Our approach avoids encoding directly the original fermions into qubits and instead relies on reformulating the original model onto a system of fermions coupled to spins and then decoupling them in a self-consistent manner. We then introduce the auxiliary spin solver: this hybrid quantum-classical algorithm handles a free-fermion problem, which can be solved efficien…

Simulation of Muon-induced Backgrounds for the Colorado Underground Research Institute (CURIE)
Dakota K. Keblbeck, Eric Mayotte, Uwe Greife, Kyle G. Leach, Wouter Van De Pontseele, Caitlyn Stone-Whitehead, Luke Wanner, Grace Wagner
https://arxiv.org/abs/2510.06150

Simulation of Muon-induced Backgrounds for the Colorado Underground Research Institute (CURIE)
We present a comprehensive Monte Carlo simulation of muon-induced backgrounds for the Colorado Underground Research Institute (CURIE), a shallow-underground facility with $\approx 415$~m.w.e. overburden. Using coupled \textsc{mute} and \textsc{geant4} frameworks, we characterize the production and transport of muon-induced secondaries through site-specific rock compositions and geometries, establishing a proof-of-concept for high-precision, end-to-end simulations. Our simulations employ angular…

Generalized Multi-agent Social Simulation Framework
Gang Li, Jie Lin, Yining Tang, Ziteng Wang, Yirui Huang, Junyu Zhang, Shuang Luo, Chao Wu, Yike Guo
https://arxiv.org/abs/2510.06225

Generalized Multi-agent Social Simulation Framework
Multi-agent social interaction has clearly benefited from Large Language Models. However, current simulation systems still face challenges such as difficulties in scaling to diverse scenarios and poor reusability due to a lack of modular design. To address these issues, we designed and developed a modular, object-oriented framework that organically integrates various base classes through a hierarchical structure, harvesting scalability and reusability. We inherited the framework to realize comm…

Bridging the Gap Between Methodological Research and Statistical Practice: Toward "Translational Simulation Research
Anne-Laure Boulesteix, Patrick Callahan, Luzia Hanssum, Vincent Gaertner, Eva Hoster
https://arxiv.org/abs/2510.05800

Bridging the Gap Between Methodological Research and Statistical Practice: Toward "Translational Simulation Research
Simulations are valuable tools for empirically evaluating the properties of statistical methods and are primarily employed in methodological research to draw general conclusions about methods. In addition, they can often be useful to applied statisticians, who may rely on published simulation results to select an appropriate statistical method for their application. However, on the one hand, applying published simulation results directly to practical settings is frequently challenging, as the s…

Limitations of Current Evaluation Practices for Conversational Recommender Systems and the Potential of User Simulation
Nolwenn Bernard, Krisztian Balog
https://arxiv.org/abs/2510.05624

Limitations of Current Evaluation Practices for Conversational Recommender Systems and the Potential of User Simulation
Research and development on conversational recommender systems (CRSs) critically depends on sound and reliable evaluation methodologies. However, the interactive nature of these systems poses significant challenges for automatic evaluation. This paper critically examines current evaluation practices and identifies two key limitations: the over-reliance on static test collections and the inadequacy of existing evaluation metrics. To substantiate this critique, we analyze real user interactions w…

Simulation-based inference via telescoping ratio estimation for trawl processes
Dan Leonte, Rapha\"el Huser, Almut E. D. Veraart
https://arxiv.org/abs/2510.04042 https://…

Simulation-based inference via telescoping ratio estimation for trawl processes
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussian tails, long memory, and even non-Markovian dynamics. While such models are often easy to simulate from, parameter estimation remains challenging. Simulation-based inference (SBI) offers a promising way forward, but existing methods typically require large training datasets or complex architectures and frequently yi…

Modeling ROI in Chronic Disease Management, A Simulation-Based Framework Integrating Patient Adherence and Policy Timing
Jinho Cha, Eunchan D. Cha, Emily Yoo, Hyoshin Song
https://arxiv.org/abs/2510.06379

Modeling ROI in Chronic Disease Management, A Simulation-Based Framework Integrating Patient Adherence and Policy Timing
Background: Chronic diseases impose a sustained burden on healthcare systems through progressive deterioration and long-term costs. Although adherence-enhancing interventions are widely promoted, their return on investment (ROI) remains uncertain, particularly under heterogeneous patient behavior and socioeconomic variation. Methods: We developed a simulation-based framework integrating disease progression, time-varying adherence, and policy timing. Cumulative healthcare costs were modeled over…

Simulation: Radioteleskope auf dem Mond könnten Rätsel der Dunklen Materie lösen
Nach dem Urknall hat sich die Dunkle Materie verklumpt, Spuren davon soll es geben. Weil sie nicht von der Erde aus nachweisbar sind, gibt es einen Vorschlag.

Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning
Xuemin Liu, Tom Hickling, Jonathan F. MacArt
https://arxiv.org/abs/2510.07106 https://

Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning
We train active neural-network flow controllers using a deep learning PDE augmentation method to optimize lift-to-drag ratios in turbulent airfoil flows at Reynolds number $5\times10^4$ and Mach number 0.4. Direct numerical simulation and large eddy simulation are employed to model compressible, unconfined flow over two- and three-dimensional semi-infinite NACA 0012 airfoils at angles of attack $α= 5^\circ$, $10^\circ$, and $15^\circ$. Control actions, implemented through a blowing/suction jet…

Accretion, Jets, and Recoil in Merging Supermassive Binary Black Holes
Maria Chiara de Simone (RIT), Manuela Campanelli (RIT), Lorenzo Ennoggi (RIT), Carlos O. Lousto (RIT), Yosef Zlochower (RIT)
https://arxiv.org/abs/2510.05883

Accretion, Jets, and Recoil in Merging Supermassive Binary Black Holes
We report the first 3D general relativistic magnetohydrodynamic (GRMHD) simulation that captures the full, self-consistent evolution from the late inspiral through merger and subsequent recoil of a supermassive binary black hole (SMBBH) with misaligned spins embedded in an equilibrated circumbinary disk (CBD). Our full numerical simulation follows the final 40 orbits of the inspiral and merger of the binary, following an initial phase of 165 orbits of CBD evolution toward equilibrium. We find t…

Difference in Neoclassical Edge Flows Between Strongly Negative and Positive Triangularities in the XGC Gyrokinetic Simulation
S. Ku, C. S. Chang, R. Hager, L. W. Schmitz, A. O. Nelson
https://arxiv.org/abs/2510.05287

Difference in Neoclassical Edge Flows Between Strongly Negative and Positive Triangularities in the XGC Gyrokinetic Simulation
The neoclassical baseline study of a strongly negative triangularity (NT) plasma and the corresponding positive triangularity plasma is performed using the edge-specialized, total-f gyrokinetic code XGC. A DIII-D-like plasma is used, based on the negative triangularity discharge of DIII-D \#193793. An artificial positive triangularity (PT) equilibrium has been constructed to compare the edge rotation physics at the same triangularity strength, but with opposite sign, while keeping the same elon…

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Big Thief:
🎵 Simulation Swarm
#BigThief
https://bigthief.bandcamp.com/track/simulation-swarm
https://open.spotify.com/track/2FwDApgXk91kXvqy2oB7dz

Adaptive Tool Generation with Models as Tools and Reinforcement Learning
Chenpeng Wang, Xiaojie Cheng, Chunye Wang, Linfeng Yang, Lei Zhang
https://arxiv.org/abs/2510.06825 http…

Adaptive Tool Generation with Models as Tools and Reinforcement Learning
Tool-augmented language models have demonstrated strong capabilities, but their reliance on live API access creates scalability and reliability challenges during training and deployment. We propose MTR, a simulation-first training framework for tool-augmented reasoning. Instead of relying on live APIs, MTR learns from complete ReAct traces with schema-validated, simulated observations. Our approach operates through a multi-agent architecture where a ToolMaker generates task-specific, OpenAI-com…

A standalone simulation program for Resistive Cylindrical Chamber (RCC)
M. Abbrescia, M. De Serio, S. Colafranceschi, B. Liberti, S. Meola, A. Paoloni, A. Pastore, D. Piccolo, A. Rocchi, G. Saviano, C. Vendittozzi
https://arxiv.org/abs/2510.05631

A standalone simulation program for Resistive Cylindrical Chamber (RCC)
In recent years, the Resistive Cylindrical Chamber (RCC) has been introduced as a novel gaseous detector, extending the well-established Resistive Plate Chambers (RPCs) to the case of cylindrical electrode geometry. Preliminary experimental studies have highlighted several promis- ing features of this configuration, motivating the need for further systematic investigations of its operation. In contrast, from the simulation perspective, detailed studies of the RCC have not been performed yet, de…

LegalSim: Multi-Agent Simulation of Legal Systems for Discovering Procedural Exploits
Sanket Badhe
https://arxiv.org/abs/2510.03405 https://arxiv.org/pdf/2…

LegalSim: Multi-Agent Simulation of Legal Systems for Discovering Procedural Exploits
We present LegalSim, a modular multi-agent simulation of adversarial legal proceedings that explores how AI systems can exploit procedural weaknesses in codified rules. Plaintiff and defendant agents choose from a constrained action space (for example, discovery requests, motions, meet-and-confer, sanctions) governed by a JSON rules engine, while a stochastic judge model with calibrated grant rates, cost allocations, and sanction tendencies resolves outcomes. We compare four policies: PPO, a co…

Crosslisted article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- MADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation
Mingjin Li, Yu Liu, Huayi Liu, Xiang Ye, Chao Jiang, Hongguang Zhang

Accelerating wave simulations with neural dispersion correctors
Felipe Rinc\'on, Andreas Fichtner, Mattia Aleardi, Andrea Tognarelli, Eusebio Stucchi
https://arxiv.org/abs/2510.06881

Accelerating wave simulations with neural dispersion correctors
We present a Fourier neural operator network, designed to correct dispersion errors in numerical wave simulations. The neural dispersion corrector enables the replacement of a computationally expensive high-accuracy simulation by a less expensive low-accuracy simulation. In contrast to neural network surrogates that fully replace a wave equation, the neural dispersion corrector has only a weak dependence on the distribution of model parameters, such as wave speeds. Consequently, the network can…

A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
Shengjiao Ji, Yujin Zhang, Zihan Zou, Bin Jiang, Jun Jiang, Yi Luo, Wei Hu
https://arxiv.org/abs/2510.04227

A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
Accurate and efficient simulation of infrared (IR) and Raman spectra is essential for molecular identification and structural analysis. Traditional quantum chemistry methods based on the harmonic approximation neglect anharmonicity and nuclear quantum effects, while ab initio molecular dynamics (AIMD) remains computationally expensive. Here, we integrate our deep equivariant tensor attention network (DetaNet) with a velocity-Verlet integrator to enable fast and accurate machine learning molecul…

Modeling Terahertz Propagation via Frequency-Domain Physics-Informed Neural Networks
Pengfei Zhu, Hai Zhang, Stefano Sfarra, Elena Pivar\v{c}iov\'a, Cunlin Zhang, Xavier Maldague
https://arxiv.org/abs/2510.04889

Modeling Terahertz Propagation via Frequency-Domain Physics-Informed Neural Networks
Terahertz time-domain spectroscopy (THz-TDS) provides a non-invasive and label-free method for probing the internal structure and electromagnetic response of materials. Numerical simulation of THz-TDS can help understanding wave-matter interactions, guiding experimental design, and interpreting complex measurement data. However, existing simulation techniques face challenges in accurately modeling THz wave propagation with low computational cost. Additionally, conventional simulation solvers of…

Utility-Scale Quantum State Preparation: Classical Training using Pauli Path Simulation
Cheng-Ju Lin, Hrant Gharibyan, Vincent P. Su
https://arxiv.org/abs/2510.02428 https://

Utility-Scale Quantum State Preparation: Classical Training using Pauli Path Simulation
We use Pauli Path simulation to variationally obtain parametrized circuits for preparing ground states of various quantum many-body Hamiltonians. These include the quantum Ising model in one dimension, in two dimensions on square and heavy-hex lattices, and the Kitaev honeycomb model, all at system sizes of one hundred qubits or more, beyond the reach of exact state-vector simulation, thereby reaching utility scale. We benchmark the Pauli Path simulation results against exact ground-state energ…

Selection Bias in Hybrid Randomized Controlled Trials using External Controls: A Simulation Study
Han Chang Chiam, Franz K\"onig, Martin Posch
https://arxiv.org/abs/2510.04829

Selection Bias in Hybrid Randomized Controlled Trials using External Controls: A Simulation Study
Hybrid randomized controlled trials (hybrid RCTs) integrate external control data, such as historical or concurrent data, with data from randomized trials. While numerous frequentist and Bayesian methods, such as the test-then-pool and Meta-Analytic-Predictive prior, have been developed to account for potential disagreement between the external control and randomized data, they cannot ensure strict type I error rate control. However, these methods can reduce biases stemming from systematic diff…

Field-Theoretic Simulation of Dean-Kawasaki Dynamics for Interacting Particles
Jaehyeok Jin, Chen Liu, David R. Reichman
https://arxiv.org/abs/2510.05042 https://

Field-Theoretic Simulation of Dean-Kawasaki Dynamics for Interacting Particles
The formulation of a fluctuating hydrodynamic theory for interacting particles is a crucial step in the theoretical description of liquids. The microscopic mappings proposed decades ago by Dean and Kawasaki have played a central role in the analytical treatment of such problems. However, the singular mathematical nature of the density distributions used in these derivations raises concerns about the validity and practical utility of the resulting stochastic partial differential equations, parti…

Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning
Yilun Hao, Yongchao Chen, Chuchu Fan, Yang Zhang
https://arxiv.org/abs/2510.03182 https://

Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning
Vision Language Models (VLMs) show strong potential for visual planning but struggle with precise spatial and long-horizon reasoning. In contrast, Planning Domain Definition Language (PDDL) planners excel at long-horizon formal planning, but cannot interpret visual inputs. Recent works combine these complementary advantages by enabling VLMs to turn visual planning problems into PDDL files for formal planning. However, while VLMs can generate PDDL problem files satisfactorily, they struggle to a…

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
- Probabilistic Simulation of Aircraft Descent via a Hybrid Physics-Informed Machine Learning Approach
Amy Hodgkin, Nick Pepper, Marc Thomas

The simulation chain for the Terzina Cherenkov telescope on board the NUSES space mission
M. Abdullahi, R. Aloisio, F. Arneodo, S. Ashurov, U. Atalay, F. C. T. Barbato, R. Battiston, M. Bertaina, E. Bissaldi, D. Boncioli, L. Burmistrov, F. Cadoux, I. Cagnoli, E. Casilli, D. Cortis, A. Cummings, M. D'Arco, S. Davarpanah, I. De Mitri, G. De Robertis, A. Di Giovanni, A. Di Salvo, L. Di Venere, J. Eser, Y. Favre, S. Fogliacco, G. Fontanella, P. Fusco, S. Garbolino, F. Gargano, M. Gilib…

The simulation chain for the Terzina Cherenkov telescope on board the NUSES space mission
The Terzina telescope is designed to detect ultra-high energy cosmic rays (UHECRs) and Earth-skimming neutrinos from a 550 km low-Earth orbit (LEO) by observing Cherenkov light emitted by Extensive Air Showers (EAS) in the Earth's atmosphere pointing towards the telescope and in the field of view. In this contribution, a simulation chain for the Terzina telescope on board the NUSES mission will be presented. The chain encompasses all stages of the detection process, from event generation and EA…

Consciousness As Entropy Reduction (Short Version)
Yifeng Chen, J. W. Sanders
https://arxiv.org/abs/2510.06297 https://arxiv.org/pdf/2510.06297

Consciousness As Entropy Reduction (Short Version)
A model of consciousness is proposed which, having a logical basis, lends itself to simulation using a simple mathematical model called Consciousness as Entropy Reduction (CER). The approach has been inspired by previous models such as GWT, IIT and an earlier less mainstream model called "Feature Map" in Psychology. CER considers the contents of consciousness and subconsciousness as \textit{scenarios}: a vector of patterns (or features) on various "channels" (or feature locations). In CER, a fe…

Optimal Real-time Communication in 6G Ultra-Massive V2X Mobile Networks
He Huang, Zilong Liu, Zeping Sui, Wei Huang, Md. Noor-A-Rahim, Haishi Wang, Zhiheng Hu
https://arxiv.org/abs/2510.06937

Optimal Real-time Communication in 6G Ultra-Massive V2X Mobile Networks
This paper introduces a novel cooperative vehicular communication algorithm tailored for future 6G ultra-massive vehicle-to-everything (V2X) networks leveraging integrated space-air-ground communication systems. Specifically, we address the challenge of real-time information exchange among rapidly moving vehicles. We demonstrate the existence of an upper bound on channel capacity given a fixed number of relays, and propose a low-complexity relay selection heuristic algorithm. Simulation results…

Machine Learning Interatomic Potentials Enable Molecular Dynamics Simulations of Doped MoS2
Abrar Faiyad, Ashlie Martini
https://arxiv.org/abs/2510.05339 https://

Machine Learning Interatomic Potentials Enable Molecular Dynamics Simulations of Doped MoS2
We present the first computational framework for molecular dynamics simulation of MoS2 doped with 25 elements spanning metals, non-metals, and transition metals using Meta's Universal Model for Atoms machine learning interatomic potential (MLIP). Benchmarking against density functional theory calculations demonstrates the accuracy of the MLIP for simulating doped-MoS2 systems and highlights opportunities for improvement. Using the MLIP, we perform heating-cooling simulations of doped-MoS2 super…

A comprehensive look into the accuracy of SpEC binary black hole waveforms
Taylor Knapp, Katerina Chatziioannou, Keefe Mitman, Mark A. Scheel, Michael Boyle, Lawrence E. Kidder, Harald Pfeiffer
https://arxiv.org/abs/2510.06393

A comprehensive look into the accuracy of SpEC binary black hole waveforms
Numerical relativity simulations provide a full description of the dynamics of binary systems, including gravitational radiation. The waveforms produced by these simulations have a number of applications in gravitational-wave detection and inference. In this work, we revisit the accuracy of the waveforms produced by the Spectral Einstein Code. Motivated by the wide range of waveform applications, we propose and explore three accuracy metrics between simulation resolutions: (i) the generalized f…

Radiation magnetohydrodynamics modeling of an impulsively driven chromospheric jet in the solar atmosphere
J. J. Gonz\'alez-Avil\'es
https://arxiv.org/abs/2510.06482 htt…

Radiation magnetohydrodynamics modeling of an impulsively driven chromospheric jet in the solar atmosphere
In this paper, we present a numerical simulation of an impulsively driven chromospheric jet in the solar atmosphere using the non-ideal magnetohydrodynamic (MHD) equations coupled with frequency- and angle-averaged radiation transport equations. These include the dynamics of the radiation energy density and radiation flux. The jet is initiated by a localized Gaussian pulse applied to the vertical velocity component in the upper chromosphere (y = 1.75 Mm), producing a collimated plasma structure…

Short-Pulse High-Power THz Generation Using Optical Klystron FELs: Simulation Results
Najmeh Mirian
https://arxiv.org/abs/2510.05842 https://arxiv.org/pdf/…

Short-Pulse High-Power THz Generation Using Optical Klystron FELs: Simulation Results
We investigate the feasibility of extending the optical klystron (OK) concept into the terahertz (THz) regime, where strong radiation slippage and diffraction fundamentally challenge efficient free- electron laser (FEL) operation. Numerical simulations were carried out for resonant wavelengths of 10, 30, and 100 μm using parameters relevant to the planned DALI facility. The results show that while long wavelengths exhibit rapid energy growth, they suffer from significant temporal broadening du…

M&SCheck: Towards a Checklist to Support Software Engineering Newcomers to the Modeling and Simulation Area
Luiza Martins de Freitas Cintra, Philipp Zech, Mohamad Kassab, Eliomar Ara\'ujo Lima, Sofia Larissa da Costa Paiva, Valdemar Vicente Graciano Neto
https://arxiv.org/abs/2509.25625

M&SCheck: Towards a Checklist to Support Software Engineering Newcomers to the Modeling and Simulation Area
The advent of increasingly complex and dynamic ecosystems, such as digital twins (DT), smart cities and Industry 4.0 and 5.0, has made evident the need to include modeling and simulation (M&S) in the software development life cycle. Such disruptive systems include simulation models in their own architecture (such as DT) or require the use of simulation models to represent the high degree of movement and the multiplicity of interactions that occur between the involved systems. However, when soft…

DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning
Ke Guo, Haochen Liu, Xiaojun Wu, Chen Lv
https://arxiv.org/abs/2510.06913

DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning
Realistic traffic simulation is critical for the development of autonomous driving systems and urban mobility planning, yet existing imitation learning approaches often fail to model realistic traffic behaviors. Behavior cloning suffers from covariate shift, while Generative Adversarial Imitation Learning (GAIL) is notoriously unstable in multi-agent settings. We identify a key source of this instability: irrelevant interaction misguidance, where a discriminator penalizes an ego vehicle's reali…

🇧🇪 Belgian TSO Elia has published a dedicated page on EV fleet charging as part of their flexibility simulation tool. How much could fleet users save by using smart charging for company cars at workplaces and drivers' homes?
https://www.wattshappening.be/case-studies/electri…

Comment on "Physical significance of artificial numerical noise in direct numerical simulation of turbulence"
Ryan M. McMullen, Michael A. Gallis, Ishan Srivastava, Andrew J. Nonaka, John B. Bell, Alejandro L. Garcia
https://arxiv.org/abs/2510.04828

Comment on "Physical significance of artificial numerical noise in direct numerical simulation of turbulence"
Recently, Liao and Qin [J. Fluid Mech. 1008, R2 (2025)] claimed that numerical noise in direct numerical simulation of turbulence using the deterministic Navier-Stokes equations is "approximately equivalent" to the physical noise arising from random molecular motion (thermal fluctuations). We show here that it this claim not supported by their results and that it contradicts other results in the literature. Furthermore, we demonstrate that the numerical implementation of thermal fluctuations in…

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment
Sairam Sri Vatsavai, Raees Khan, Kuan-Chieh Hsu, Ozgur O. Kilic, Paul Nilsson, Tatiana Korchuganova, David K. Park, Sankha Dutta, Yihui Ren, Joseph Boudreau, Tasnuva Chowdhury, Shengyu Feng, Jaehyung Kim, Scott Klasky, Tadashi Maeno, Verena Ingrid Martinez, Norbert Podhorszki, Fr\'ed\'eric Suter, Wei Yang, Yiming Yang, Shinjae Yoo, Alexei Klimentov, Adolfy Hoisie

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment
Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distribu…

The Milky Way - Large Magellanic Cloud Interaction with Simulation Based Inference
Richard A. N. Brooks, Jason L. Sanders, Vedant Chandra, Nicol\'as Garavito-Camargo, Adam M. Dillamore, Adrian M. Price-Whelan, Yuan-Sen Ting
https://arxiv.org/abs/2510.04735

The Milky Way - Large Magellanic Cloud Interaction with Simulation Based Inference
The infall of the Large Magellanic Cloud (LMC) into the Milky Way (MW) has displaced the MW's centre of mass, manifesting as an observed reflex motion in the velocities of outer halo stars. We use a Simulation Based Inference framework to constrain properties of the MW, LMC and the induced reflex motion using the dynamics of outer MW halo stars. Specifically, we use the mean radial and tangential velocities of outer halo stars calculated in a set of distance and on-sky bins. We train neural net…

An Open-Access Web Tool for Light Curve Simulation and Analysis of Small Solar System Objects
J. L. Rizos, J. L. Ortiz, P. J. Gutierrez, I. M. Navajas, L. M. Lara
https://arxiv.org/abs/2510.03192

An Open-Access Web Tool for Light Curve Simulation and Analysis of Small Solar System Objects
We present a web-based application designed to simulate rotational light curves of small airless Solar System bodies under user-defined geometrical and physical conditions. The tool integrates both physical and empirical photometric models and enables users to input custom shape models, surface properties, and viewing geometries. A dedicated module also computes projected silhouettes at the epoch of stellar occultations, allowing direct comparison with observed chords. The application, develope…

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/2]:
- SCART: Simulation of Cyber Attacks for Real-Time
Eliron Rahimi, Kfir Girstein, Roman Malits, Avi Mendelson
…

Mathematical Proof Debunks the Idea That the Universe Is a Computer Simulation - Slashdot
https://science.slashdot.org/story/25/10/30/2232258/mathematical-proof-debunks-the-idea-that-the-universe-is-a-computer-simulation

NegotiationGym: Self-Optimizing Agents in a Multi-Agent Social Simulation Environment
Shashank Mangla, Chris Hokamp, Jack Boylan, Demian Gholipour Ghalandari, Yuuv Jauhari, Lauren Cassidy, Oisin Duffy
https://arxiv.org/abs/2510.04368

NegotiationGym: Self-Optimizing Agents in a Multi-Agent Social Simulation Environment
We design and implement NegotiationGym, an API and user interface for configuring and running multi-agent social simulations focused upon negotiation and cooperation. The NegotiationGym codebase offers a user-friendly, configuration-driven API that enables easy design and customization of simulation scenarios. Agent-level utility functions encode optimization criteria for each agent, and agents can self-optimize by conducting multiple interaction rounds with other agents, observing outcomes, an…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Exploring the Potential of Conversational AI Support for Agent-Based Social Simulation Model Design
Peer-Olaf Siebers

Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation
Akshay Govind Srinivasan, Vikas Dwivedi, Balaji Srinivasan
https://arxiv.org/abs/2510.04490

Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation
Partial differential equation (PDE) solvers are fundamental to engineering simulation. Classical mesh-based approaches (finite difference/volume/element) are fast and accurate on high-quality meshes but struggle with higher-order operators and complex, hard-to-mesh geometries. Recently developed physics-informed neural networks (PINNs) and their variants are mesh-free and flexible, yet compute-intensive and often less accurate. This paper systematically benchmarks RBF-PIELM, a rapid PINN varian…

Convex Pollution Control of Wastewater Treatment Systems
Joshua Taylor
https://arxiv.org/abs/2510.03918 https://arxiv.org/pdf/2510.03918

Convex Pollution Control of Wastewater Treatment Systems
We design a model-predictive controller for managing the actuators in sewer networks. It minimizes flooding and combined-sewer overflow during rain and pollution at other times. To make the problem tractable, we use a convex relaxation of the microbial growth kinetics and a physically motivated linearization of the mass flow bilinearities. With these approximations, the trajectory optimization in each control period is a second-order cone program. In simulation, the controller releases roughly …

One-Loop Effects in the Neutrino Matter Potential and Implications for Non-Standard Interactions
Jihong Huang, Tommy Ohlsson, Sampsa Vihonen, Shun Zhou
https://arxiv.org/abs/2510.04841

One-Loop Effects in the Neutrino Matter Potential and Implications for Non-Standard Interactions
In this work, we emphasize that it is necessary to take into account one-loop corrections of $2.0\%$ to the neutrino matter potential in the precision measurements of neutrino oscillation parameters and in the experimental searches for new physics beyond the Standard Model. With the numerical simulation of the DUNE experiment, we study how radiative corrections to the matter potential affect neutrino oscillation probabilities, and thus, the event rates in the presence of neutrino non-standard i…

ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
Luke Thompson, Davy Guan, Dai Shi, Slade Matthews, Junbin Gao, Andi Han
https://arxiv.org/abs/2510.05482 http…

ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
Molecular dynamics (MD) simulations underpin modern computational drug dis- covery, materials science, and biochemistry. Recent machine learning models provide high-fidelity MD predictions without the need to repeatedly solve quantum mechanical forces, enabling significant speedups over conventional pipelines. Yet many such methods typically enforce strict equivariance and rely on sequential rollouts, thus limiting their flexibility and simulation efficiency. They are also com- monly single-tas…

Ein massiver Rückgang wilder #Bestäuberinsekten könnte Europa laut einer Simulation bis 2030 wirtschaftlich rund 24 Milliarden Euro kosten.
Besonders betroffen wären Regionen mit hoher #landwirtschaftlicher Abhängigkeit von

Europa ohne Wildbestäuber: Simulation zeigt die teuren Folgen des Insektensterbens
Ein hypothetisches Verschwinden der Wildbestäuber im Jahr 2030 würde nicht nur Ernteausfälle und steigende Lebensmittelpreise nach sich ziehen, sondern auch die Ernährungssicherheit und den wirtschaftlichen Wohlstand weltweit gefährden. Zu diesem Schluss kommt eine Simulation der Universität Hohenheim: Allein in Europa würde im Jahr 2030 der gesamtwirtschaftliche Schaden rund 24 Milliarden Euro betragen. Der weltweite Handel könnte die Ausfälle nur teilweise ausgleichen. Die Ergebnisse…

Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data
Tianyu Li, Yihan Li, Zizhe Zhang, Nadia Figueroa
https://arxiv.org/abs/2510.02738

Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data
While visuomotor policy has made advancements in recent years, contact-rich tasks still remain a challenge. Robotic manipulation tasks that require continuous contact demand explicit handling of compliance and force. However, most visuomotor policies ignore compliance, overlooking the importance of physical interaction with the real world, often leading to excessive contact forces or fragile behavior under uncertainty. Introducing force information into vision-based imitation learning could hel…

Entanglement dynamics and performance of two-qubit gates for superconducting qubits under non-Markovian effects
Kiyoto Nakamura, Joachim Ankerhold
https://arxiv.org/abs/2510.05872

Entanglement dynamics and performance of two-qubit gates for superconducting qubits under non-Markovian effects
Within a numerically exact simulation technique, the dissipative dynamics of a two-qubit architecture is considered in which each qubit couples to its individual noise source (reservoir). The goal is to reveal the role of subtle qubit-reservoir correlations including non-Markovian processes as a prerequisite to guide further improvements of quantum computing devices. This paper addresses the following three topics. First, we examine the validity of the rotating wave approximation imposed previo…

A Particle-in-Cell Simulation Framework for Thomson Scattering Analysis in Inertial Confinement Fusion
Ziang Zhu, Yifan Liu, Jun Li, Han Wen, Shihui Cao, Yin Shi, Qing Jia, Chaoxin Chen, Yaoyuan Liu, Hang Zhao, Tao Gong, Zhichao Li, Dong Yang, Jian Zheng
https://arxiv.org/abs/2510.04298

A Particle-in-Cell Simulation Framework for Thomson Scattering Analysis in Inertial Confinement Fusion
In inertial confinement fusion (ICF), Thomson scattering (TS) is a widely used diagnostic technique for probing plasma conditions. We present a first-principles numerical approach to obtaining scattered light signals of ion acoustic features with high resolution in angle and frequency space using particle-in-cell simulations under typical ICF conditions. Our method demonstrates good agreement with existing theories for thermal collective TS. In the super-thermal collective regime, the results a…

Vinci, which uses AI simulations to accelerate chip and other hardware design, raised a $36M Series A led by Xora Innovation, taking its total funding to $46M (Max A. Cherney/Reuters)
https://www.reuters.com/business/software-

„News Tower“ angespielt: So frisch, dass man die Tinte riechen kann
Werft die Druckmaschinen an! Sparrow Night liefert mit der Zeitungs-Sim „News Tower“ eines der originellsten und besten Management-Spiele des Jahres ab.

Digital Twins for Intelligent Intersections: A Literature Review
Alben Rome Bagabaldo, J\"urgen Hackl
https://arxiv.org/abs/2510.05374 https://arxiv.o…

Digital Twins for Intelligent Intersections: A Literature Review
Intelligent intersections play a pivotal role in urban mobility, demanding innovative solutions such as digital twins to enhance safety and efficiency. This literature review investigates the integration and application of digital twins for intelligent intersections, a critical area within smart urban traffic systems. The review systematically categorizes existing research into five key thematic areas: (i) Digital Twin Architectures and Frameworks; (ii) Data Processing and Simulation Techniques…

(PhD thesis, 2024) Prototyping phosphene vision: Simulation-based optimization of visual neuroprosthetics using deep learning #BCI

Inferring the dark matter distribution of massive galaxy clusters from deep optical observations: insights from the TNG300 simulation
Aditya Manuwal (Universidad Nacional Aut\'onoma de M\'exico, Instituto de Astronom\'ia, A.P. 70-264, 04510 CDMX, M\'exico), Vladimir Avila-Reese (Universidad Nacional Aut\'onoma de M\'exico, Instituto de Astronom\'ia, A.P. 70-264, 04510 CDMX, M\'exico), Daniel Montenegro-Taborda (Instituto de Radioastronom\'ia y Astrof…

Inferring the dark matter distribution of massive galaxy clusters from deep optical observations: insights from the TNG300 simulation
Extragalactic stars within galaxy clusters contribute to the intracluster light (ICL), which is thought to be a promising tracer of the underlying dark matter (DM) distribution. In this study, we employ the TNG300 simulation to investigate the prospect of recovering the dark matter distribution of galaxy clusters from deep, wide-field optical images. For this, we generate mock observations of 40 massive clusters ($M_{200}\gtrsim 10^{14.5}\,{\rm M}_\odot$) at $z=0.06$ for the $g'$ band of the We…

The Thirteenth Floor (1999) was a great concept but the execution (the acting and dialogue) weren't the greatest - and this is coming from me, who watches and doesn't mind a lot of B movies. This one could really do with a modern remake. Simulation etc type stuff. I can just imagine this remade now, but so much better 😂
https://boxd.it/294Y<…

The Thirteenth Floor (1999)
In Los Angeles, a wealthy man, known as Mr. Fuller, discovers a shocking secret about the world he lives in. Fearing for his life, he leaves a desperate message for a friend of his in the most unexpected place.

Consequences of Undecidability in Physics on the #TheoryOfEverything: #universe is a #ComputerSiimulation: https://news.ok.ubc.ca/2025/10/30/ubco-study-debunks-the-idea-that-the-universe-is-a-computer-simulation/ - new study uses logic and physics to definitively answer one of science's biggest questions.

Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
Michael D. Atkinson, Michael D. White, Adam J. Plowman, Pratheek Shanthraj
https://arxiv.org/abs/2510.06904

Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
The development of next-generation structural materials for harsh environments requires rapid assessment of mechanical performance and its dependence on microstructure. While full-field crystal plasticity (CP) models provide detailed insights, the high computational cost limits their use with uncertainty quantification workflows and in component-scale simulation. Surrogate models based on recurrent neural networks (RNNs) have shown promise in reproducing history-dependent mechanical behaviour b…

Data-driven linear solver selection and performance tuning for multiphysics simulations in porous media
Yury Zabegaev, Inga Berre, Eirik Keilegavlen
https://arxiv.org/abs/2510.04920

Data-driven linear solver selection and performance tuning for multiphysics simulations in porous media
Modeling multiphysics processes in porous media requires preconditioned iterative linear solvers to enable efficient simulations at industry-relevant scales. These solvers are typically composed of sub-algorithms that target individual physical processes. Various options are available for each algorithm, with the corresponding ranges of numerical parameters. The choices of sub-algorithms and their parameters significantly affects simulation performance and robustness. Optimizing these choices f…

For #TextureTuesday some more WIP snapshots of STRATA, a generative system I've been on/off working on since 2014 (in Clojure/TypeScript/Zig, originally for the cover design of HOLO magazine), loosely based on 1950s research/experiments by Barricelli, somewhat related to cellular automata and extended to use a different and much larger set of "reproduction/collision rules" f…

Crosslisted article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Field-Theoretic Simulation of Dean-Kawasaki Dynamics for Interacting Particles
Jaehyeok Jin, Chen Liu, David R. Reichman

Universal initial state preparation for first quantized quantum simulations
Jack S. Baker, Gaurav Saxena, Thi Ha Kyaw
https://arxiv.org/abs/2510.07278 https://

Universal initial state preparation for first quantized quantum simulations
Preparing symmetry-adapted initial states is a principal bottleneck in first-quantized quantum simulation. We present a universal approach that efficiently maps any polynomial-size superposition of occupation-number configurations to the first-quantized representation on a digital quantum computer. The method exploits the Jordan--Schwinger Lie algebra homomorphism, which identifies number-conserving second-quantized operators with their first-quantized action and induces an equivariant bijectio…

Wind Farm Dynamics over a Diurnal Cycle: Analysis of a Comprehensive Large Eddy Simulation, Web-Services Accessible Dataset
Shuolin Xiao, Xiaowei Zhu, Ghanesh Narasimhan, Dennice F Gayme, Charles Meneveau
https://arxiv.org/abs/2510.05005

Wind Farm Dynamics over a Diurnal Cycle: Analysis of a Comprehensive Large Eddy Simulation, Web-Services Accessible Dataset
The atmospheric boundary layer undergoes significant changes throughout a diurnal cycle, affecting wind turbine performance and wakes in wind farms. Wind farm Large Eddy Simulations (LES) under such conditions provide rich datasets to study the underlying dynamics and identify important trends. Here, we describe a comprehensive open dataset generated using LES of an 8-turbine wind farm consisting of four rows of two turbines. To avoid specifying either prescribed surface temperature or heat flu…

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
https://arxiv.org/abs/2510.07006

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
This study develops and analyzes an optimization model of smart contract adoption under bounded risk, linking structural theory with simulation and real-world validation. We examine how adoption intensity alpha is structurally pinned at a boundary solution, invariant to variance and heterogeneity, while profitability and service outcomes are variance-fragile, eroding under volatility and heavy-tailed demand. A sharp threshold in the fixed cost parameter A3 triggers discontinuous adoption collap…

Curiosity-Driven Co-Development of Action and Language in Robots Through Self-Exploration
Theodore Jerome Tinker, Kenji Doya, Jun Tani
https://arxiv.org/abs/2510.05013 https://

Curiosity-Driven Co-Development of Action and Language in Robots Through Self-Exploration
Human infants acquire language and action co-developmentally, achieving remarkable generalization capabilities from only a minimal number of learning examples. In contrast, recent large language models require exposure to billions of training tokens to achieve such generalization. What mechanisms underlie such efficient developmental learning in humans? This study addresses this question through simulation experiments in which robots learn to perform various actions corresponding to imperative …

Prototyping Digital Social Spaces through Metaphor-Driven Design: Translating Spatial Concepts into an Interactive Social Simulation
Yoojin Hong, Martina Di Paola, Braahmi Padmakumar, Hwi Joon Lee, Mahnoor Shafiq, Joseph Seering
https://arxiv.org/abs/2510.02759

Prototyping Digital Social Spaces through Metaphor-Driven Design: Translating Spatial Concepts into an Interactive Social Simulation
Social media platforms are central to communication, yet their designs remain narrowly focused on engagement and scale. While researchers have proposed alternative visions for online spaces, these ideas are difficult to prototype within platform constraints. In this paper, we introduce a metaphor-driven system to help users imagine and explore new social media environments. The system translates users' metaphors into structured sets of platform features and generates interactive simulations pop…

TeraAgent: A Distributed Agent-Based Simulation Engine for Simulating Half a Trillion Agents
Lukas Breitwieser, Ahmad Hesam, Abdullah Giray Ya\u{g}l{\i}k\c{c}{\i}, Mohammad Sadrosadati, Fons Rademakers, Onur Mutlu
https://arxiv.org/abs/2509.24063

TeraAgent: A Distributed Agent-Based Simulation Engine for Simulating Half a Trillion Agents
Agent-based simulation is an indispensable paradigm for studying complex systems. These systems can comprise billions of agents, requiring the computing resources of multiple servers to simulate. Unfortunately, the state-of-the-art platform, BioDynaMo, does not scale out across servers due to its shared-memory-based implementation. To overcome this key limitation, we introduce TeraAgent, a distributed agent-based simulation engine. A critical challenge in distributed execution is the exchange…

Investigating the Lower Hybrid Drift Instability in Reconnecting Current Sheets Using a Hybrid Kinetic Model (ssV Code)
S. Thatikonda, F. N. De Oliveira-Lopes, A. Mustonen, K. Pommois, D. Told, F. Jenko
https://arxiv.org/abs/2510.05912

Investigating the Lower Hybrid Drift Instability in Reconnecting Current Sheets Using a Hybrid Kinetic Model (ssV Code)
We investigate the nonlinear evolution of the lower hybrid drift instability (LHDI) in reconnecting current sheets using a hybrid kinetic simulation model implemented in the Super Simple Vlasov (ssV) code. The model treats ions kinetically and electrons with a drift-kinetic approximation, solving self-consistent coupled electrostatic and electromagnetic fields. A parametric study explores the effects of mass ratio, temperature ratio, plasma beta, and sheet thickness. In electrostatic cases, LHD…

Crosslisted article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- MADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation
Mingjin Li, Yu Liu, Huayi Liu, Xiang Ye, Chao Jiang, Hongguang Zhang

DRAGON-III simulation: modelling million-body globular and nuclear star clusters
Kai Wu, Philip Cho, Rainer Spurzem, Long Wang, Francesco Flammini Dotti, Vahid Amiri
https://arxiv.org/abs/2510.03933

DRAGON-III simulation: modelling million-body globular and nuclear star clusters
As a continuation of DRAGON-II, we present the DRAGON-III project, which focuses on the simulations of million-body globular clusters and nuclear clusters over 10 Gyr. We report on its preliminary results on globular clusters. The first 100 Myr of the simulations have produced 41 pulsars, 191 X-ray binaries, 17 gravitational wave sources, and one black hole-black hole merger due to the loss of orbital energy in the form of gravitational wave emission. The inclusion of initial soft binaries brin…

The PESCAD Method for Autonomous Systems: An Application to Photoionization at Near-optical Wavelengths
Selst{\o} S{\o}lve, Bendik Steinsv{\aa}g Dalen
https://arxiv.org/abs/2510.05776

The PESCAD Method for Autonomous Systems: An Application to Photoionization at Near-optical Wavelengths
In a recent publication, Dalen, and Selstø, Phys. Rev. A {\bf 111}, 033116 (2025), it was demonstrated how converged photo electron spectra could be determined using a complex absorbing potential on a truncated numerical domain considerably smaller than the extension of the dynamical wave function. That approach required simulation until virtually all unbound parts of the wave function was absorbed, far beyond the duration of the interaction with the external field. In this work we formulate t…

Performance Analysis for Multi-User Holographic MIMO Downlink with Matched Filter Precoding
Gayathri Shekar, Saman Atapattu, Prathapasinghe Dharmawansa, Kandeepan Sithamparanathan
https://arxiv.org/abs/2510.04530

Performance Analysis for Multi-User Holographic MIMO Downlink with Matched Filter Precoding
Holographic MIMO (HMIMO) has emerged as a promising solution for future wireless systems by enabling ultra-dense, spatially continuous antenna deployments. While prior studies have primarily focused on electromagnetic (EM) modeling or simulation-based performance analysis, a rigorous communication-theoretic framework remains largely unexplored. This paper presents the first analytical performance study of a multi-user HMIMO downlink system with matched filter (MF) precoding - a low-complexity b…

Noch einige der zuletzt hier besonders häufig geteilten #News:
Web-Tipps: Stau verstehen
https://www.heise.de/news/Web-Tip…

Restrictions of PCBNs for integration-free computations
Alexis Derumigny, Niels Horsman, Dorota Kurowicka
https://arxiv.org/abs/2510.03518 https://arxiv.or…

Restrictions of PCBNs for integration-free computations
The pair-copula Bayesian Networks (PCBN) are graphical models composed of a directed acyclic graph (DAG) that represents (conditional) independence in a joint distribution. The nodes of the DAG are associated with marginal densities, and arcs are assigned with bivariate (conditional) copulas following a prescribed collection of parental orders. The choice of marginal densities and copulas is unconstrained. However, the simulation and inference of a PCBN model may necessitate possibly high-dimen…

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
Aaron Nagel, Johannes L\"owe
https://arxiv.org/abs/2510.05965

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
To simulate highly-resolved flow fields, we extend the Quantum Lattice Boltzmann Method (QLBM) to be able to simulate multiple time steps without state extraction or reinitialization. We adjust and extend given QLBM approaches from the literature to completely remove the need to measure or reinitialize the flow field in between the simulation time steps. Therefore, our algorithm does not require to sample the entire flow field at any time. We solve the linear advection-diffusion problem and der…

Enceladus Water Plume Modeling Using DSMC (i.e. Direct Simulation Monte Carlo): #Enceladus shoots less ice into space than previous estimates: https://tacc.utexas.edu/news/latest-news/2025/09/30/out-of-this-world-ice-geysers/

Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy
Weixu Zhu, Marco Dorigo, Mary Katherine Heinrich
https://arxiv.org/abs/2510.04774 https://

Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy
Our recently introduced self-organizing nervous system (SoNS) provides robot swarms with 1) ease of behavior design and 2) global estimation of the swarm configuration and its collective environment, facilitating the implementation of online automatic code generation for robot swarms. In a demonstration with 6 real robots and simulation trials with >30 robots, we show that when a SoNS-enhanced robot swarm gets stuck, it can automatically solicit and run code generated by an external LLM on the …

Self-Speculative Masked Diffusions
Andrew Campbell, Valentin De Bortoli, Jiaxin Shi, Arnaud Doucet
https://arxiv.org/abs/2510.03929 https://arxiv.org/pdf/2…

Self-Speculative Masked Diffusions
We present self-speculative masked diffusions, a new class of masked diffusion generative models for discrete data that require significantly fewer function evaluations to generate samples. Standard masked diffusion models predict factorized logits over currently masked positions. A number of masked positions are then sampled, however, the factorization approximation means that sampling too many positions in one go leads to poor sample quality. As a result, many simulation steps and therefore n…

From Patchwork to Network: A Comprehensive Framework for Demand Analysis and Fleet Optimization of Urban Air Mobility
Xuan Jiang, Xuanyu Zhou, Yibo Zhao, Shangqing Cao, Jinhua Zhao, Mark Hansen, Raja Sengupta
https://arxiv.org/abs/2510.04186

From Patchwork to Network: A Comprehensive Framework for Demand Analysis and Fleet Optimization of Urban Air Mobility
Urban Air Mobility (UAM) presents a transformative vision for metropolitan transportation, but its practical implementation is hindered by substantial infrastructure costs and operational complexities. We address these challenges by modeling a UAM network that leverages existing regional airports and operates with an optimized, heterogeneous fleet of aircraft. We introduce LPSim, a Large-Scale Parallel Simulation framework that utilizes multi-GPU computing to co-optimize UAM demand, fleet opera…

Quantum simulation of carbon capture in periodic metal-organic frameworks
Dario Rocca, Jerome F. Gonthier, Joshua Levin, Tobias Schafer, Andreas Gruneis, Byeol Kang, Hong Woo Lee
https://arxiv.org/abs/2510.02550

Quantum simulation of carbon capture in periodic metal-organic frameworks
Carbon capture is vital for decarbonizing heavy industries such as steel and chemicals. Metal-organic frameworks (MOFs), with their high surface area and structural tunability, are promising materials for CO2 capture. This study focuses on Fe-MOF-74, a magnetic Mott insulator with exposed metal sites that enhance CO2 adsorption. Its strongly correlated electronic structure challenges standard DFT methods, which often yield inconsistent predictions. We initially benchmark adsorption energies usi…

Assessment of Hybrid RANS-LES and WALE Formulations for Wake and Resistance Prediction of the BB2 Submarine
Noh Zainal Abidin (GeM), Frederic Grondin (GeM), Pol Muller (Naval Expert), Jean-Fran\c{c}ois Sigrist (Naval Expert)
https://arxiv.org/abs/2510.03383

Assessment of Hybrid RANS-LES and WALE Formulations for Wake and Resistance Prediction of the BB2 Submarine
Submarine hydrodynamics presents unique challenges in accurately predicting flow separation, wake structure, and resistance due to complex geometry and turbulent behaviour at high Reynolds (Re) numbers. Traditional Reynolds-Averaged Navier-Stokes (RANS) approaches are often limited in resolving unsteady flow structures and turbulence in the near and far regions. To address these limitations, hybrid RANS-LES models such as Detached Eddy Simulation (DES) and Large Eddy Simulation (LES) offer impr…

ILLUSTRating red nugget assembly through observations and simulations
Micheli T. Moura, Anna Ferr\'e-Mateu, Ana L. Chies-Santos, Cristina Furlanetto, Michael A. Beasley
https://arxiv.org/abs/2510.05312

ILLUSTRating red nugget assembly through observations and simulations
The properties of massive and compact early-type galaxies provide important constraints on early galaxy formation. Among these, massive relic galaxies, characterized by old stellar populations and minimal late-time accretion, are considered preserved compact galaxies from the high-$z$ Universe. We investigate compact and massive galaxies (CMGs) using the TNG50 cosmological simulation, applying uniform selection criteria matching observational surveys at $z=0$, $z=0.3$, and $z=0.7$, enabling dir…

Reliable and Scalable Robot Policy Evaluation with Imperfect Simulators
Apurva Badithela, David Snyder, Lihan Zha, Joseph Mikhail, Matthew O'Kelly, Anushri Dixit, Anirudha Majumdar
https://arxiv.org/abs/2510.04354

Reliable and Scalable Robot Policy Evaluation with Imperfect Simulators
Rapid progress in imitation learning, foundation models, and large-scale datasets has led to robot manipulation policies that generalize to a wide-range of tasks and environments. However, rigorous evaluation of these policies remains a challenge. Typically in practice, robot policies are often evaluated on a small number of hardware trials without any statistical assurances. We present SureSim, a framework to augment large-scale simulation with relatively small-scale real-world testing to prov…

Flow Matching for Robust Simulation-Based Inference under Model Misspecification
Pierre-Louis Ruhlmann, Pedro L. C. Rodrigues, Michael Arbel, Florence Forbes
https://arxiv.org/abs/2509.23385

Flow Matching for Robust Simulation-Based Inference under Model Misspecification
Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simulated data. A persistent challenge, however, is model misspecification: simulators are only approximations of reality, and mismatches between simulated and real data can yield biased or overconfident posteriors. We address this issue by introducing Flow Matching Corrected Posterior Estimation (FMCPE), a framework that leverages the flow matching paradigm …

Digital quantum simulation of many-body localization crossover in a disordered kicked Ising model
Tomoya Hayata, Kazuhiro Seki, Seiji Yunoki
https://arxiv.org/abs/2510.01983 htt…

Digital quantum simulation of many-body localization crossover in a disordered kicked Ising model
Simulating nonequilibrium dynamics of quantum many-body systems is one of the most promising applications of quantum computers. However, a faithful digital quantum simulation of the Hamiltonian evolution is very challenging in the present noisy quantum devices. Instead, nonequilibrium dynamics under the Floquet evolution realized by the Trotter decomposition of the Hamiltonian evolution with a large Trotter step size is considered to be a suitable problem for simulating in the present or near-t…

An Agent-Based Simulation of Ageing Societies: Accessibility and Care Dynamics in Remote Areas
Roberto garrone
https://arxiv.org/abs/2509.26496 https://arx…

An Agent-Based Simulation of Ageing Societies: Accessibility and Care Dynamics in Remote Areas
This paper presents an agent-based simulation of accessibility and care dynamics in ageing societies, applied to the Italian inner area of Premeno (VB). The model integrates census and municipal data, drone-derived elevation models, GIS road networks, and survey-based caregiving information to generate synthetic populations of older adults and their caregivers. Agents are organized into dyads with socio-economic and mobility attributes, enabling the simulation of both micro-scale accessibility …

Robust magnetic field estimates in star-forming galaxies with the equipartition formula in the absence of equipartition
H. -H. Sandy Chiu, Mateusz Ruszkowski, Maria Werhahn, Christoph Pfrommer, Timon Thomas
https://arxiv.org/abs/2510.03229

Robust magnetic field estimates in star-forming galaxies with the equipartition formula in the absence of equipartition
The equipartition model is widely used to estimate magnetic field strength from synchrotron intensity in radio galaxies, yet the validity of its underlying assumptions remains uncertain. Using an Arepo simulation which incorporates a two-moment cosmic ray (CR) transport scheme and a multiphase interstellar medium, we compare magnetic fields inferred from synthetic synchrotron emission maps with the true fields in the simulation. Starting from the derivation of the equipartition formula, we find…

Leveraging modal structure similarity for simulation of spatially evolving wakes
Divyanshu Gola, Sutanu Sarkar
https://arxiv.org/abs/2509.24925 https://arx…

Leveraging modal structure similarity for simulation of spatially evolving wakes
We present a new methodology to enable efficient simulation of high Reynolds number wakes. In this approach, a body-exclusive hybrid simulation at Re = 5 x 10^4 is initialized using inflow fields reconstructed from a lower Reynolds number (Re = 5 x 10^3) body-inclusive simulation. Spectral Proper Orthogonal Decomposition (SPOD) is employed to identify dominant coherent structures, and a low-rank reconstruction generates physically meaningful inflow conditions. The resulting simulations accurate…

PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Zixing Lei, Zibo Zhou, Sheng Yin, Yueru Chen, Qingyao Xu, Weixin Li, Yunhong Wang, Bowei Tang, Wei Jing, Siheng Chen
https://arxiv.org/abs/2510.01708

PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Humanoid whole-body control (WBC) policies trained in simulation often suffer from the sim-to-real gap, which fundamentally arises from simulator inductive bias, the inherent assumptions and limitations of any single simulator. These biases lead to nontrivial discrepancies both across simulators and between simulation and the real world. To mitigate the effect of simulator inductive bias, the key idea is to train policies jointly across multiple simulators, encouraging the learned controller to…

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Vasilis Skarlatos, Nikos Konofaos
https://arxiv.org/abs/2510.04736 https://arxiv.…

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Conditional Value-at-Risk (CVaR) is a leading tail-risk measure in finance, central to both regulatory and portfolio optimization frameworks. Classical estimation of CVaR and its gradients relies on Monte Carlo simulation, incurring $O(1/ε^2)$ sample complexity to achieve $ε$-accuracy. In this work, we design and analyze a quantum subgradient oracle for CVaR minimization based on amplitude estimation. Via a tripartite proposition, we show that CVaR subgradients can be estimated with $O(1/ε)$…

Rapid Mixing of Quantum Gibbs Samplers for Weakly-Interacting Quantum Systems
\v{S}t\v{e}p\'an \v{S}m\'id, Richard Meister, Mario Berta, Roberto Bondesan
https://arxiv.org/abs/2510.04954

Rapid Mixing of Quantum Gibbs Samplers for Weakly-Interacting Quantum Systems
Dissipative quantum algorithms for state preparation in many-body systems are increasingly recognised as promising candidates for achieving large quantum advantages in application-relevant tasks. Recent advances in algorithmic, detailed-balance Lindbladians enable the efficient simulation of open-system dynamics converging towards desired target states. However, the overall complexity of such schemes is governed by system-size dependent mixing times. In this work, we analyse algorithmic Lindbla…

Azimuthal Misalignments in Stellar Warp Structure as Dynamical Tracers of Mergers in Milky Way-like Galaxies
Lekshmi Thulasidharan, Elena D'Onghia, Robert Benjamin
https://arxiv.org/abs/2510.04194 …

Azimuthal Misalignments in Stellar Warp Structure as Dynamical Tracers of Mergers in Milky Way-like Galaxies
We investigate the origin of warps in stellar disks using high-resolution Milky Way analogs from the IllustrisTNG50 simulation. Focusing on galaxies that experienced a major merger, we identify a characteristic azimuthal misalignment between the warp structures of stellar populations formed before and after the merger. This misalignment persists even after correcting for differential rotation, suggesting it is a dynamical imprint of the merger rather than a consequence of internal kinematics. I…

The relationship between surface features and sub-surface turbulence: simulations and experiments
Omer M. Babiker, J{\o}rgen R. Aarnes, Ali Semati, Am\'elie Ferran, Yi Hui Tee, R. Jason Hearst, Simen {\AA}. Ellingsen
https://arxiv.org/abs/2510.03732

The relationship between surface features and sub-surface turbulence: simulations and experiments
Turbulent flows close beneath a free water surface are of central importance in the Earth system, yet remain relatively little studied with many open questions. We study the degree of correlation between surface motion and sub-surface velocities, comparing data from direct numerical simulation to a new experimental setup where the free-surface motion and sub-surface velocity field are measured simultaneously in a jet-stirred tank. A previous study showed a close correlation between the time ser…

A new Timestep Criterion for the Simulation of Immiscible Two-Phase Flow with IMPES Solvers
Dominik Burr, Stefan Rief, Konrad Steiner
https://arxiv.org/abs/2510.00577 https://…

A new Timestep Criterion for the Simulation of Immiscible Two-Phase Flow with IMPES Solvers
We present an iterative IMPES solver and a novel timestep criterion for the simulation of immiscible two-phase flow involving compressible fluid phases. The novel timestep criterion uses the Courant-Friedrichs-Lewy (CFL) condition and employs numerically computed velocity derivatives to adapt the timestep size, regardless of the dominant flow characteristics. The solver combined with this timestep criterion demonstrates both efficiency and robustness across a range of flow scenarios, including …

Benchmarking Quantum Simulation Methods
Calvin Ku, Yu-Cheng Chen, Alice Hu, Min-Hsiu Hsieh
https://arxiv.org/abs/2510.01710 https://arxiv.org/pdf/2510.0171…

Benchmarking Quantum Simulation Methods
Quantum Phase Estimation (QPE) is a cornerstone algorithm for fault-tolerant quantum computation, especially for electronic structure calculations of chemical systems. To accommodate the diverse characteristics of quantum chemical systems, numerous variants of QPE have been developed, each with distinct qubit and gate cost implications. In this paper, we quantify the impact of three key parameters on the overall quantum resource costs for the QPE algorithm: the choice between trotterization and…

Bounds on Atomistic Disorder for Scalable Electron Shuttling
Rapha\"el J. Prentki, Pericles Philippopoulos, Mohammad Reza Mostaan, F\'elix Beaudoin
https://arxiv.org/abs/2510.03113

Bounds on Atomistic Disorder for Scalable Electron Shuttling
Electron shuttling is emerging as a key enabler of scalable silicon spin-qubit quantum computing, but fidelities are limited by atomistic disorder. We introduce a multiscale simulation framework combining time-dependent finite-element electrostatics and atomistic tight-binding to capture the impact of random alloying and interface roughness on the valley splitting and phase of shuttled electrons. We find that shuttling fidelities are strongly suppressed by interface roughness, with a sharp anom…

Relativistic Quantum Simulation under Periodic and Dirichlet Boundary Conditions: A First-Quantised Framework for Near-Term Devices
Jaewoo Joo, Timothy P. Spiller, Kyunghyun Baek, Jeongho Bang
https://arxiv.org/abs/2509.22579

Relativistic Quantum Simulation under Periodic and Dirichlet Boundary Conditions: A First-Quantised Framework for Near-Term Devices
We present a new recipe for relativistic quantum simulation using the first quantisation approach, under periodic (PBC) and Dirichlet (DBC) boundary conditions. The wavefunction is discretised across a finite grid represented by system qubits, and the squared momentum operator is expressed using the finite-difference method based on quantum translation operations. The relativistic kinetic energy is approximated through a perturbative expansion of the total kinetic Hamiltonian, incorporating hig…

Absence of quantum Darwinism as a resource in secure quantum communication and computation
Bishal Kumar Das, Sourav Manna, Vaibhav Madhok
https://arxiv.org/abs/2510.03225 https:…

Absence of quantum Darwinism as a resource in secure quantum communication and computation
The emergence of classical world from underlying quantum mechanics is characterized by not only vanishing quantum correlations but also an unfolding of objectivity also known as quantum Darwinism. We show that the absence of this objectivity has a quantum advantage in cryptography and also provides the crucial missing link in efficient classical simulation of quantum circuits with zero discord. For this purpose, we consider a model of mixed state quantum computation where one is promised concor…

Combining Error Detection and Mitigation: A Hybrid Protocol for Near-Term Quantum Simulation
Dawei Zhong, William Munizzi, Huo Chen, Wibe Albert de Jong
https://arxiv.org/abs/2510.01181

Combining Error Detection and Mitigation: A Hybrid Protocol for Near-Term Quantum Simulation
Practical implementation of quantum error correction is currently limited by near-term quantum hardware. In contrast, quantum error mitigation has demonstrated strong promise for improving the performance of noisy quantum circuits without the requirement of full fault tolerance. In this work, we develop a hybrid error suppression protocol that integrates Pauli twirling, probabilistic error cancellation, and the $[[n, n-2, 2]]$ quantum error detecting code. In addition, to reduce overhead from e…