October 2025 arXiv papers — page 228

Daniel Valentine, Hannah R. Wakeford, Mark Hammond, Ryan C. Challener

Eclipse mapping is a powerful tool for measuring 3D profiles of exoplanet atmospheres. To date, only JWST has been capable of widely applying this technique, but as a general observatory, it is too time-limited to conduct population-level mapping studies. Ariel, on the other hand, is a dedicated exoplanet mission set to observe 1000 transiting exoplanets, ma

Ya Gao

In this paper, we consider the $L_p$ dual Minkowski problem for capillary hypersurfaces for $p>q$ and $q\leq 1$, which aims to find a capillary convex body with a prescribed capillary $(p,q)$-th dual curvature measure in the Euclidean half-space. We reduce it to a Monge-Amp\`ere type equation with a Robin boundary condition on the unit spherical cap, we prov

Xinhan Liu, Piet Van Mieghem

Our original paper \cite{VanMieghem2025} described the stochastic approximation $\overline{rel}_G(p)=\bigl[1-\phi_D(1-p)\bigr]^{N}$ in \cite[eq. (2.2)]{VanMieghem2025} and the first-order approximation $(R_1)_G(p)=\prod_{i=1}^{N}\!\bigl[1-(1-p)^{d_i}\bigr]$ in \cite[eq. (4.1)]{VanMieghem2025} as upper bounds for the all-terminal reliability polynomial \(rel_

Julián D. Alvarado-Gómez, Gaitee A. J. Hussain, Eliana M. Amazo-Gómez, Yu Xu

We present a comprehensive investigation of the magnetic cycle of the young, active solar analogue $\iota$ Horologii ($\iota$ Hor) based on intensive spectropolarimetric monitoring using HARPSpol. Over a nearly three-year campaign, the technique of Zeeman-Doppler Imaging (ZDI) was used to reconstruct 18 maps of the large-scale surface magnetic field of the s

Marco Linton

We show that finitely generated mapping tori of free groups have a canonical collection of maximal sub-mapping tori of finitely generated free groups with respect to which they are relatively hyperbolic and locally relatively quasi-convex. As a consequence, we characterise locally quasi-convex hyperbolic groups amongst free-by-cyclic and one-relator groups.

Ray Garner, Robert C. Kennicutt, Laurent Drissen, Carmelle Robert

Observing giant HII regions at fine spatial scales uncovers detailed structures and reveals variations in ionization, abundance, and dynamical properties of ionized gas and the effect of stellar feedback. Using emission line data of M33 observed with SITELLE as part of the Star-formation, Ionized Gas, and Nebular Abundances Legacy Survey (SIGNALS), we presen

Kamyar Khodamoradi, Farnam Mansouri, Sandra Zilles

We investigate the complexity of stable (or perturbation-resilient) instances of $\mathrm{k-M\small{EANS}}$ and $\mathrm{k-M\small{EDIAN}}$ clustering problems in metrics with small doubling dimension. While these problems have been extensively studied under multiplicative perturbation resilience in low-dimensional Euclidean spaces (e.g., (Friggstad et al.,

Adrian E. Fraser, Alexis K. Kaminski, Jeffrey S. Oishi

In astrophysical shear flows, the Kelvin-Helmholtz (KH) instability is generally suppressed by magnetic tension provided a sufficiently strong streamwise magnetic field. This is often used to infer upper (or lower) bounds on field strengths in systems where shear-driven fluctuations are (or are not) observed, on the basis that perturbations cannot grow in th

Pratyasha Gitika, Ryan M. Shannon, Matthew Bailes, Daniel J. Reardon

Pulsar timing arrays (PTAs) are Galactic-scale nanohertz-frequency gravitational wave (GW) detectors. Recently, several PTAs have found evidence for the presence of GWs in their datasets, but none of them have achieved a community-defined definitive (> 5$\sigma$) detection. Here, we identify limiting noise sources for PTAs and quantify their impact on sensit

S. Martinet, G. Goriely, A. Choplin, L. Siess

Propagating nuclear uncertainties to nucleosynthesis simulations is key to understand the impact of theoretical uncertainties on the predictions, especially for processes far from the stability region, where nuclear properties are scarcely known. While systematic (model) uncertainties have been thoroughly studied, the statistical (parameter) ones have been m

Ej Zhou, Caiqi Zhang, Tiancheng Hu, Chengzu Li

Confidence calibration, the alignment of a model's predicted confidence with its actual accuracy, is crucial for the reliable deployment of Large Language Models (LLMs). However, this critical property remains largely under-explored in multilingual contexts. In this work, we conduct the first large-scale, systematic studies of multilingual calibration ac

Gen Li, Bo Zhao, Jianfei Yang, Laura Sevilla-Lara

Generating interaction-centric videos, such as those depicting humans or robots interacting with objects, is crucial for embodied intelligence, as they provide rich and diverse visual priors for robot learning, manipulation policy training, and affordance reasoning. However, existing methods often struggle to model such complex and dynamic interactions. Whil

Flavio Giorgi, Matteo Silvestri, Cesare Campagnano, Fabrizio Silvestri

Explainable Artificial Intelligence has become a crucial area of research, aiming to demystify the decision-making processes of deep learning models. Among various explainability techniques, counterfactual explanations have been proven particularly promising, as they offer insights into model behavior by highlighting minimal changes that would alter a predic

Lior Benizri

In this letter, we study grand-canonical symmetric orbifolds of conformal field theories. We propose to define them as the direct sum of symmetric orbifolds of all degrees. The natural basis of operators is one that mixes all sectors. We describe this basis in terms of partial permutations, and explain how to define and calculate the operator product expansi

Mengqi Chen, Charita Dellaporta, Thomas B. Berrett, Theodoros Damoulas

Modern regression analyses are often undermined by covariate measurement error, misspecification of the regression model, and misspecification of the measurement error distribution. We present, to the best of our knowledge, the first Bayesian nonparametric learning framework targeting total robustness to all three challenges in general nonlinear regression.

Robin Adams, Jean-Philippe Bernardy, Lorenzo Perticone, Jeremy Pope

The operations to be performed by a quantum computer are almost invariably given in the form of a quantum circuit. In the final stage of compilation, a quantum circuit must be translated into the input signals accepted by the quantum hardware itself. For a quantum computer based on superconducting qubits, this will be a sequence of microwave control pulses t

Yoontae Hwang, Stefan Zohren

Modern deep learning for asset allocation typically separates forecasting from optimization. We argue this creates a fundamental mismatch where minimizing prediction errors fails to yield robust portfolios. We propose the Signature Informed Transformer to address this by unifying feature extraction and decision making into a single policy. Our model employs

Philippe Magalhães, Virginie Fresse, Benoît Suffran, Olivier Alata

Implementing convolutional neural networks (CNNs) on field-programmable gate arrays (FPGAs) has emerged as a promising alternative to GPUs, offering lower latency, greater power efficiency and greater flexibility. However, this development remains complex due to the hardware knowledge required and the long synthesis, placement and routing stages, which slow

William Davis, Olivia Dumitrescu

Nearly Frobenius structures and 2-dimensional Almost TQFTs were introduced and shown to be in categorical equivalence in arXiv:1907.05470 in the attempt to extend the Atiyah-Segal's definition to the category of infinite dimensional vector spaces. In this paper, we investigate nearly Frobenius structures and we give a classification result for Almost TQFTs i

Binze Li

Analogical reasoning lies at the core of human cognition and remains a fundamental challenge for artificial intelligence. Raven's Progressive Matrices (RPM) serve as a widely used benchmark to assess abstract reasoning by requiring the inference of underlying structural rules. While many vision-based and language-based models have achieved success on RPM tas

Noh Zainal Abidin, Frederic Grondin, Pol Muller, Jean-François Sigrist

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 regi

Peidi Song, Alexandros Daglis, Michael Filler, Ahmed Saeed

Advances in fabrication technology have enabled modularizing electronic components at the micro- or nano-scale and composing these modules on demand into larger circuits. Micromodular and nanomodular electronics (ME and NE) open a new design space in electronics, promising a degree of flexibility, extensibility, and accessibility far superior to traditional

Inga Seidler, Bence Hetényi, Lisa Sommer, Leonardo Massai

Holes in Ge/SiGe heterostructures are now a leading platform for semiconductor spin qubits, thanks to the high confinement quality, two-dimensional arrays, high tunability, and larger gate structure dimensions. One limiting factor for the operation of large arrays of qubits is the considerable variation in qubit frequencies or properties resulting from the s

Zhe Shen

Stability certificates play a critical role in ensuring the safety and reliability of robotic systems. However, deriving these certificates for complex, unknown systems has traditionally required explicit knowledge of system dynamics, often making it a daunting task. This work introduces a novel framework that learns a Lyapunov function directly from traject

Shiyi Zhang, Dong Liang, Hairong Zheng, Yihang Zhou

The reconstruction of visual information from brain activity fosters interdisciplinary integration between neuroscience and computer vision. However, existing methods still face challenges in accurately recovering highly complex visual stimuli. This difficulty stems from the characteristics of natural scenes: low-level features exhibit heterogeneity, while h

Muhammad Usama, Haris Koutsopoulos

Efficient real-time dispatching in urban metro systems is essential for ensuring service reliability, maximizing resource utilization, and improving passenger satisfaction. This study presents a novel deep learning framework centered on a Convolutional Long Short-Term Memory (ConvLSTM) model designed to predict the complex spatiotemporal propagation of train

Zhaojun Sun, Xuzhou Zhu, Xuanhe Zhou, Xin Tong

Academic survey writing, which distills vast literature into a coherent and insightful narrative, remains a labor-intensive and intellectually demanding task. While recent approaches, such as general DeepResearch agents and survey-specialized methods, can generate surveys automatically (a.k.a. LLM4Survey), their outputs often fall short of human standards an

Chaoxiang Ye, Guido de Croon, Salua Hamaza

Tiny flying robots hold great potential for search-and-rescue, safety inspections, and environmental monitoring, but their small size and limited computational resources constrain onboard sensing capabilities. Inspired by animals such as rats and moles, which rely on lightweight whiskers to navigate and perceive their surroundings through touch, we present a

Christophe Ringeval

We show that the recently released B-mode polarisation data from the South Pole Telescope (SPT) favour a non-vanishing contribution of primordial gravitational waves of inflationary origin which is in tension with the previous BICEP-Keck (BK) measurements. Our analysis uses the third-order slow-roll primordial power spectra, with theoretically motivated prio

Jacobo Romero-Díaz, Gerard I. Gállego, Oriol Pareras, Federico Costa

Speech-to-Text Translation (S2TT) systems built from Automatic Speech Recognition (ASR) and Text-to-Text Translation (T2TT) modules face two major limitations: error propagation and the inability to exploit prosodic or other acoustic cues. Chain-of-Thought (CoT) prompting has recently been introduced, with the expectation that jointly accessing speech and tr

Sushmitha S, Subhasmita Ray, Lavanya Rao, Mahesha P Nayak

Herein, a self-assembled hierarchical structure of hematite ($\alpha$-$Fe_2O_3$) was synthesized via a one-pot hydrothermal method. Subsequently, the nanomaterial was doped to get $M_{x}Fe_{2-x}O_3$ (M = Mn-Co; x = 0.01, 0.05, 0.1) at precise concentrations. The electrode was fabricated by coating the resulting nanocomposite onto a Nickel Foam (NF) substrate

Viktor Eisler, Riccarda Bonsignori, Stefano Scopa

We provide an exact analytical solution of the single-particle Schr\"odinger equation for a chain of non-interacting fermions subject to a time-dependent linear potential, with its slope varied as an arbitrary function of time. The resulting dynamics exhibit self-similar behavior, with a structure reminiscent of the domain wall melting problem, albeit charac

Matías Di Bernardo, Emmanuel Misley, Ignacio Correa, Mateo García Iacovelli

This work introduces a reproducible, metric-driven methodology to evaluate preprocessing pipelines for in-the-wild TTS corpora generation. We apply a custom low-cost pipeline to the first in-the-wild Argentine Spanish collection and compare 24 pipeline configurations combining different denoising and quality filtering variants. Evaluation relies on complemen

Beibei Lin, Tingting Chen, Robby T. Tan

Reference-driven image completion, which restores missing regions in a target view using additional images, is particularly challenging when the target view differs significantly from the references. Existing generative methods rely solely on diffusion priors and, without geometric cues such as camera pose or depth, often produce misaligned or implausible co

Terje Mildner, Paris Giampouras, Theodoros Damoulas

We prove rates of convergence and robustness to prior misspecification within a Generalised Variational Inference (GVI) framework with bounded divergences. This addresses a significant open challenge for GVI and Federated GVI that employ a different divergence to the Kullback-Leibler under prior misspecification, operate within a subset of possible probabili

Miguel M. G. Pascual-Caballo

In this paper, we prove the existence of nontrivial stationary homogeneous solutions with infinite energy (unbounded at infinity) for the SQG equation. Our analysis also covers the existence of stationary solutions for the generalized De Gregorio equation $\partial_t w+αu\,\partial_x w= w\,\partial_x u,\ \partial_x u=Hw$ with $α>\tfrac{1}{2}$, where $H$ deno

Isaac Alpizar-Chacon, Hieke Keuning, Imke de Jong, Ioanna Lykourentzou

The application of Artificial Intelligence, in particular Generative AI, has become more widespread among educational institutions. Opinions vary widely on whether integrating AI into classrooms is the way forward or if it is detrimental to the quality of education. Increasingly, research studies are giving us more insight into the consequences of using AI t

M. C. Bugueño, Facundo A. Gómez, Arianna Dolfi, Patricia B. Tissera

Understanding galaxy evolution is key to explaining the structures we observe in the present-day Universe. Counterrotating stellar disks (CRDs), i.e. co-spatial stellar disks rotating with opposite angular momentum, have been proposed as signatures of past accretion events. Therefore, they constitute potentially valuable tracers of galactic assembly. We aim

Mehdi Ghasemi, Murray Marshall

Let $f$ be a polynomial in $n$ variables $x_1,\dots,x_n$ with real coefficients. In [Ghasemi-Marshal], Ghasemi and Marshall give an algorithm, based on geometric programming, which computes a lower bound for $f$ on $\mathbb{R}^n$. In [Ghasemi-Lasserre-Marshall] Ghasemi, Lasserre and Marshall show how the algorithm in [Ghasemi-Marshal] can be modified to comp

Zhiting Mei, Ola Shorinwa, Anirudha Majumdar

Semantic distillation in radiance fields has spurred significant advances in open-vocabulary robot policies, e.g., in manipulation and navigation, founded on pretrained semantics from large vision models. While prior work has demonstrated the effectiveness of visual-only semantic features (e.g., DINO and CLIP) in Gaussian Splatting and neural radiance fields

Shinichi Tajima, Katsuyoshi Ohara, Akira Terui

An efficient method is proposed for computing the structure of Jordan blocks of a matrix of integers or rational numbers by exact computation. We have given a method for computing Jordan chains of a matrix with exact computation. However, for deriving just the structure of Jordan chains, the algorithm can be reduced to increase its efficiency. We propose a m

Beth Pearson, Ahmed Adnan, Zahraa S. Abdallah

Radiology report evaluation is a crucial part of radiologists' training and plays a key role in ensuring diagnostic accuracy. As part of the standard reporting workflow, a junior radiologist typically prepares a preliminary report, which is then reviewed and edited by a senior radiologist to produce the final report. Identifying semantic differences between

Irene Tenison, Soumyajit Chatterjee, Fahim Kawsar, Mohammad Malekzadeh

To utilize pre-trained neural networks on edge and mobile devices, we often require efficient adaptation to user-specific runtime data distributions while operating under limited compute and memory resources. On-device retraining with a target dataset can facilitate such adaptations; however, it remains impractical due to the increasing depth of modern neura

Tianhua Gao

Quadrotor stability under complex dynamic disturbances and model uncertainties poses significant challenges. One of them remains the underfitting problem in high-dimensional features, which limits the identification capability of current learning-based methods. To address this, we introduce a new perspective: Dimension-Decomposed Learning (DiD-L), from which

Filippo Troiani, Athanassios K. Boudalis

Quasi-optical experiments are emerging as a powerful technique to probe magnetic transitions in molecular spin systems. However, the simultaneous presence of the electric- and magnetic-dipole induced transitions poses the challenge of discriminating between these two contributions. Besides, the identification of the spin-electric transitions can hardly rely

B. Vollmer, M. Soida, V. Heesen

In addition to the radio continuum emission of the thin galactic disk, vertically extended emission is ubiquitous in starforming disk galaxies. This halo emission can represent an important fraction of the total emission of the galaxy The cosmic ray electrons (CRe) responsible for the radio continuum emission are produced within the thin disk and transported

Prem Agarwal, Kirill Melnikov, Ivan Pedron

We compute the next-to-leading-power corrections in the $N$-jettiness variable to the production of a prompt photon and a jet at next-to-leading order in perturbative QCD in the $q \bar q$ annihilation channel. We employ the $k_\perp$ jet algorithm and assume that the $N$-jettiness value divided by the jet transverse momentum is the smallest parameter in the

Liyang Xie, Haoran Zhang, Zhendong Wang, Wesley Tansey

Diffusion- and flow-based generative models have recently demonstrated strong performance in protein backbone generation tasks, offering unprecedented capabilities for de novo protein design. However, while achieving notable performance in generation quality, these models are limited by their generating speed, often requiring hundreds of iterative steps in t

Surjeet Singh Choudhary, Chun-Yen Shen, Saurabh Shrivastava

In this paper, we investigate the $L^p-$boundedness of the bilinear spherical maximal function associated with a general set of dilations $E\subset\R_+$. We quantify the range of $L^p-$boundedness in terms of a dilation-invariant notion of the upper Minkowski dimension of the set $E$. A particular case of this study settles an open question of $L^p-$boundedn

Michael Ben Ali, Imen Megdiche, André Peninou, Olivier Teste

Federated Learning (FL) is a decentralized paradigm that enables a client-server architecture to collaboratively train a global Artificial Intelligence model without sharing raw data, thereby preserving privacy. A key challenge in FL is Non-IID data. Quantity Skew (QS) is a particular problem of Non-IID, where clients hold highly heterogeneous data volumes.

Oriol Pareras, Gerard I. Gállego, Federico Costa, Cristina España-Bonet

Recent work on Speech-to-Text Translation (S2TT) has focused on LLM-based models, introducing the increasingly adopted Chain-of-Thought (CoT) prompting, where the model is guided to first transcribe the speech and then translate it. CoT typically outperforms direct prompting primarily because it can exploit abundant Automatic Speech Recognition (ASR) and Tex

Dorian Béret, Louka Hemmen, Vishwas Jindal, Sreyan Raha

Studies of excitonic transport in transition metal dichalcogenide monolayers have attracted increasing interest in recent years in order to develop nano-optoelectronic devices made with 2D materials. These studies began with low to moderate optical excitation regimes, and more recently have focused on high injection regimes where nonlinear effects appear. Th

Panayiotis Panayiotou

We report on the perturbative study, at next-to-leading order (NLO), of correlation functions at finite temperature of two chromoelectric fields connected by an adjoint Wilson line in Euclidean space. We find a source of asymmetry in two of the correlators studied. Finally, we compare the results with recent Lattice QCD calculations at high temperatures and

Naresh Kumar Devulapally, Shruti Agarwal, Tejas Gokhale, Vishnu Suresh Lokhande

Text-to-image diffusion models have demonstrated remarkable effectiveness in rapid and high-fidelity personalization, even when provided with only a few user images. However, the effectiveness of personalization techniques has lead to concerns regarding data privacy, intellectual property protection, and unauthorized usage. To mitigate such unauthorized usag

Hiyu Inoue, Shun-ichi Kimura, Hikaru Manabe, Koki Suetsugu

{\sc Yama Nim} is a variant of two piles {\sc Nim}. In this ruleset, the player chosses one of the piles and removes at least two tokens from the pile. In the same move, the player adds one token to the other pile. We show the winning strategies and SG-values of this ruleset. In addition, we introduce a generalization of {\sc Yama Nim}, named {\sc Digraph Ya

Michel Alexandre, Thiago Christiano Silva, Francisco A. Rodrigues

In this paper, we assess how the stability of financial networks is affected by interconnectedness considering its tiniest variation: the edge. We compute the impact of edges as the percentage difference in the systemic risk (SR) of the whole network caused by the inclusion of that edge. We apply this framework to a thorough Brazilian dataset to compute the

Peter A. Boyle, Richard C. Brower, George T. Fleming, Emanuel Katz

To investigate the three-dimensional quantum electrodynamics in the radial quantization on the lattice, the lattice action is constructed and the free limit is studied on $S^2 \times \mathbb{R}$. With the overlap fermion, it is numerically verified that the important symmetries of the theory can be realized on the lattice. The analytic correlators are derive

Pylyp Cherevan

We consider the resonant paraproduct (high-high $\to$ low regime) in the nonlinearity $(u\cdot\nabla)u$ for the three-dimensional Navier-Stokes equations. For sufficiently smooth, divergence-free u, we establish the a priori estimate without logarithmic loss $$\|R_N(u)\|{\dot H^{-1}} \lesssim N^{-1}\,\|u\|{\dot H^{1/2}}\,\|u\|_{\dot H^{1}},$$ with a constant

José D. Alvarado, Yoshiharu Kohayakawa, Patrick Morris, Guilherme O. Mota

The canonical van der Waerden theorem asserts that, for sufficiently large $n$, every colouring of $[n]$ contains either a monochromatic or a rainbow arithmetic progression of length $k$ ($k$-AP, for short). In this paper, we determine the threshold at which the binomial random subset $[n]_p$ almost surely inherits this canonical Ramsey type property. As an

Karunya Shailesh Shirali, Kyle Sherbert, Yanzhu Chen, Adrien Florio

We investigate the role of symmetries in constructing resource-efficient operator pools for adaptive variational quantum eigensolvers. In particular, we focus on the lattice Schwinger model, a discretized model of $1+1$ dimensional electrodynamics, which we use as a proxy for spin chains with a continuum limit. We present an extensive set of simulations comp

R. J. van den Hoogen, H. Forance, L. Taylor, M. Lawton

A procedure to determine the initial ansatz for the co-frame and spin connection characterizing a Riemann-Cartan geometry respecting a given group of continuous symmetries is illustrated. Given a particular group of symmetries and assuming an orthonormal gauge we can determine the co-frame and corresponding spin connection having this symmetry group by emplo

Guiliang Liu, Bo Yue, Yi Jin Kim, Kui Jia

Humanoid robots, as general-purpose physical agents, must integrate both intelligent control and adaptive morphology to operate effectively in diverse real-world environments. While recent research has focused primarily on optimizing control policies for fixed robot structures, this position paper argues for evolving both control strategies and humanoid robo

Svetlana Simak, Grigory Feofilov

In this article we present the results of application of the Monte Carlo modified Glauber model for the predictions of collision centrality dependence of the total charged-particle yields for 16O +16O and 20Ne+20Ne colliding systems at the LHC. Our model differs from the Standard Glauber model by the effective account of the energy losses in successive inela

Anna Trapp, Mersedeh Sadeghi, Andreas Vogelsang

Explainability is increasingly seen as an essential feature of rule-based smart environments. While counterfactual explanations, which describe what could have been done differently to achieve a desired outcome, are a powerful tool in eXplainable AI (XAI), no established methods exist for generating them in these rule-based domains. In this paper, we present

Frederic Higham, Tommy Yuan

This study explores the effectiveness of applying AI and gamification into a presentation platform aimed at University students wanting to improve their public speaking skills in their native tongue. Specifically, a platform based on the radio show, Just a Minute (JAM), is explored. In this game, players are challenged to speak fluently on a topic for 60 sec

Niels M. P. Neumann, Carlos M. R. Rocha, Jasper Verbree, Marc van Vliet

Significant efforts are being spent on building a quantum computer. At the same time, developments in quantum software are rapidly progressing. Insufficient quantum resources often are the problem when running quantum algorithms. New techniques can aid in using smaller quantum computers to run larger quantum algorithms. One of these techniques is circuit cut

Mahya Beheshti, Todd E Hudson, Rajvardhan Gadde, Glenn Alvarez Arias

Background: Coordinated control of eye and hand movements is critical for nearly all goal-directed actions, underpinning tasks ranging from simple object manipulation to complex tool use. This coordination relies on temporal coupling between reach and saccade. Stroke disrupts this process at several levels. Methods: We conducted a comparative eye-tracking st

Karim Farid, Rajat Sahay, Yumna Ali Alnaggar, Simon Schrodi

Compositional generalization, the ability to generate novel combinations of known concepts, is a key ingredient for visual generative models. Yet, not all mechanisms that enable or inhibit it are fully understood. In this work, we conduct a systematic study of how various design choices influence compositional generalization in image and video generation in

Jeffrey Regier

Upcoming astronomical surveys will produce petabytes of high-resolution images of the night sky, providing information about billions of stars and galaxies. Detecting and characterizing the astronomical objects in these images is a fundamental task in astronomy -- and a challenging one, as most of these objects are faint and many visually overlap with other

D. O. Chernyshov, A. V. Ivlev, V. A. Dogiel

The theory of cosmic-ray (CR) penetration into dense molecular clouds developed recently for relativistic particles by Chernyshov et al. (2024) is extended to non-relativistic CRs. Interstellar CRs streaming into the clouds are able to resonantly excite MHD waves in diffuse cloud envelopes. This leads to the self-modulation, such that streaming particles are

Martijn Gösgens, Bart P. G. Van Parys

We consider minimizing nonsmooth convex functions with bounded subgradients. However, instead of directly observing a subgradient at every step $k\in [0, \dots, N-1]$, we assume that the optimizer receives an adversarially corrupted subgradient. The adversary's power is limited to a finite corruption budget, but allows the adversary to strategically time its

Facundo Molina, Nazareno Aguirre, Alessandra Gorla

The effectiveness of testing in uncovering software defects depends not only on the characteristics of the test inputs and how thoroughly they exercise the software, but also on the quality of the oracles used to determine whether the software behaves as expected. Therefore, assessing the quality of oracles is crucial to improve the overall effectiveness of

Andreas Bouterakos, Georgios Tzounas

In this paper, we formulate a continuation method for tracking eigenvalue trajectories in power system models with time-delayed measurement and control signals. Such delays are known to weaken damping and reduce stability margins if not properly accounted for in stability analysis and control design. The proposed formulation follows selected eigenpairs direc

Rom Hirsch, Ziv Aharoni, Henry D. Pfister, Haim H. Permuter

In this paper, we adapt and analyze Neural Polar Decoders (NPDs) for end-to-end communication systems. While prior work demonstrated the effectiveness of NPDs on synthetic channels, this study extends the NPD to real-world communication systems. The NPD was adapted to complete OFDM and single-carrier communication systems. To satisfy practical system require

Eunjeong Lee, Jae-Hyouk Lee

In this article, we construct correspondences between polygon spaces in Euclidean spaces of dimension $2,3,5,9\ $and the quotient spaces of $2$-Steifel manifolds along the normed division algebra$\ \mathbb{F}$ real $\mathbb{R}$, complex $\mathbb{C}$, quaternions $\mathbb{H}$, octonions $\mathbb{O}$. For the purpose, we introduce Hopf map on $\mathbb{F}^{2}\

Ahsan Farabi, Israt Khandaker, Ibrahim Khalil Shanto, Md Abdul Ahad Minhaz

Facial Emotion Recognition (FER) is a key task in affective computing, enabling applications in human-computer interaction, e-learning, healthcare, and safety systems. Despite advances in deep learning, FER remains challenging due to occlusions, illumination and pose variations, subtle intra-class differences, and dataset imbalance that hinders recognition o

Mingfeng Fan, Jiaqi Cheng, Yaoxin Wu, Yifeng Zhang

In recent years, deep reinforcement learning (DRL) has gained traction for solving the NP-hard traveling salesman problem (TSP). However, limited attention has been given to the close-enough TSP (CETSP), primarily due to the challenge introduced by its neighborhood-based visitation criterion, wherein a node is considered visited if the agent enters a compact

Ubayd Bapoo, Clement N Nyirenda

This study evaluates the performance of Soft Actor Critic (SAC), Greedy Actor Critic (GAC), and Truncated Quantile Critics (TQC) in high-dimensional decision-making tasks using fully observable environments. The focus is on parametrized action (PA) spaces, eliminating the need for recurrent networks, with benchmarks Platform-v0 and Goal-v0 testing discrete a

Sathyanarayanan Chandramouli, Simeon I. Mistakidis, Garyfallia C. Katsimiga, Daniel J. Ratliff

We explore the existence and dynamical generation of rogue waves (RWs) within a one dimensional quantum droplet bearing environment. RWs are computed by deploying a spacetime fixed point scheme to the relevant extended Gross Pitaevskii equation (eGPE). Parametric regions where the ensuing RWs are different from their counterparts in the nonlinear Schroedinge

Yihang Liu, Yongshuai Zhang, Maohua Li

This paper constructs the $N$-fold Darboux transformation (DT) for the vector complex modified Korteweg-de Vries (vcmKdV) equation and presents its determinant representation. Utilizing the DT and multi-fold eigenvalue degeneracy, we derive globally bounded solutions for the vcmKdV equation, including $N$-bright-bright-bright solitons, $N$-dark-bright-bright

Pravesh K. Kothari, Jeff Xu

In this work, we revisit algorithms for Tensor PCA: given an order-$r$ tensor of the form $T = G+\lambda \cdot v^{\otimes r}$ where $G$ is a random symmetric Gaussian tensor with unit variance entries and $v$ is an unknown boolean vector in $\{\pm 1\}^n$, what's the minimum $\lambda$ at which one can distinguish $T$ from a random Gaussian tensor and more gen

Rongchen Guo, Vincent Francoeur, Isar Nejadgholi, Sylvain Gagnon

Speech Emotion Recognition (SER) is essential for improving human-computer interaction, yet its accuracy remains constrained by the complexity of emotional nuances in speech. In this study, we distinguish between descriptive semantics, which represents the contextual content of speech, and expressive semantics, which reflects the speaker's emotional state. A

Claudio Bonanno, Claudio Bonati, Massimo D'Elia

In this chapter we introduce the $\theta$-dependence and the topological properties of QCD, features of the strongly interacting sector which give rise to the strong CP problem in the more general context of the Standard Model of particle physics. We discuss the analytical approaches that can be used to obtain qualitative, or in some cases quantitative, info

Auxiliadora Padrón-Brito, Natalia Arteaga-Marrero, Ian Cunnyngham, Jeff Kuhn

We propose a focal-plane wavefront sensor (FPWFS) based on a short multimode fiber (MMF) capable of operating under moderately broadband illumination. By coupling the aberrated focal-plane field into an MMF of length <1 cm, we preserve modal interference over a 10 nm bandwidth at near-infrared wavelengths. The resulting output intensity pattern encodes pupil

Anirudh Krishna, Gilles Zémor

Dating back to the seminal work of von Neumann [von Neumann, Automata Studies, 1956], it is known that error correcting codes can overcome faulty circuit components to enable robust computation. Choosing an appropriate code is non-trivial as it must balance several requirements. Increasing the rate of the code reduces the relative number of redundant bits us

Valentin Zagrebnov

This short review is devoted to celebration of two major events in quantum physics. The first one is the birth of the concept of Bose-Einstein condensation (1925) and the second is the experimental proof that it does exist and appears in the liquid 4He simultaneously with superfluidity below the $\lambda$-point (1975). The both of these events are tightly re

Dexin Wang, Isha Jariwala, Ahmad Bazzi, Sundeep Rangan

Joint detection and localization of users and scatterers in multipath-rich channels on multiple bands is critical for integrated sensing and communication (ISAC) in 6G. Existing multiband sensing methods are limited by classical beamforming or computationally expensive approaches. This paper introduces alternating direction method of multipliers (ADMM)-assis

Natalia Zawadzka, Kristina Vaklinova, Tomasz Woźniak, Mihai I. Sturza

Exploring the electron tunneling mechanisms in diverse materials systems constitutes a versatile strategy for tailoring the properties of optoelectronic devices. In this domain, bipolar vertical tunneling junctions composed of van der Waals materials with vastly different electronic band structures enable simultaneous injection of electrons and holes into an

Peng Chen, Hui Jiang, Jing Wang

In this paper, we investigate the Milstein numerical scheme with step size $\eta$ for a stochastic differential equation driven by multiplicative Brownian motion. Under some appropriate coefficient conditions, the continuous-time system and its discrete Milstein scheme approximation each possess unique invariant measures, which we denote by $\pi$ and $\pi_\e

Luca Sortino, Armando Genco, Cristina Cruciano, Michele Guizzardi

Enabling coherent light-matter interactions is a critical step toward next-generation quantum technologies. However, achieving this under ambient temperature conditions remains challenging due to rapid dephasing in optically excited systems. Optical metasurfaces based on quasi-bound states in the continuum have recently emerged as a powerful platform for rea

Jamison Meindl, Yunsheng Tian, Tony Cui, Veronika Thost

Global optimization of expensive, derivative-free black-box functions requires extreme sample efficiency. While Bayesian optimization (BO) is the current state-of-the-art, its performance hinges on surrogate and acquisition function hyper-parameters that are often hand-tuned and fail to generalize across problem landscapes. We present ZeroShotOpt, a general-

Rita Peixoto, Filipe F. Correia, Thatiane Rosa, Eduardo Guerra

As organizations increasingly transition from monolithic systems to microservices, they aim to achieve higher availability, automatic scaling, simplified infrastructure management, enhanced collaboration, and streamlined deployments. However, this migration process remains largely manual and labour-intensive. While existing literature offers various strategi

Ruotong Liao, Guowen Huang, Qing Cheng, Thomas Seidl

Text-to-video (T2V) generation has surged in response to challenging questions, especially when a long video must depict multiple sequential events with temporal coherence and controllable content. Existing methods that extend to multi-event generation omit an inspection of the intrinsic factor in event shifting. The paper aims to answer the central question

Tianheng Zhu, Yinfeng Yu, Liejun Wang, Fuchun Sun

This paper presents EGSTalker, a real-time audio-driven talking head generation framework based on 3D Gaussian Splatting (3DGS). Designed to enhance both speed and visual fidelity, EGSTalker requires only 3-5 minutes of training video to synthesize high-quality facial animations. The framework comprises two key stages: static Gaussian initialization and audi

Jack C. M. Hughes, Fedor V. Kusmartsev

We show that the structure of the Lorentz group in four dimensions is such that unimodular (trace-free) gravity can be consistently represented as an algebraic condition on the symmetric product space of 2-forms. This condition states that the commutator between the Riemann tensor and the Hodge dual must be equal to the commutator between the Kulkarni-Nomizu

F. Gómez-Ortiz, A. Zabalo, A. M. Glazer, E. E. McCabe

Natural optical activity (NOA), the ability of a material to rotate the plane of polarized light, has traditionally been associated with structural chirality. However, this relationship has often been oversimplified, leading to conceptual misunderstandings, particularly when attempts are made to directly correlate structural handedness with optical rotatory

Soohaeng Yoo Willow, Tae Hyeon Park, Gi Beom Sim, Sung Wook Moon

Machine learning potentials (MLPs) have become essential for large-scale atomistic simulations, enabling ab initio-level accuracy with computational efficiency. However, current MLPs struggle with uncertainty quantification, limiting their reliability for active learning, calibration, and out-of-distribution (OOD) detection. We address these challenges by de

Ulysse Marquis, Marc Barthelemy

The growth of cities has traditionally been studied from a population perspective, while urban expansion-its spatial growth-has often been approached qualitatively. However, characterizing and modeling this spatial expansion is crucial, particularly given its parallels with surface growth extensively studied in physics. Despite these similarities, approaches

David Witt Nyström

We discuss two closely related Calabi-Yau theorems for degenerations of compact K\"ahler manifolds. The first is a Calabi-Yau theorem for big test configurations, that generalizes a result in [WN24]. It follows from recent joint work with Mesquita-Piccione [MW25], but is here given a more direct proof. The second result is a Calabi-Yau theorem for a wider cl

Xiaoqiao Chen, Xuewen Zhang, Minghao Han, Adrian Wing-Keung Law

The real-time operation of open water systems is essential for ensuring operational safety, satisfying operational requirements, and optimizing energy usage. However, existing rule-based control strategies rely heavily on human experience, while model-based approaches depend on accurate hydrodynamic models, which limit their applicability to water systems wi