Tootfinder

MonochromeEvolutionaryBioDigitalMultiCellularSymbiosisStruggle
(Selected stills from my infinitely evolving C-SCAPE project, 2022 - made with #MonochromeMonday

A Multi-Simulation Bridge for IoT Digital Twins
Marco Picone, Samuele Burattini, Marco Melloni, Prasad Talasila, Davide Ziglioli, Matteo Martinelli, Nicola Bicocchi, Alessandro Ricci, Peter Gorm Larsen
https://arxiv.org/abs/2510.08164

A Multi-Simulation Bridge for IoT Digital Twins
The increasing capabilities of Digital Twins (DTs) in the context of the Internet of Things (IoT) and Industrial IoT (IIoT) call for seamless integration with simulation platforms to support system design, validation, and real-time operation. This paper introduces the concept, design, and experimental evaluation of the DT Simulation Bridge - a software framework that enables diverse interaction patterns between active DTs and simulation environments. The framework supports both the DT developme…

Simulation-based inference for neutrino interaction model parameter tuning
Karla Tame-Narvaez, Aleksandra \'Ciprijanovi\'c, Steven Gardiner, Giuseppe Cerati
https://arxiv.org/abs/2510.07454

Simulation-based inference for neutrino interaction model parameter tuning
High-energy physics experiments studying neutrinos rely heavily on simulations of their interactions with atomic nuclei. Limitations in the theoretical understanding of these interactions typically necessitate ad hoc tuning of simulation model parameters to data. Traditional tuning methods for neutrino experiments have largely relied on simple algorithms for numerical optimization. While adequate for the modest goals of initial efforts, the complexity of future neutrino tuning campaigns is expe…

A new simulation from the European Central Bank shows that the digital euro could trigger a deposit outflow of up to €700B during a run on commercial banks (Reuters)
https://www.reuters.com/business/finance/digital…

Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models
David Layden, Ryan Sweke, Vojt\v{e}ch Havl\'i\v{c}ek, Anirban Chowdhury, Kirill Neklyudov
https://arxiv.org/abs/2510.08462

Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models
Flow models are a cornerstone of modern machine learning. They are generative models that progressively transform probability distributions according to learned dynamics. Specifically, they learn a continuous-time Markov process that efficiently maps samples from a simple source distribution into samples from a complex target distribution. We show that these models are naturally related to the Schrödinger equation, for an unusual Hamiltonian on continuous variables. Moreover, we prove that the…

Multi-modal Foundation Model for Cosmological Simulation Data
Bin Xia, Nesar Ramachandra, Azton I. Wells, Salman Habib, John Wise
https://arxiv.org/abs/2510.07684 https://

Multi-modal Foundation Model for Cosmological Simulation Data
We present a multi-modal foundation model for astrophysical galaxy data, designed to map between simulation- and observation-based galactic features. Our encoder-only transformer flexibly ingests scalar quantities (e.g., redshifts, galaxy masses) and vectors (e.g., star formation histories, spectra), supporting multi-task training that includes within-modality reconstruction and cross-modality prediction. With a dynamic masking strategy, the model can query arbitrary galaxy properties from part…

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…

Aeolian dune simulation (made in 2017) for #MeerMittwoch:
The images show a screenshot of the JavaScript application to create the simulation and some Houdini renders of exported height fields. The sim itself had 5 macro params to control the behavior of the interactive deposit/erosion/transportation process. It supported tileable patterns, customizable seed terrain (images) and ran r…

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…

Scalings and simulation requirements in two-phase flows
Luis H. Hatashita, Pranav Nathan, Suhas S. Jain
https://arxiv.org/abs/2510.07727 https://arxiv.org/…

Scalings and simulation requirements in two-phase flows
In this work, important two-phase flow scalings are derived, which enable the quantification of grid-point and time-step requirements as functions of Re, We, and Ca numbers. The adequate grid resolution is determined in the inertia-dominated regime with the aid of high-fidelity simulations of stationary two-phase homogeneous isotropic turbulence by evaluating convergence of total interfacial area, size distribution, SMD, and curvature distribution. Although standards for DNS for single-phase tu…

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…

Baudrillard (the author of Simulation and Simulacra in 1981, the inspiration for The Matrix movies) predicted Internet bubbles and the influence of algorithms and AI 30 years ago.
https://theconversation.com/how-the-fr

How the French philosopher Jean Baudrillard predicted today’s AI 30 years before ChatGPT
Baudrillard’s genius lay in foreseeing what these rudimentary devices like fax machines suggested about likely future uses of technology.

Effects of skewing collision cells on transport properties in multiparticle collision dynamics simulations
Jinny Cha, Wilfred Kwabena Darko, Jeremy C. Palmer, Michael P. Howard
https://arxiv.org/abs/2510.07446

Effects of skewing collision cells on transport properties in multiparticle collision dynamics simulations
Multiparticle collision dynamics (MPCD) is a mesoscale simulation technique that uses a simplified solvent to model hydrodynamic interactions. Rather than interact through pairwise forces, MPCD solvent particles undergo momentum-exchanging collisions within spatially localized cells according to prescribed rules. The conventional MPCD algorithm employs cubic collision cells, but this choice is not optimal for systems that are most naturally described using skewed simulation boxes. Here, we inve…

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.

NFL longshot picks, 2025 Week 6 odds, player props: This parlay would return well over $44,000 on a $10 bet

https://www.cbssports.com/nfl/news/nfl-week-6-longshot-parlay…

When "self-driving" cars were first getting some hype back in ~2015 or so, I told people who asked me that I didn't think they'd be safe, and that I wished the same money were being invested in driver-assistance systems instead.
At the time, advocates were claiming that self-driving cars would be safer than human drivers.
We now have both self-driving cars and some nifty new driver assistance things, and it turns out that the self-driving cars are in fact being developed by corporations whose attention to the bottom line results in danger to others on the road pretty regularly. I don't actually have stats here for whether they're "safer than human drivers" or not, but the opportunity for one bad software update to make *all* self-driving cars dangerous at once kinda makes me doubt that.
Here's an example of Waymo cars getting "more aggressive" as they try to balance between being too timid and obstructing traffic (including emergency vehicles) and being too dangerous:
https://archive.ph/JJuGv
Here's another example of passing stopped schoolbusses leading to a software recall:
https://abcnews.go.com/GMA/News/waymo-issue-voluntary-software-recall-after-close-calls/story?id=128207776
In the first article, Waymo claims 91% fewer serious accidents per mile. Obviously an independent audit would be actually trustworthy, but even if we take that claim at face value, it's meaningless if an update tomorrow causes 100,000 accidents.
Note that they could be using better engineering practices, and the fact that they aren't shows that they don't care enough about the risks. They could be deploying new software versions incrementally and slowly, letting new versions rack up lots of miles only on a few vehicles before pushing them to a fleet. The should also have the equivalent of a simulation unit test for "schoolbus is stopped, what do?" and if a software version fails that test, it doesn't make it to the fleet. Clearly they don't have that.
I feel pretty vindicated in my earlier prediction that this tech is a bad idea in the hands of the current advocates.

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…

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…

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…

Stability of digital and analog quantum simulations under noise
Jayant Rao, Jens Eisert, Tommaso Guaita
https://arxiv.org/abs/2510.08467 https://arxiv.org/…

Stability of digital and analog quantum simulations under noise
Quantum simulation is a central application of near-term quantum devices, pursued in both analog and digital architectures. A key challenge for both paradigms is the effect of imperfections and noise on predictive power. In this work, we present a rigorous and physically transparent comparison of the stability of digital and analog quantum simulators under a variety of perturbative noise models. We provide rigorous worst- and average-case error bounds for noisy quantum simulation of local obser…

DexMan: Learning Bimanual Dexterous Manipulation from Human and Generated Videos
Jhen Hsieh, Kuan-Hsun Tu, Kuo-Han Hung, Tsung-Wei Ke
https://arxiv.org/abs/2510.08475 https://…

DexMan: Learning Bimanual Dexterous Manipulation from Human and Generated Videos
We present DexMan, an automated framework that converts human visual demonstrations into bimanual dexterous manipulation skills for humanoid robots in simulation. Operating directly on third-person videos of humans manipulating rigid objects, DexMan eliminates the need for camera calibration, depth sensors, scanned 3D object assets, or ground-truth hand and object motion annotations. Unlike prior approaches that consider only simplified floating hands, it directly controls a humanoid robot and …

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…

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…

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…

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

Crosslisted article(s) found for cs.IT. https://arxiv.org/list/cs.IT/new
[1/1]:
- Simulation of Quantum Repeater Networks under Decoherence and Purification Constraints
Wenhan Li, Shiyu Zhang

Replaced article(s) found for eess.SP. https://arxiv.org/list/eess.SP/new
[1/1]:
- From Simulation to Practice: Generalizable Deep Reinforcement Learning for Cellular Schedulers
Petteri Kela, Bryan Liu, Alvaro Valcarce

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…

Simulation of the thermoelectric effect in a multi-metallic superconducting cavity
N. K. Raut, N. Stilin, J. Vennekate, S. Wang, G. Ciovati
https://arxiv.org/abs/2510.08285 http…

Simulation of the thermoelectric effect in a multi-metallic superconducting cavity
Superconducting radio frequency accelerating cavities made with different material layers, such as copper, Nb or Nb3Sn, are susceptible to thermoelectric effects due to differences in Seebeck coefficients between the metals. A temperature gradient across the surfaces can drive thermoelectric currents, which may impact the cavity performance. A layered Cu/Nb/Nb3Sn single cell cavity was tested with cryocoolers in 2022. Three heaters were mounted on the cavity surface at different locations and t…

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…

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…

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.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- AI-Generated Compromises for Coalition Formation: Modeling, Simulation, and a Textual Case Study
Eyal Briman, Ehud Shapiro, Nimrod Talmon
https://arxiv.org/abs/2512.05983 https://mastoxiv.page/@arXiv_csMA_bot/115688474865840195
- Going All-In on LLM Accuracy: Fake Prediction Markets, Real Confidence Signals
Michael Todasco
https://arxiv.org/abs/2512.05998
- Small-Gain Nash: Certified Contraction to Nash Equilibria in Differentiable Games
Vedansh Sharma
https://arxiv.org/abs/2512.06791 https://mastoxiv.page/@arXiv_csLG_bot/115689591150148735
- Characterizing Lane-Changing Behavior in Mixed Traffic
Sungyong Chung, Alireza Talebpour, Samer H. Hamdar
https://arxiv.org/abs/2512.07219 https://mastoxiv.page/@arXiv_csMA_bot/115688571373683355
- Understanding LLM Agent Behaviours via Game Theory: Strategy Recognition, Biases and Multi-Agent ...
Kiet Huynh, et al.
https://arxiv.org/abs/2512.07462 https://mastoxiv.page/@arXiv_csMA_bot/115688610063828863
- Optimal Auction Design under Costly Learning
Kemal Ozbek
https://arxiv.org/abs/2512.07798 https://mastoxiv.page/@arXiv_econTH_bot/115688939067758036
toXiv_bot_toot

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…

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…

FlowLensing: Simulating Gravitational Lensing with Flow Matching
Hamees Sayed, Pranath Reddy, Michael W. Toomey, Sergei Gleyzer
https://arxiv.org/abs/2510.07878 https://

FlowLensing: Simulating Gravitational Lensing with Flow Matching
Gravitational lensing is one of the most powerful probes of dark matter, yet creating high-fidelity lensed images at scale remains a bottleneck. Existing tools rely on ray-tracing or forward-modeling pipelines that, while precise, are prohibitively slow. We introduce FlowLensing, a Diffusion Transformer-based compact and efficient flow-matching model for strong gravitational lensing simulation. FlowLensing operates in both discrete and continuous regimes, handling classes such as different dark…

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…

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…

Three-Dimensional Electrostatic and Quantum-Confinement Modeling of Silicon Nanowire Double Quantum Dots
Nilesh Pandey, Dipanjan Basu, Leonard F Register, Sanjay K Banerjee
https://arxiv.org/abs/2510.07831

Three-Dimensional Electrostatic and Quantum-Confinement Modeling of Silicon Nanowire Double Quantum Dots
We present a three-dimensional simulation study of silicon nanowire double quantum dots with leads, which extends beyond traditional effective-mass or quasi-1D and quasi-2D approaches typically applied to bulk or planar geometries. Using the Sentaurus QTX, we self-consistently couple a 3-D Poisson solver with two-dimensional Schrödinger solutions along the strongly confined width * thickness cross-sections normal to the transport direction, yielding bound-state energies and wavefunctions acros…

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…

Modified Monte Carlo method with the heat bath algorithm for a model cuprate
Yu. D. Panov, V. A. Ulitko, D. N. Yasinskaya, A. S. Moskvin
https://arxiv.org/abs/2510.08289 https:/…

Modified Monte Carlo method with the heat bath algorithm for a model cuprate
The results of numerical simulation using a modified Monte Carlo method with a heat bath algorithm for the pseudospin model of cuprates are presented. The temperature phase diagrams are constructed for various degrees of doping and for various parameters of the model, and the effect of local correlations on the critical temperatures of the model cuprate is investigated. It is shown that, in qualitative agreement with the results of the mean field, the heat bath algorithm leads to a significant …

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…

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…

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…

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…

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…

DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model
Xueyi Liu, He Wang, Li Yi
https://arxiv.org/abs/2510.08556 https://

DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model
Achieving generalized in-hand object rotation remains a significant challenge in robotics, largely due to the difficulty of transferring policies from simulation to the real world. The complex, contact-rich dynamics of dexterous manipulation create a "reality gap" that has limited prior work to constrained scenarios involving simple geometries, limited object sizes and aspect ratios, constrained wrist poses, or customized hands. We address this sim-to-real challenge with a novel framework that …

Replaced article(s) found for q-fin.MF. https://arxiv.org/list/q-fin.MF/new
[1/1]:
- Efficient simulation of a new class of Volterra-type SDEs
Ofelia Bonesini, Giorgia Callegaro, Martino Grasselli, Gilles Pag\`es

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

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…

🇧🇪 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…

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 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

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…

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…

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…

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
…

Towards Proprioception-Aware Embodied Planning for Dual-Arm Humanoid Robots
Boyu Li, Siyuan He, Hang Xu, Haoqi Yuan, Yu Zang, Liwei Hu, Junpeng Yue, Zhenxiong Jiang, Pengbo Hu, B\"orje F. Karlsson, Yehui Tang, Zongqing Lu
https://arxiv.org/abs/2510.07882

Towards Proprioception-Aware Embodied Planning for Dual-Arm Humanoid Robots
In recent years, Multimodal Large Language Models (MLLMs) have demonstrated the ability to serve as high-level planners, enabling robots to follow complex human instructions. However, their effectiveness, especially in long-horizon tasks involving dual-arm humanoid robots, remains limited. This limitation arises from two main challenges: (i) the absence of simulation platforms that systematically support task evaluation and data collection for humanoid robots, and (ii) the insufficient embodime…

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…

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

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…

„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.

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…

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…

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…

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…

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

Injecting Hallucinations in Autonomous Vehicles: A Component-Agnostic Safety Evaluation Framework
Alexandre Moreira Nascimento, Gabriel Kenji Godoy Shimanuki, L\'ucio Flavio Vismari, Jo\~ao Batista Camargo Jr, Jorge Rady de Almeida Jr, Paulo Sergio Cugnasca, Anna Carolina Muller Queiroz, Jeremy Noah Bailenson
https://arxiv.org/abs/2510…

Injecting Hallucinations in Autonomous Vehicles: A Component-Agnostic Safety Evaluation Framework
Perception failures in autonomous vehicles (AV) remain a major safety concern because they are the basis for many accidents. To study how these failures affect safety, researchers typically inject artificial faults into hardware or software components and observe the outcomes. However, existing fault injection studies often target a single sensor or machine perception (MP) module, resulting in siloed frameworks that are difficult to generalize or integrate into unified simulation environments. …

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…

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…

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…

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…

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…

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…

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 …

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…

Platform-Agnostic Modular Architecture for Quantum Benchmarking
Neer Patel, Anish Giri, Hrushikesh Pramod Patil, Noah Siekierski, Avimita Chatterjee, Sonika Johri, Timothy Proctor, Thomas Lubinski, Siyuan Niu
https://arxiv.org/abs/2510.08469

Platform-Agnostic Modular Architecture for Quantum Benchmarking
We present a platform-agnostic modular architecture that addresses the increasingly fragmented landscape of quantum computing benchmarking by decoupling problem generation, circuit execution, and results analysis into independent, interoperable components. Supporting over 20 benchmark variants ranging from simple algorithmic tests like Bernstein-Vazirani to complex Hamiltonian simulation with observable calculations, the system integrates with multiple circuit generation APIs (Qiskit, CUDA-Q, C…

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

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

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

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 …

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…

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…

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…

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…