Tootfinder

Luttons ensemble pour les droits des enfants et contre les violences sexistes et sexuelles !
Un appel du cœur pour que les violences Š l'encontre des enfants mineurs soient prises au sérieux et deviennent une réelle priorité de nos sociétés.
https://chardonsbleus.org/luttons…

Sub-Ensemble Isolation in SERF Magnetometry Enabled by Micrometer-Scale Polarization Control
Zihua Liang, Yuhao Zhang, Lu Liu, Jinsheng Hu, Peng Zhou, Gen Hu, Gaopu Hou, Mao Ye
https://arxiv.org/abs/2506.23160

Sub-Ensemble Isolation in SERF Magnetometry Enabled by Micrometer-Scale Polarization Control
Conventional understanding of spin-exchange relaxation-free (SERF) atom ensemble pertains to the common perception that the rapid exchange of atom state finally results in uniform time evolution of the whole ensemble. However, in this study, we demonstrate that by manipulation of pumping polarization in micro-meter level, misalignment between the time evolution of different sub-ensemble can be created within single SERF ensemble with unprecedent independency. A novel pumping system consists of …

On the Weight Distribution of Concatenated Code Ensemble Based on the Plotkin Construction
Xiao Ma
https://arxiv.org/abs/2508.21515 https://arxiv.org/pdf/2…

On the Weight Distribution of Concatenated Code Ensemble Based on the Plotkin Construction
In this note, we reveal a relation between the weight distribution of a concatenated code ensemble based on the Plotkin construction and those of its component codes. The relation may find applications in the calculation of the ensemble weight distributions for many codes, including Reed-Muller (RM)-like codes.

HSFN: Hierarchical Selection for Fake News Detection building Heterogeneous Ensemble
Sara B. Coutinho, Rafael M. O. Cruz, Francimaria R. S. Nascimento, George D. C. Cavalcanti
https://arxiv.org/abs/2508.21482

HSFN: Hierarchical Selection for Fake News Detection building Heterogeneous Ensemble
Psychological biases, such as confirmation bias, make individuals particularly vulnerable to believing and spreading fake news on social media, leading to significant consequences in domains such as public health and politics. Machine learning-based fact-checking systems have been widely studied to mitigate this problem. Among them, ensemble methods are particularly effective in combining multiple classifiers to improve robustness. However, their performance heavily depends on the diversity of …

Multi-Method Ensemble for Out-of-Distribution Detection
Lucas Rakotoarivony
https://arxiv.org/abs/2508.21463 https://arxiv.org/pdf/2508.21463

Multi-Method Ensemble for Out-of-Distribution Detection
Detecting out-of-distribution (OOD) samples is essential for neural networks operating in open-world settings, particularly in safety-critical applications. Existing methods have improved OOD detection by leveraging two main techniques: feature truncation, which increases the separation between in-distribution (ID) and OOD samples, and scoring functions, which assign scores to distinguish between ID and OOD data. However, most approaches either focus on a single family of techniques or evaluate…

Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
Rajiv Kailasanathan, William R. Clements, Mohammad Reza Boskabadi, Shawn M. Gibford, Emmanouil Papadakis, Christopher J. Savoie, Seyed Soheil Mansouri
https://arxiv.org/abs/2508.21438

Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
The development of continuous biomanufacturing processes requires robust and early anomaly detection, since even minor deviations can compromise yield and stability, leading to disruptions in scheduling, reduced weekly production, and diminished economic performance. These processes are inherently complex and exhibit non-linear dynamics with intricate relationships between process variables, thus making advanced methods for anomaly detection essential for efficient operation. In this work, we p…

Ensemble Simulations of Coronal Mass Ejections in Interplanetary Space with Elliptical Cone Models
Johan Muhamad, Tiar Dani, Muhamad Zamzam Nurzaman, Rasdewita Kesumaningrum, Santi Sulistiani, Farahhati Mumtahana, Gerhana P. Putri, Ayu D. Pangestu, Ahmad Z. Utama
https://arxiv.org/abs/2507.23204

Ensemble Simulations of Coronal Mass Ejections in Interplanetary Space with Elliptical Cone Models
The estimation of CME arrival time strongly depends on the CME propagation models in interplanetary space and the geometrical aspects of the CME model. We conducted ensemble simulations of CMEs propagation with various elliptical cone shapes to study the relation between the CME speed and the optimum cone shape. We numerically searched for the best elliptical aspect ratio of the elliptical cone for each CME in our CME-ICME pair data. We found that the fast CMEs tend to have a higher elliptical …

Ensemble Fuzzing with Dynamic Resource Scheduling and Multidimensional Seed Evaluation
Yukai Zhao, Shaohua Wang, Jue Wang, Xing Hu, Xin Xia
https://arxiv.org/abs/2507.22442 http…

Ensemble Fuzzing with Dynamic Resource Scheduling and Multidimensional Seed Evaluation
Fuzzing is widely used for detecting bugs and vulnerabilities, with various techniques proposed to enhance its effectiveness. To combine the advantages of multiple technologies, researchers proposed ensemble fuzzing, which integrates multiple base fuzzers. Despite promising results, state-of-the-art ensemble fuzzing techniques face limitations in resource scheduling and performance evaluation, leading to unnecessary resource waste. In this paper, we propose Legion, a novel ensemble fuzzing fram…

Ensemble Kalman Filter for Data Assimilation coupled with low-resolution computations techniques applied in Fluid Dynamics
Paul Jeanney, Ashton Hetherington, Shady E. Ahmed, David Lanceta, Susana Saiz, Jos\'e Miguel Perez, Soledad Le CLainche
https://arxiv.org/abs/2507.00539

Ensemble Kalman Filter for Data Assimilation coupled with low-resolution computations techniques applied in Fluid Dynamics
This paper presents an innovative Reduced-Order Model (ROM) for merging experimental and simulation data using Data Assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach implementing the Ensemble Kalman Filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the prop…

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction
Samuel Filgueira da Silva, Mehmet Fatih Ozkan, Faissal El Idrissi, Marcello Canova
https://arxiv.org/abs/2507.00353

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction
Accurate electrochemical models are essential for the safe and efficient operation of lithium-ion batteries in real-world applications such as electrified vehicles and grid storage. Reduced-order models (ROM) offer a balance between fidelity and computational efficiency but often struggle to capture complex and nonlinear behaviors, such as the dynamics in the cell voltage response under high C-rate conditions. To address these limitations, this study proposes an Adaptive Ensemble Sparse Identif…

A Rigorous Foundation for Stochastic Thermodynamics via the Microcanonical Ensemble
Xiangjun Xing
https://arxiv.org/abs/2506.23604 https://

A Rigorous Foundation for Stochastic Thermodynamics via the Microcanonical Ensemble
We consider a small Hamiltonian system strongly interacting with a much larger Hamiltonian system (the bath), while being driven by both a time-dependent control parameter and non-conservative forces. The joint system is assumed to be thermally isolated. Under the assumption of time-scale separation (TSS)--where the bath equilibrates much faster than the system and the external driving--the bath remains in instantaneous equilibrium, described by the microcanonical ensemble conditioned on the sy…

HyperFusion: Hierarchical Multimodal Ensemble Learning for Social Media Popularity Prediction
Liliang Ye (Huazhong University of Science and Technology, Wuhan, China), Yunyao Zhang (Huazhong University of Science and Technology, Wuhan, China), Yafeng Wu (Huazhong University of Science and Technology, Wuhan, China), Yi-Ping Phoebe Chen (La Trobe University, Melbourne, Australia), Junqing Yu (Huazhong University of Science and Technology, Wuhan, China), Wei Yang (Huazhong University of S…

HyperFusion: Hierarchical Multimodal Ensemble Learning for Social Media Popularity Prediction
Social media popularity prediction plays a crucial role in content optimization, marketing strategies, and user engagement enhancement across digital platforms. However, predicting post popularity remains challenging due to the complex interplay between visual, textual, temporal, and user behavioral factors. This paper presents HyperFusion, a hierarchical multimodal ensemble learning framework for social media popularity prediction. Our approach employs a three-tier fusion architecture that pro…

A Dual Ensemble Kalman Filter Approach to Robust Control of Nonlinear Systems: An Application to Partial Differential Equations
Anant A. Joshi, Saviz Mowlavi, Mouhacine Benosman
https://arxiv.org/abs/2508.21684

A Dual Ensemble Kalman Filter Approach to Robust Control of Nonlinear Systems: An Application to Partial Differential Equations
This paper considers the problem of data-driven robust control design for nonlinear systems, for instance, obtained when discretizing nonlinear partial differential equations (PDEs). A robust learning control approach is developed for nonlinear affine in control systems based on Lyapunov redesign technique. The robust control is developed as a sum of an optimal learning control which stabilizes the system in absence of disturbances, and an additive Lyapunov-based robustification term which hand…

Microscopic Rates of Convergence for Hermitian Unitary Ensembles
Mengchun Cai, Kyle Taljan
https://arxiv.org/abs/2506.23417 https://a…

Microscopic Rates of Convergence for Hermitian Unitary Ensembles
This paper provides microscopic rates of convergence (ROC) with respect to the $L^1$-Wasserstein distance for the eigenvalue determinantal point processes (DPPs) from the three major Hermitian unitary ensembles, the Gaussian Unitary Ensemble (GUE), the Laguerre Unitary Ensemble (LUE), and the Jacobi Unitary Ensemble (JUE) to their limiting point processes. We prove ROCs for the bulk of the GUE spectrum, the hard edge of the LUE spectrum, and the soft edges of the GUE, LUE, and JUE spectrums. Th…

Conflation of Ensemble-Learned Nuclear Mass Models for Enhanced Precision
Srikrishna Agrawal, N. Chandnani, T. Ghosh, G. Saxena, B. K. Agrawal, N. Paar
https://arxiv.org/abs/2508.21771

Conflation of Ensemble-Learned Nuclear Mass Models for Enhanced Precision
Ensemble learning algorithms, the gradient boosting and bagging regressors, are employed to correct the residuals of nuclear mass excess for a diverse set of six nuclear mass models. The weighted average of these corrected residuals reduces due to their partial cancellation, yielding a significant improvement in nuclear mass predictions. Our conflated model, which integrates ensemble learning and model averaging (ELMA), achieves a root mean square error of approximately 65 keV, well below the c…

Predicting any small-scale statistics of high-Reynolds-number turbulence using ensemble simulations
Lukas Bentkamp, Michael Wilczek
https://arxiv.org/abs/2506.23712

Predicting any small-scale statistics of high-Reynolds-number turbulence using ensemble simulations
The complex small-scale statistics of turbulence are a result of the combined cascading dynamics through all scales of the flow. Predicting these statistics using fully resolved simulations at the high Reynolds numbers that typically occur in engineering, geophysical, and astrophysical flows will exceed the capabilities of even the largest supercomputers for the foreseeable future. A common observation is that high-Reynolds-number flows are organized in clusters of intense turbulent activity se…

🇺🇦 #NowPlaying on BBCRadio3's #RoundMidnight
Awen Ensemble:
🎵 Agor
#AwenEnsemble
https://open.spotify.com/track/4osgEPZwVxU4WSbaK5hC3O

Le trafic est perturbé sur l'ensemble de la ligne.
Pour plus d'informations sur cette perturbation, consultez le fil X du RER C.
Motif : incident affectant la voie Š Musée d'Orsay
🤖 01/07 19:43

Le trafic est fortement perturbé sur l'ensemble de la ligne.
Pour plus d'informations sur cette perturbation, consultez le fil X de la ligne L.
Motif : panne d'alimentation électrique entre Asnières/Seine et Paris Saint-Lazare.
🤖 01/07 14:25

Leveraging Imperfection with MEDLEY A Multi-Model Approach Harnessing Bias in Medical AI
Farhad Abtahi, Mehdi Astaraki, Fernando Seoane
https://arxiv.org/abs/2508.21648 https://…

Leveraging Imperfection with MEDLEY A Multi-Model Approach Harnessing Bias in Medical AI
Bias in medical artificial intelligence is conventionally viewed as a defect requiring elimination. However, human reasoning inherently incorporates biases shaped by education, culture, and experience, suggesting their presence may be inevitable and potentially valuable. We propose MEDLEY (Medical Ensemble Diagnostic system with Leveraged diversitY), a conceptual framework that orchestrates multiple AI models while preserving their diverse outputs rather than collapsing them into a consensus. U…

Polarization-sensitive vector magnetometry using nitrogen-vacancy centers in diamond
M. S. J. Barson, T. J. Christie, J. P. Duff, K. Helmerson
https://arxiv.org/abs/2506.23878

Polarization-sensitive vector magnetometry using nitrogen-vacancy centers in diamond
By using an ensemble of nitrogen-vacancy (NV) centers, the vector components of a time-varying (AC) magnetic field are measured in a phase sensitive manner. This allows for the determination of the magnetic field's polarization. This polarization contains useful information about the nearby magnetic environment, such as the response of lossy or anisotropic materials, or the reactance of electrical currents.

Plus de 5134 € collectés ! 🚀 Objectif : 12 439 €. Ensemble, soutenons la justice et les victimes. Chaque don compte pour atteindre notre but. Merci pour votre engagement ! 💙🌟
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The shape of quadratic Gauss paths
Justine Dell, Djordje Mili\'cevi\'c
https://arxiv.org/abs/2508.21707 https://arxiv.org/pdf/2508.21707

The shape of quadratic Gauss paths
We consider the distribution of quadratic Gauss paths, polygonal paths joining partial sums of quadratic Gauss sums to square-free fundamental discriminant moduli in a dyadic range [Q,2Q]. We prove that this striking ensemble converges in law, as Q->\infty, to a random Fourier series we explicitly describe, and we prove a convergence in probability result and a classification result for the limiting shapes that explain the visually remarkable properties of these Gauss paths.

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure
Igor Sfiligoi, Emily A. Belli, Jeff Candy
https://arxiv.org/abs/2507.22245

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure
First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a un…

Heterogeneous Ensemble Enables a Universal Uncertainty Metric for Atomistic Foundation Models
Kai Liu, Zixiong Wei, Wei Gao, Poulumi Dey, Marcel H. F. Sluiter, Fei Shuang
https://arxiv.org/abs/2507.21297

Heterogeneous Ensemble Enables a Universal Uncertainty Metric for Atomistic Foundation Models
Universal machine learning interatomic potentials (uMLIPs) are reshaping atomistic simulation as foundation models, delivering near \textit{ab initio} accuracy at a fraction of the cost. Yet the lack of reliable, general uncertainty quantification limits their safe, wide-scale use. Here we introduce a unified, scalable uncertainty metric \(U\) based on a heterogeneous model ensemble with reuse of pretrained uMLIPs. Across chemically and structurally diverse datasets, \(U\) shows a strong correl…

🇺🇦 #NowPlaying on BBCRadio3's #MusicPlanet
Ustatshakirt Ensemble:
🎵 Live at FŸrdefestival
#UstatshakirtEnsemble

🇺🇦 #NowPlaying on KEXP's #JazzTheatre
Art Ensemble of Chicago:
🎵 Dreaming of the Masters / Excerpt Part 15 & 3A
#ArtEnsembleofChicago
https://open.spotify.com/track/7tHXpiOh9F1FgWm4x2LpCY

Historical Contingencies Steer the Topology of Randomly Assembled Graphs
Cole Mathis, Harrison B. Smith
https://arxiv.org/abs/2507.00335 https://

Historical Contingencies Steer the Topology of Randomly Assembled Graphs
Graphs are used to represent and analyze data in domains as diverse as physics, biology, chemistry, planetary science, and the social sciences. Across domains, random graph models relate generative processes to expected graph properties, and allow for sampling from distinct ensembles. Here we introduce a new random graph model, inspired by assembly theory, and characterize the graphs it generates. We show that graphs generated using our method represent a diverse ensemble, characterized by a br…

🇺🇦 #NowPlaying on #BBC6Music's #AmbientFocus
Satoshi Ashikawa:
🎵 Still Park Ensemble
#SatoshiAshikawa
https://wrwtfww.com/track/still-park-ensemble
https://open.spotify.com/track/3Op3F8ipO0YQO8ps4p5kYv

Ensemble Time-Dependent Density Functional Theory
Kimberly J. Daas, Steven Crisostomo, Kieron Burke
https://arxiv.org/abs/2507.19464 https://arxiv.org/pdf/…

Ensemble Time-Dependent Density Functional Theory
Time-dependent density functional theory (TDDFT) is a standard approach for calculating optical excitations of molecules and solids, while ensemble DFT (EDFT) is a promising alternative under development. We introduce ensemble TDDFT (ETDDFT), a practical theory that combines the two, generalizing both; we ensemble-generalize the Gross-Kohn equation and the exchange-correlation kernel of TDDFT, and generalize EDFT to time-dependent problems. We relate coordinate scaling to the adiabatic connecti…

La gare de Musée d'Orsay en direction de Juvisy n'est pas desservie jusqu'Š 20h. Le trafic est également perturbé sur l'ensemble de la ligne C. Si vous souhaitez rejoindre la gare de Musée d'Orsay, rendez-vous Š St Michel-Notre-Dame et empruntez un train GOTA, NORA, SARA ou VACK.
Pour plus d'informations sur cette perturbation, consultez le fil X du RER C.
Motif : incident affectant la voie Š Musée d'Orsay.
🤖 01/07 19:09

Ensemble-Based Estimation of Alzheimer's Disease Incidence from Dynamic Population Reconstructions
Giulia Bertaglia, Elisa Iacomini, Alex Viguerie
https://arxiv.org/abs/2507.20179

Ensemble-Based Estimation of Alzheimer's Disease Incidence from Dynamic Population Reconstructions
We present a two-stage methodology for reconstructing Alzheimer's disease (AD) incidence over time using ensemble Kalman inversion (EKI) applied to mortality data. In the first stage, we use EKI to infer temporal trends in all-cause and Alzheimer's-specific mortality by fitting an age-structured demographic model to observed death counts. This yields posterior estimates of evolving population structure and age-specific AD mortality rates. In the second stage, we apply a back-calculation procedu…

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/2]:
- HSFN: Hierarchical Selection for Fake News Detection building Heterogeneous Ensemble
Sara B. Coutinho, Rafael M. O. Cruz, Francimaria R. S. Nascimento, George D. C. Cavalcanti

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Attackers Strike Back? Not Anymore - An Ensemble of RL Defenders Awakens for APT Detection
Sidahmed Benabderrahmane, Talal Rahwan
https://arxiv.org/abs/2508.19072 https://

Attackers Strike Back? Not Anymore - An Ensemble of RL Defenders Awakens for APT Detection
Advanced Persistent Threats (APTs) represent a growing menace to modern digital infrastructure. Unlike traditional cyberattacks, APTs are stealthy, adaptive, and long-lasting, often bypassing signature-based detection systems. This paper introduces a novel framework for APT detection that unites deep learning, reinforcement learning (RL), and active learning into a cohesive, adaptive defense system. Our system combines auto-encoders for latent behavioral encoding with a multi-agent ensemble of …

Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, St\'ephanie L. van der Pas
https://arxiv.org/abs/2507.22004 https://

Horseshoe Forests for High-Dimensional Causal Survival Analysis
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity through the tree structure, we place a horseshoe prior directly on the step heights to achieve adaptive global-local shrinkage. This strategy allows flexible regularisation and reduces noise. We develop a reversible jump Gibbs sampler to accommodate the non-conjugate horseshoe prior within the tree ensemble framework. We s…

A Compute-Matched Re-Evaluation of TroVE on MATH
Tobias Sesterhenn, Ian Berlot-Attwell, Janis Zenkner, Christian Bartelt
https://arxiv.org/abs/2507.22069 https://

A Compute-Matched Re-Evaluation of TroVE on MATH
Reusing established theorems and formulas is central to mathematical problem solving, serving as essential building blocks for tackling increasingly complex challenges. Recent work, TroVE, argues that code-generating Large Language Models (LLMs) can benefit similarly on the MATH benchmark by inducing and reusing higher-level toolboxes. By allocating computational budget across an ensemble of three modes -- directly generating code, creating tools, and reusing tools -- TroVE claims to outperform…

Unraveling Open Quantum Dynamics with Time-Dependent Variational Monte Carlo
Christian Apostoli, Jacopo D'Alberto, Marco G. Genoni, Gianluca Bertaina, Davide E. Galli
https://arxiv.org/abs/2506.23928

Unraveling Open Quantum Dynamics with Time-Dependent Variational Monte Carlo
We introduce a method to simulate open quantum many-body dynamics by combining time-dependent variational Monte Carlo (tVMC) with quantum trajectory techniques. Our approach unravels the Lindblad master equation into an ensemble of stochastic Schrödinger equations for a variational ansatz, avoiding the exponential cost of density matrix evolution. The method is compatible with generic ansatzë, including expressive neural-network wavefunctions. We derive the nonlinear stochastic equations of m…

Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling
Trae Research Team, Pengfei Gao, Zhao Tian, Xiangxin Meng, Xinchen Wang, Ruida Hu, Yuanan Xiao, Yizhou Liu, Zhao Zhang, Junjie Chen, Cuiyun Gao, Yun Lin, Yingfei Xiong, Chao Peng, Xia Liu
https://arxiv.org/abs/2507.23370…

Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling
Software issue resolution is a critical challenge in software engineering and has garnered increasing attention in recent years. With the rapid advancement of large language models (LLMs), substantial progress has been made in addressing real-world software engineering tasks. Recent studies have introduced ensemble reasoning techniques to enhance the performance of LLM-based issue resolution. However, existing prompting-based methods still face limitations in effectively exploring large ensembl…

Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey
Yinuo Ren, Jue Wang
https://arxiv.org/abs/2506.23154 https:…

Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey
This study explores the potential of large language models (LLMs) to enhance expert forecasting through ensemble learning. Leveraging the European Central Bank's Survey of Professional Forecasters (SPF) dataset, we propose a comprehensive framework to evaluate LLM-driven ensemble predictions under varying conditions, including the intensity of expert disagreement, dynamics of herd behavior, and limitations in attention allocation.

🇺🇦 #NowPlaying on BBCRadio3's #EssentialClassics
Carl Philipp Emanuel Bach, Jean‐Guihen Queyras, Ensemble Resonanz & Riccardo Minasi:
🎵 Cello Concerto in A major, Wq 172 (3rd mvt)
#CarlPhilippEmanuelBach
https://open.spotify.com/track/4cmyqGTc4pmILTqB5ri2na

🌟 Chardons Bleus soutient 6 survivant-es dans l’affaire OKC-Spatz. Pour garantir un procès équitable, votre soutien financier est crucial. Ensemble, faisons triompher la justice ! 💙 👉 https://chardonsbleus.org/cagnotte-en-ligne

Ensemble Control of Stochastic Oscillators via Periodic and Feedback Control
Kaito Ito, Haruhiro Kume, Hideaki Ishii
https://arxiv.org/abs/2507.21441 https://

Ensemble Control of Stochastic Oscillators via Periodic and Feedback Control
We address the problem of steering the phase distribution of oscillators all receiving the same control input to a given target distribution. In a large population limit, the distribution of oscillators can be described by a probability density. Then, our problem can be seen as that of ensemble control with a constraint on the steady-state density. In particular, we consider the case where oscillators are subject to stochastic noise, for which the theoretical understanding is still lacking. Fir…

Open-closed 3d gravity as a random ensemble
Daniel L. Jafferis, Liza Rozenberg, Diandian Wang
https://arxiv.org/abs/2506.19817 https://

Open-closed 3d gravity as a random ensemble
We investigate an ensemble of boundary CFTs within the framework of a tensor model recently constructed to model 3d quantum gravity. The incorporation of CFT borders introduces new elements to the gravity theory. In particular, it leads to an open-closed extension of Virasoro TQFT, which in the classical limit gives rise to 3d gravity with tensionful end-of-the-world branes. It also provides predictions for off-shell manifolds with bordered asymptotic boundaries, such as the annulus wormhole. A…

CNN-based Surface Temperature Forecasts with Ensemble Numerical Weather Prediction over Medium-range Forecast Periods
Takuya Inoue (Meteorological Research Institute, Tsukuba, Japan), Takuya Kawabata (Meteorological Research Institute, Tsukuba, Japan)
https://arxiv.org/abs/2507.18937

CNN-based Surface Temperature Forecasts with Ensemble Numerical Weather Prediction over Medium-range Forecast Periods
This study proposes a method that integrates convolutional neural networks (CNNs) with ensemble numerical weather prediction (NWP) models, enabling surface temperature forecasting at lead times beyond the short-range (five-day) forecast period. Owing to limited computational resources, operational medium-range temperature forecasts typically rely on low-resolution NWP models, which are prone to systematic and random errors. To resolve these limitations, the proposed method first reduces systema…

Field theory vacuum and entropic dark energy models
Michael Maziashvili
https://arxiv.org/abs/2507.22093 https://arxiv.org/pdf/2507.22093

Field theory vacuum and entropic dark energy models
We investigate the cosmological implications of a novel definition of field theory vacuum energy. The free field Hamiltonian represented as an ensemble of oscillators (in the Fourier space) usually implies the presence of mass scale for these oscillators, which in quantum field theory is of little importance since quantum energy spectrum of oscillator is mass independent. This mass scale, however, may be interesting due to its possible gravitational implications. Since black hole physics puts a…

Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
Xinyi Sheng, Dominik Baumann
https://arxiv.org/abs/2508.21443 https…

Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
Reinforcement learning (RL) algorithms typically optimize the expected cumulative reward, i.e., the expected value of the sum of scalar rewards an agent receives over the course of a trajectory. The expected value averages the performance over an infinite number of trajectories. However, when deploying the agent in the real world, this ensemble average may be uninformative for the performance of individual trajectories. Thus, in many applications, optimizing the long-term performance of individ…

Ensemble Average Analysis of Non-Adaptive Group Testing with Sparse Pooling Graphs
Emna Ben Yacoub, Gianluigi Liva, Enrico Paolini, Marco Chiani
https://arxiv.org/abs/2507.20281

Ensemble Average Analysis of Non-Adaptive Group Testing with Sparse Pooling Graphs
A combinatorial analysis of the false alarm (FA) and misdetection (MD) probabilities of non-adaptive group testing with sparse pooling graphs is developed. The analysis targets the combinatorial orthogonal matching pursuit and definite defective detection algorithms in the noiseless, non-quantitative setting. The approach follows an ensemble average perspective, where average FA/MD probabilities are computed for pooling graph ensembles with prescribed degree distributions. The accuracy of the a…

Thermodynamic properties of CrMnFeCoNi high entropy alloy at elevated electronic temperatures
Nikita Medvedev
https://arxiv.org/abs/2506.23171 https://

Thermodynamic properties of CrMnFeCoNi high entropy alloy at elevated electronic temperatures
The Cantor alloy (equiatomic CrMnFeCoNi) is a high-entropy alloy with unique physical properties and radiation resistance. To model its response to intense laser pulses, the parameters of the electronic ensemble are required. In this work, the electronic heat capacity, thermal conductivity, and electron-phonon coupling strength at elevated electronic temperatures are evaluated using a combined approach that incorporates tight-binding molecular dynamics and the Boltzmann equation. The damage thr…

Aw yeah
https://www.musicradar.com/guitars/boss-rt-2-rotary-ensemble-pedal

“This powerhouse pedal authentically recreates the complex sonic magic of its inspiration”: Boss puts psychedelic Hendrix and Gilmour rotating speaker sounds on the menu with the RT-2 Rotary Ensemble
What do you do when everyone loves that trippy rotating speaker sound but no has the space (or budget) for one? Boss has the answer – and it has three modes and lots of features

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Solitons, chaos, and quantum phenomena: a deterministic approach to the Schr\"odinger equation
Dami\`a Gomila
https://arxiv.org/abs/2507.22868 https://

Solitons, chaos, and quantum phenomena: a deterministic approach to the Schrödinger equation
We show that the Schrödinger equation describes the ensemble mean dynamics of solitons in a Galilean invariant field theory where we interpret solitons as particles. On a zero background, solitons move classically, following Newton`s second law, however, on a non-zero amplitude chaotic background, their momentum and position fluctuate fulfilling an exact uncertainty relation, which give rise to the emergence of quantum phenomena. The Schrodinger equation for the ensemble of solitons is obtaine…

Dense Subgraph Clustering and a New Cluster Ensemble Method
The-Anh Vu-Le, Jo\~ao Alfredo Cardoso Lamy, Tom\'as Alessi, Ian Chen, Minhyuk Park, Elfarouk Harb, George Chacko, Tandy Warnow
https://arxiv.org/abs/2508.17013

Dense Subgraph Clustering and a New Cluster Ensemble Method
We propose DSC-Flow-Iter, a new community detection algorithm that is based on iterative extraction of dense subgraphs. Although DSC-Flow-Iter leaves many nodes unclustered, it is competitive with leading methods and has high-precision and low-recall, making it complementary to modularity-based methods that typically have high recall but lower precision. Based on this observation, we introduce a novel cluster ensemble technique that combines DSC-Flow-Iter with modularity-based clustering, to pr…

🇺🇦 Auf radioeins läuft...
Frank Popp Ensemble feat. Lucy Kruger:
🎵 Drifting
#NowPlaying #FrankPoppEnsemble #LucyKruger
https://open.spotify.com/track/6fOtBvrsXgc6iqOAy6YOaX

Crosslisted article(s) found for q-bio.OT. https://arxiv.org/list/q-bio.OT/new
[1/1]:
- Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
Kailasanathan, Clements, Boskabadi, Gibford, Papadakis, Savoie, Mansouri

Light-induced Pairing Instability of Ultrafast Electron Beams with Space Charge Interactions
Hao Geng, Qiaofei Pan, Jian Kang, Yiming Pan
https://arxiv.org/abs/2507.00869

Light-induced Pairing Instability of Ultrafast Electron Beams with Space Charge Interactions
Ultrafast electron beams are essential for many applications, yet space-charge interactions in high-intensity beams lead to energy dissipation, coherence loss, and pulse broadening. Existing techniques mitigate these effects by using low-flux beams, preserving beam coherence into the quantum regime. Here, we propose a novel approach by treating the electrons as a strongly correlated Fermi gas rather than merely as an ensemble of charged point-like particles. We introduce a photon-induced pairin…

Random matrix theory of charge distribution in disordered quantum impurity models
Maxime Debertolis, Serge Florens
https://arxiv.org/abs/2507.22586 https://

Random matrix theory of charge distribution in disordered quantum impurity models
We introduce a bare-bone random matrix quantum impurity model, by hybridizing a localized spinless electronic level with a bath of random fermions in the Gaussian Orthogonal Ensemble (GOE). While stripped out of correlations effects, this model reproduces some salient features of the impurity charge distribution obtained in previous works on interacting disordered impurity models. Computing by numerical sampling the impurity charge distribution in our model, we find a crossover from a Gaussian …

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Will it glue? On short-depth designs beyond the unitary group
Lorenzo Grevink, Jonas Haferkamp, Markus Heinrich, Jonas Helsen, Marcel Hinsche, Thomas Schuster, Zolt\'an Zimbor\'as
https://arxiv.org/abs/2506.23925

Will it glue? On short-depth designs beyond the unitary group
We provide a range of results on several groups of broad interest in quantum information science: the Clifford group, the orthogonal group, the unitary symplectic groups, and the matchgate group. For all of these groups, we prove that analogues of unitary designs cannot be generated by any circuit ensemble with light-cones that are smaller than the system size. This implies linear lower bounds on the circuit depth in one-dimensional systems. For the Clifford and orthogonal group, we moreover sh…

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Spatialize v1.0: A Python/C Library for Ensemble Spatial Interpolation
Alvaro F. Ega\~na, Alejandro Ehrenfeld, Felipe Garrido, Mar\'ia Jes\'us Valenzuela, Juan F. S\'anchez-P\'erez
https://arxiv.org/abs/2507.17867

Spatialize v1.0: A Python/C++ Library for Ensemble Spatial Interpolation
In this paper, we present Spatialize, an open-source library that implements ensemble spatial interpolation, a novel method that combines the simplicity of basic interpolation methods with the power of classical geostatistical tools, like Kriging. It leverages the richness of stochastic modelling and ensemble learning, making it robust, scalable and suitable for large datasets. In addition, Spatialize provides a powerful framework for uncertainty quantification, offering both point estimates an…

An approach to control design for two-level quantum ensemble systems
Ruikang Liang, Gong Cheng
https://arxiv.org/abs/2506.19740 https://

An approach to control design for two-level quantum ensemble systems
Quantum ensemble systems arise in a variety of applications, including NMR spectroscopy and robust quantum control. While their theoretical properties have been extensively studied, relatively little attention has been given to the explicit construction of control inputs. In this paper, we address this gap by presenting a fully implementable control strategy for a one-parameter family of driftless two-level quantum systems. The proposed method is supported by rigorous analysis that guarantees a…

Full counting statistics and first-passage times in quantum Markovian processes: Ensemble relations, metastability, and fluctuation theorems
Paul Menczel, Christian Flindt, Fredrik Brange, Franco Nori, Clemens Gneiting
https://arxiv.org/abs/2508.18614

Full counting statistics and first-passage times in quantum Markovian processes: Ensemble relations, metastability, and fluctuation theorems
We develop a comprehensive framework for characterizing fluctuations in quantum transport and nonequilibrium thermodynamics using two complementary approaches: full counting statistics and first-passage times. Focusing on open quantum systems governed by Markovian Lindblad dynamics, we derive general ensemble relations that connect the two approaches at all times, and we clarify how the steady states reached at long times relate to those reached at large jump counts. In regimes of metastability…

Neural network ensemble for computing cross sections for rotational transitions in H$_{2}$O H$_{2}$O collisions
Bikramaditya Mandal, Dmitri Babikov, Phillip C. Stancil, Robert C. Forrey, Roman V. Krems, Naduvalath Balakrishnan
https://arxiv.org/abs/2507.18974

Neural network ensemble for computing cross sections for rotational transitions in H$_{2}$O + H$_{2}$O collisions
Water (H$_2$O) is one of the most abundant molecules in the universe and is found in a wide variety of astrophysical environments. Rotational transitions in H$_2$O + H$_2$O collisions are important in modeling environments rich in water molecules but they are computationally intractable using quantum mechanical methods. Here, we present a machine learning (ML) tool using an ensemble of neural networks (NNs) to predict cross sections to construct a database of rate coefficients for rotationally …

🔊 #NowPlaying on #BBCRadio3:
#ThroughTheNight
- Ensemble Midtvest from the NŸrre Vosborg Chamber Music Festival
Ensemble Midtvest and harpist Anneleen Lenaerts perform Takemitsu, Dvorak and Piazzolla. John Shea presents.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002dxyw

Luttons ensemble pour les droits des enfants et contre les violences sexistes et sexuelles !
Un appel du cœur pour que les violences Š l'encontre des enfants mineurs soient prises au sérieux et deviennent une réelle priorité de nos sociétés.
https://chardonsbleus.org/luttons…

Boosting Ensembles for Statistics of Tails at Conditionally Optimal Advance Split Times
Justin Finkel, Paul A. O'Gorman
https://arxiv.org/abs/2507.22310 https://

Boosting Ensembles for Statistics of Tails at Conditionally Optimal Advance Split Times
Climate science needs more efficient ways to study high-impact, low-probability extreme events, which are rare by definition and costly to simulate in large numbers. Rare event sampling (RES) and ensemble boosting offer a novel strategy to extract more information from those occasional simulated events: small perturbations in advance can turn a moderate event into a severe one, which otherwise might not come for many more simulation-years. But how to choose this ``advance split time'' (AST) rem…

Revisiting RAG Ensemble: A Theoretical and Mechanistic Analysis of Multi-RAG System Collaboration
Yifei Chen, Guanting Dong, Yutao Zhu, Zhicheng Dou
https://arxiv.org/abs/2508.13828

Revisiting RAG Ensemble: A Theoretical and Mechanistic Analysis of Multi-RAG System Collaboration
Retrieval-Augmented Generation (RAG) technology has been widely applied in recent years. However, despite the emergence of various RAG frameworks, a single RAG framework still cannot adapt well to a broad range of downstream tasks. Therefore, how to leverage the advantages of multiple RAG systems has become an area worth exploring. To address this issue, we have conducted a comprehensive and systematic investigation into ensemble methods based on RAG systems. Specifically, we have analyzed the …

Logarithmically Divergent Vacuum Energy in Effective Field Theory
Jonathan Sullivan-Wood, Craig Pryor
https://arxiv.org/abs/2507.21320 https://arxiv.org/pd…

Logarithmically Divergent Vacuum Energy in Effective Field Theory
The vacuum energy density due to a single quantum field diverges quarticly with the ultraviolet cutoff $Λ$, in wild disagreement with the value implied by cosmological observations. We show that in effective field theories containing bosons and fermions the requirement of a Lorentz invariant vacuum makes any divergence faster than logarithmic exponentially unlikely. We show this by generating an ensemble of mass spectra by Monte Carlo, and find that the probability distribution function for th…

🔊 #NowPlaying on #BBCRadio3:
#NewMusicShow
- Klaus Lang's Diaphonia
Riot Ensemble and Yaron Deutsch perform Klaus Lang's Diaphonia for electric guitar and ensemble plus new releases from Mary Halvorson and Hannah Kendall.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002dxyt

Luttons ensemble pour les droits des enfants et contre les violences sexistes et sexuelles !
Un appel du cœur pour que les violences Š l'encontre des enfants mineurs soient prises au sérieux et deviennent une réelle priorité de nos sociétés.
https://chardonsbleus.…

Ensemble nonlinear optical learner by electrically tunable linear scattering
Tunan Xia, Cheng-Kuan Wu, Duan-Yi Guo, Lidan Zhang, Bofeng Liu, Tsung-Hsien Lin, Xingjie Ni, Iam-Choon Khoo, Zhiwen Liu
https://arxiv.org/abs/2506.19976

Ensemble nonlinear optical learner by electrically tunable linear scattering
Recent progress in effective nonlinearity, achieved by exploiting multiple scatterings within the linear optical regime, has been demonstrated to be a promising approach to enable nonlinear optical processing without relying on actual material nonlinearity. Here we introduce an ensemble nonlinear optical learner, via electrically tunable linear scattering in a liquid-crystal-polymer composite film under low optical power and low applied electrical voltages. We demonstrate, through several image…

A digital twin of atomic ensemble quantum memories
Elizabeth Robertson, Benjamin Maa{\ss}, Konrad Tschernig, Janik Wolters
https://arxiv.org/abs/2506.20403

A digital twin of atomic ensemble quantum memories
Accurate performance estimation of experimentally demonstrated quantum memories is key to understand the nuances in their deployment in photonic quantum networks. While several software packages allow for accessible quantum simulation, they often do not account for the loss and noise in physical devices. We present a framework for modeling ensemble-based atomic quantum memories using the quantum channel formalism. We provide a Kraus matrix representation of several experimentally implemented st…

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
The Wind Ensemble of the Hungarian Radio Orchestra & Jean Françaix:
🎵 Le Gai Paris for wind ensemble
#TheWindEnsembleoftheHungarianRadioOrchestra #JeanFrançaix
https://open.spotify.com/track/305XftVWtuVe33OKLGy352

📢 Il reste seulement 7305 € Š collecter ! Ensemble, atteignons notre objectif. Un grand merci Š tous les donateurs pour leur générosité. Votre soutien est essentiel, n'oubliez pas de partager notre campagne. #Solidarité #Engagement

Impedance-tuned microwave loop for fast, homogeneous Rabi oscillations of a dense ensemble of NV-diamond electronic spins
Han Sae Jung, Johannes Cremer, Aoyang Zhang, Sangha Kim, Guang Yang, Ronald L. Walsworth, Donhee Ham
https://arxiv.org/abs/2507.17689

Impedance-tuned microwave loop for fast, homogeneous Rabi oscillations of a dense ensemble of NV-diamond electronic spins
Obtaining a high Rabi oscillation frequency homogeneously across a spatially-extended population of nitrogen-vacancy (NV) center electronic spins in diamond is useful for efficient spin-state manipulation of the NV ensemble and in using NVs to detect ensembles of other spin species. Here, we achieve a high, homogeneous Rabi frequency for a dense NV ensemble by enhancing the microwave magnetic fields in the center region of a diamond-coupled planar metallic loop via systematic engineering that i…

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LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecasting
Yilin Zhuang, Karthik Duraisamy
https://arxiv.org/abs/2506.09193 https://…

LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecasting
Accurate probabilistic weather forecasting demands both high accuracy and efficient uncertainty quantification, challenges that overburden both ensemble numerical weather prediction (NWP) and recent machine-learning methods. We introduce LaDCast, the first global latent-diffusion framework for medium-range ensemble forecasting, which generates hourly ensemble forecasts entirely in a learned latent space. An autoencoder compresses high-dimensional ERA5 reanalysis fields into a compact representa…

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Luttons ensemble pour les droits des enfants et contre les violences sexistes et sexuelles !
Un appel du cœur pour que les violences Š l'encontre des enfants mineurs soient prises au sérieux et deviennent une réelle priorité de nos sociétés.
https://chardonsbleus.org/luttons…

Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
Adithya Mohan, Dominik R\"o{\ss}le, Daniel Cremers, Torsten Sch\"on
https://arxiv.org/abs/2507.17070

Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
Recent advancements in Deep Reinforcement Learning (DRL) have demonstrated its applicability across various domains, including robotics, healthcare, energy optimization, and autonomous driving. However, a critical question remains: How robust are DRL models when exposed to adversarial attacks? While existing defense mechanisms such as adversarial training and distillation enhance the resilience of DRL models, there remains a significant research gap regarding the integration of multiple defense…

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The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
Francesco Calcagno, Delmar G. A. Cabral, Ivan Rivalta, Victor S. Batista
https://arxiv.org/abs/2508.15896

The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
Designing molecules with optimized properties remains a fundamental challenge due to the intricate relationship between molecular structure and properties. Traditional computational approaches that address the combinatorial number of possible molecular designs become unfeasible as the molecular size increases, suffering from the so-called `curse of dimensionality' problem. Recent advances in quantum computing hardware present new opportunities to address this problem. Here, we introduce the Qua…

🇺🇦 #NowPlaying on BBCRadio3's #Breakfast
John Wilbye & The Hilliard Ensemble:
🎵 Sweet hony-sucking bees
#JohnWilbye #TheHilliardEnsemble
https://open.spotify.com/track/0q7KgFR97YSLjZ37MC2kGg

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🇺🇦 #NowPlaying on BBCRadio3's #EssentialClassics
Niels Wilhelm Gade & Ensemble MidtVest:
🎵 String Sextet in E flat major, Op.44 (2nd mvt)
#NielsWilhelmGade #EnsembleMidtVest

🇺🇦 #NowPlaying on BBCRadio3's #MusicMatters
Hugh Shrapnel & Ivory Duo Piano Ensemble:
🎵 3rd Lamp post in Tressillian Road
#HughShrapnel #IvoryDuoPianoEnsemble

🇺🇦 #NowPlaying on BBCRadio3's #EssentialClassics
Georg Philipp Telemann & Ensemble Symposium:
🎵 Scherzo in A major TWV 42:A4 (Lunedi)
#GeorgPhilippTelemann #EnsembleSymposium

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
Leonel Power & The Hilliard Ensemble:
🎵 Salve Regina
#LeonelPower #TheHilliardEnsemble

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1/7

🇺🇦 #NowPlaying on BBCRadio3's #ClassicalMixtape
Luise Adolpha Le Beau, Yekaterina Chemberdzhi, Berlin Chamber Symphony Ensemble & Jürgen Bruns:
🎵 Piano Concerto in D minor, Op. 37: II. Poco adagio
#LuiseAdolphaLeBeau #newRelease 🆕 album
https://open.spotify.com/track/52jKJeA4ligC7ZlpnresdS

🇺🇦 #NowPlaying on BBCRadio3's #Breakfast
Giovanni Battista Vitali, Alessandro Andiani, Claudio Andriani & Italico Splendore:
🎵 Sonate da camera, Op. 14 (Excerpts Arr. for Chamber Ensemble): Suite No. 3
https://open.spotify.com/track/0S2Vc5HlvMh351dsK2k6Qc

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Luttons ensemble pour les droits des enfants et contre les violences sexistes et sexuelles !
Un appel du cœur pour que les violences Š l'encontre des enfants mineurs soient prises au sérieux et deviennent une réelle priorité de nos sociétés.
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Nous avons déjŠ collecté 5134 € grâce Š vous ! 💪 Mais nous devons encore atteindre notre objectif : 12 439 € pour soutenir la justice. Ensemble, faisons avancer ce projet. Merci ! 🙏 👉 https://chardonsbleus.org/cagnotte-en-ligne

Malheureusement, notre cagnotte juridique nécessite encore votre aide. Les victimes que notre association représente ont toujours besoin de vous. Nous avons déjŠ collecté plus de 9399€ grâce Š votre générosité 🙏💙
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