October 2025 arXiv papers — page 131

Ahmad Awad, Erik Scharwächter

Soil organic carbon (SOC) sequestration projects require unbiased, precise and cost-effective Monitoring, Reporting, and Verification (MRV) systems that balance sampling costs against uncertainty deductions imposed by regulatory frameworks. Design-based estimators guarantee unbiasedness but cannot exploit auxiliary data. Model-based approaches (VCS Methodolo

Youngin Kim, Laurenz Kulmer, Jae-Yong Kim, Hamza Kurt

We demonstrate an electronic-photonic (EP) interface for multiuser optical wireless communication (OWC), consisting of a multibeam optical phased array (MBOPA) along with co-integrated electro-optic (EO) modulators and high-speed CMOS drivers. The MBOPA leverages a path-length difference in the optical phased array (OPA) along with wavelength-division multip

Riccardo Santi, Riccardo Salami, Simone Calderara

Nowdays, there are an abundance of portable devices capable of collecting large amounts of data and with decent computational power. This opened the possibility to train AI models in a distributed manner, preserving the participating clients' privacy. However, because of privacy regulations and safety requirements, elimination upon necessity of a client cont

Alexsandro A. Ferreira, Gauss M. Cordeiro

The generalized Marshall-Olkin Lomax distribution is introduced, and its properties are easily obtained from those of the Lomax distribution. A regression model for censored data is proposed. The parameters are estimated through maximum likelihood, and consistency is verified by simulations. Three real datasets are selected to illustrate the superiority of t

Theophanes K. Karydas, Rodrigo Vicente, Gianfranco Bertone

In extreme/intermediate-mass-ratio inspirals (E/IMRIs) embedded in dark-matter (DM) spikes, the secondary black hole can accrete collisionless particles from the surrounding halo. We study how the companion's spin controls this process, and the ensuing back-reaction on the magnitude and direction of the companion's spin vector. We find that higher spin suppr

S. K. Mahatha, A. Kar, J. Corral-Sertal, Josu Diego

First-order phase transitions, characterized by a discontinuous change in the order parameter, are intriguing phenomena in condensed matter physics. However, the underlying, material-specific, microscopic mechanisms often remain unclear. Here, we unveil a high-temperature incommensurate charge-order precursor with the wave vector $\mathbf{q}^* = (0, \frac{1}

Yuxiang Huang, Pengjie Wang, Jicheng Han, Weilin Zhao

Decoding throughput improvements from larger inference batches are limited by GPU memory, which is largely consumed by the key-value (KV) cache. Prior training-free KV cache offloading alleviates this by keeping redundant context on the CPU and fetching only a sparse subset for attention, but it often degrades long-generation quality due to training-inferenc

Xizhuo Zhang, Bing Yao

Recent advances in sensing and imaging technologies have enabled the collection of high-dimensional spatiotemporal data across complex geometric domains. However, effective modeling of such data remains challenging due to irregular spatial structures, rapid temporal dynamics, and the need to jointly predict multiple interrelated physical variables. This pape

Jiahao Wang, Nived Chebrolu, Yifu Tao, Lintong Zhang

Building an online 3D LiDAR mapping system that produces a detailed surface reconstruction while remaining computationally efficient is a challenging task. In this paper, we present PlanarMesh, a novel incremental, mesh-based LiDAR reconstruction system that adaptively adjusts mesh resolution to achieve compact, detailed reconstructions in real-time. It intr

Tianxiang Yang, Marco Volino, Armin Mustafa, Greg Maguire

We present an image-based rig inversion framework that leverages two modalities: RGB appearance and RGB-encoded normal maps. Each modality is processed by an independent Hiera transformer backbone, and the extracted features are fused to regress 102 rig parameters derived from the Facial Action Coding System (FACS). Experiments on synthetic and scanned datas

Kristýna Onderková, Ondřej Plátek, Zdeněk Kasner, Ondřej Dušek

Table-to-text generation (insight generation from tables) is a challenging task that requires precision in analyzing the data. In addition, the evaluation of existing benchmarks is affected by contamination of Large Language Model (LLM) training data as well as domain imbalance. We introduce FreshTab, an on-the-fly table-to-text benchmark generation from Wik

Henrik Podéus, Gustav Magnusson, Sasan Keshmiri, Kajsa Tunedal

When modeling complex, hierarchical, and time-dynamic systems, such as biological systems, good computational tools are essential. Current tools, while powerful, often lack comprehensive frameworks for modular model composition, hierarchical system building, and time-dependent input handling, particularly within the Python ecosystem. We present SUND (Simulat

Fabrizio Aguzzi, Martín Armoa, Santiago M. Rabazzi, César Pairetti

This work presents a modeling framework to represent the thermomechanical behavior of complex materials based on micromechanical dynamics. The framework is applied to nuclear fuel rod elements composed of Zircaloy-2 cladding tubes and spacer grids under typical Pressurized Water Reactor (PWR) conditions. Thermal expansion and thermal creep are incorporated t

Keiho Matsumoto

We construct a covariant realization functor, denoted \textsc{Solidm}, from the category of motives with modulus to the derived category of solid modules in the sense of Clausen--Scholze. For any smooth modulus pair (X, D), the dual of Solidm(X, D) recovers the Hodge realization of Kelly--Miyazaki for (X, D). Using Ren's pro-solid comparison theorem, we give

Zeeshan Kaleem, Muhammad Afaq, Chau Yuen, Octavia A. Dobre

This letter introduces a Graph-Condensed Quantum-Inspired Placement (GC-QAP) framework for reliability-driven trajectory optimization in Uncrewed Aerial Vehicle (UAV) assisted low-altitude wireless networks. The dense waypoint graph is condensed using probabilistic quantum-annealing to preserve interference-aware centroids while reducing the control state sp

Ethan K. Gordon, Bruke Baraki, Hien Bui, Michael Posa

General robot manipulation requires the handling of previously unseen objects. Learning a physically accurate model at test time can provide significant benefits in data efficiency, predictability, and reuse between tasks. Tactile sensing can compliment vision with its robustness to occlusion, but its temporal sparsity necessitates careful online exploration

Austin Barret, Meng Cheng Lau

The operation of humanoid robotics is an essential field of research with many practical and competitive applications. Many of these systems, however, do not invest heavily in developing a non-expert-centered graphical user interface (GUI) for operation. The focus of this research is to develop a scalable GUI that is tailored to be simple and intuitive so no

V. P. Kozhevnikov

Recently, in the VSX database, G. Murawski reported the discovery of an oscillation with a period of about 40 min in the probable cataclysmic variable 1RXS J014549.6+514314. To confirm the existence of this oscillation and precisely measure its period, I conducted extensive photometric observations of the object over 25 nights between 2022 and 2024. The tota

Chen Wang, Yansen Wang, Dongqi Han, Zilong Wang

Analyzing stereoelectroencephalography (SEEG) signals is critical for brain-computer interface (BCI) applications and neuroscience research, yet poses significant challenges due to the large number of input channels and their heterogeneous relevance. Traditional channel selection methods struggle to scale or provide meaningful interpretability for SEEG data.

Nicola Fabiano

The European Union's Artificial Intelligence Act (Regulation (EU) 2024/1689) establishes the world's first comprehensive regulatory framework for AI systems through a sophisticated ecosystem of interconnected subjects defined in Article 3. This paper provides a structured examination of the six main categories of actors - providers, deployers, authorized rep

Jiale Han, Austin Cheung, Yubai Wei, Zheng Yu

Knowledge is inherently time-sensitive and continuously evolves over time. Although current Retrieval-Augmented Generation (RAG) systems enrich LLMs with external knowledge, they largely ignore this temporal nature. This raises two challenges for RAG. First, current RAG methods lack effective time-aware representations. Same facts of different time are diffi

Timothée Herbeau, Leonid Pastur, Pascal Viot, Gleb Oshanin

We consider stochastic dynamics of a particle on a plane in presence of two noises and a confining parabolic potential - an analog of the experimentally-relevant Brownian Gyrator (BG) model. In contrast to the standard BG model, we suppose here that the time-evolution of the position components is driven not by Gaussian white-noises, but by two statistically

Jie Xu

Let $ X $ be an oriented, closed manifold with $ \dim X \geqslant 2 $. In this article, we give both Riemannian geoemtry and complex geometry results on (sub)manifolds of the type $ X \times \mathbb{C}^{k} $ or $ X \times \mathbb{R}^{k} $. For Riemannian geometry side, we show that if $ X \times \mathbb{C} = X \times \mathbb{R}^{2} $ admits a Riemannian metr

Chao Shi, Shenghao Jia, Jinhui Liu, Yong Zhang

We present HRM$^2$Avatar, a framework for creating high-fidelity avatars from monocular phone scans, which can be rendered and animated in real time on mobile devices. Monocular capture with smartphones provides a low-cost alternative to studio-grade multi-camera rigs, making avatar digitization accessible to non-expert users. Reconstructing high-fidelity av

Nader Nemati

Clinical 12-lead ECG classification remains difficult because of diverse recording conditions, overlapping pathologies, and pronounced label imbalance hinder generalization, while unconstrained augmentations risk distorting diagnostically critical morphology. In this study, Sinusoidal Time--Amplitude Resampling (STAR) is introduced as a beat-wise augmentatio

Pasin Buakhaw, Kun Kerdthaisong, Phuree Phenhiran, Pitikorn Khlaisamniang

The emergence of large language models (LLMs) has opened new opportunities for creating dynamic non-player characters (NPCs) in gaming environments, enabling both functional task execution and persona-consistent dialogue generation. In this paper, we (Tu_Character_lab) report our participation in the Commonsense Persona-Grounded Dialogue Challenge (CPDC) 202

Chandan Kumar Borah, Chandan Duarah

$\mu-\tau$ reflection symmetry is an attractive flavour symmetry in lepton mixing, which accommodates maximal values of atmospheric mixing angle ($\theta_{23}=\pi/4$) and Dirac CP phase ($\delta=\pi/2/3\pi/2$). Another significance of this symmetry is that it does not constrain $\theta_{13}$ to be zero. As the recent results from $T2K$ and $NO\nu A$ experime

Tian-Le Wang, Ze-An Zhao, Peng Wang, Sheng Zhang

Hamiltonian inverse engineering enables the design of protocols for specific quantum evolutions or target state preparation. Perfect state transfer (PST) and remote entanglement generation are notable examples, as they serve as key primitives in quantum information processing. However, Hamiltonians obtained through conventional methods often lack robustness

Andrew B. Kahng. Seokhyeong Kang, Seonghyeon Park, Dooseok Yoon

In advanced nodes, optimization of power, performance and area (PPA) has become highly complex and challenging. Machine learning (ML) and design-technology co-optimization (DTCO) provide promising mitigations, but face limitations due to a lack of diverse training data as well as long design flow turnaround times (TAT). We propose ArtNet, a novel artificial

Wen-Yi Zhang, Meng-Yun Mao, Qing-Min Hu, Xinzhi Zhao

We present a comprehensive theoretical framework for quantum criticality in the non-Hermitian detuned PXP model, and establish the complete phase diagram, which had remained elusive in previous studies. Starting from a numerically identified phase transition point, we construct an exact second-order phase transition boundary through a similarity transformati

Daniil Gurgurov, Tanja Baeumel, Josef van Genabith, Simon Ostermann

Large language models (LLMs) exhibit substantial performance disparities across languages, particularly between high- and low-resource settings. We propose a framework for improving performance in underrepresented languages while preserving general-purpose capabilities via targeted fine-tuning of sparse, language-associated subnetworks. Our approach identifi

Marie-Camille Delarue

The Higman--Thompson groups $V_{n,r}$ consist of piecewise linear automorphisms of $r$ intervals where cut points and slopes are $n$-adic. Szymik and Wahl prove homological stability for this family of groups as $r$ increases, and compute the stable homology to be that of the infinite loop space of the Moore spectrum. We give a new proof of this result using

Saeed Samadi, Łukasz Cywiński, Jan A. Krzywda

Properties of quantum dot based spin qubits have significant inter-device variability due to unavoidable presence of various types of disorder in semiconductor nanostructures. A significant source of this variability is charge disorder at the semiconductor-oxide interface, which causes unpredictable, yet, as we show here, correlated fluctuations in such esse

Kazuya Shinjo, Kazuhiro Seki, Seiji Yunoki

Floquet many-body phases such as discrete time crystals (DTCs) are typically fragile to imperfections, and stabilizing them on noisy quantum hardware remains a central challenge in nonequilibrium quantum physics. Here, we use IBM Eagle and Heron superconducting processors to implement Floquet dynamics of a kicked Ising model on two-dimensional Kagome lattice

Mousomi Bhakta, Anup Biswas, Roberta Filippucci

In this paper, we establish several Liouville-type theorems for a class of nonhomogenenous quasilinear inequalities. In the first part, we prove various Liouville results associated with nonnegative solutions to \begin{equation*}\tag{$P_s$} -\Delta_p u-\Delta_q u\geq u^{s-1} \, \text{ in }\, \Omega, \end{equation*} where $1<q<p$, $s>1$ and $\Omega$ is any ex

Han Fu, Sigrid Eldh, Kristian Wiklund, Andreas Ermedahl

The co-development of hardware and software in industrial embedded systems frequently leads to compilation errors during continuous integration (CI). Automated repair of such failures is promising, but existing techniques rely on test cases, which are not available for non-compilable code. We employ an automated repair approach for compilation errors driven

Franciele M. da Silva, Adamu Issifu, Luis C. N. Santos, Tobias Frederico

The structural evolution of rotating protoneutron stars encodes essential information about their observable signatures, while microscopic properties provide complementary knowledge to advance observational investigations. Using a relativistic mean-field model with density-dependent couplings that account for temperature and particle composition, we investig

Yingheng Li, Xulong Tang, Paul Hovland, Ji Liu

Hamiltonian simulation is a key quantum algorithm for modeling complex systems. To implement a Hamiltonian simulation, it is typically decomposed into a list of Pauli strings, each corresponds to an RZ rotation gate with many Clifford gates. These RZ gates are generally synthesized into a sequence of Clifford and T gates in fault-tolerant quantum computers,

Geoffrey R. Grimmett, Mark Holmes

A Markov chain $X^i$ on a finite state space $S$ has transition matrix $P$ and initial state $i$. We may run the chains $(X^i: i\in S)$ in parallel, while insisting that any two such chains coalesce whenever they are simultaneously at the same state. There are $|S|$ trajectories which evolve separately, but not necessarily independently, prior to coalescence

Siying Liu, Shisheng Zhang, Indu Bala

Large language models (LLMs) are increasingly applied in biomedical domains, yet their reliability in drug-safety prediction remains underexplored. In this work, we investigate whether LLMs incorporate socio-demographic information into adverse event (AE) predictions, despite such attributes being clinically irrelevant. Using structured data from the United

Tolga Altinoluk, Guillaume Beuf, Swaleha Mulani

We compute the next-to-eikonal (NEik) power corrections to inclusive deep inelastic scattering (DIS) and semi-inclusive deep inelastic scattering (SIDIS) at low $x$ beyond dipole factorization, which represent the eikonal result. The analysis is restricted to contributions arising from t-channel quark exchanges, thereby probing the quark background field of

Ivan Dubrovsky, Anastasia Orlova, Illarion Iov, Nina Gubina

Benchmarking outcomes increasingly govern trust, selection, and deployment of LLMs, yet these evaluations remain vulnerable to semantically equivalent adversarial perturbations. Prior work on adversarial robustness in NLP has emphasized text attacks that affect many models equally, leaving open the question of whether it is possible to selectively degrade or

Ziwen Zhong

The ETAS models are currently the most popular in the field of earthquake forecasting. The MCMC method is time-consuming and limited by parameter correlation while bringing parameter uncertainty. The INLA-based method "inlabru" solves these problems and performs better at Bayesian inference. The report introduces the composition of the ETAS model, then provi

Di Fan, Changming Ke, Shi Liu

Symmetry considerations suggest that moire superlattices formed by twisted two-dimensional materials should preserve overall inversion symmetry. However, experiments consistently report robust ferroelectricity in systems such as twisted bilayer h-BN, posing a fundamental discrepancy between theory and experiment regarding its microscopic origin. Here, using

Omayma Moussadek, Riccardo Salami, Simone Calderara

Federated continual learning (FCL) enables models to learn new tasks across multiple distributed clients, protecting privacy and without forgetting previously acquired knowledge. However, current methods face challenges balancing performance, privacy preservation, and communication efficiency. We introduce a Distributed Online LoRA for Federated INcremental

Su Yang, Shaoxuan Chen, Wei Zhu, Panayotis G. Kevrekidis

In this paper, we revisit the investigation of solitary-wave interactions in the nonlinear Schr\"odinger model, both in the presence and absence of a parabolic trapping potential. While approximate dynamics, based on variational or similar methods, governed by a system of ordinary differential equations (ODEs) for both bright and dark-soliton interactions ha

Marie-Camille Delarue

The homology of the symmetric groups stabilizes, and the Barratt--Priddy--Quillen theorem identifies the stable homology with that of the infinite loop space underlying the sphere spectrum. We formulate a new proof inspired by Galatius, Kupers, and Randal-Williams using scanning methods. We build a topological model for the monoid formed by all the symmetric

Peng Di, Faqiang Chen, Xiao Bai, Hongjun Yang

The escalating complexity of modern software imposes an unsustainable operational burden on Site Reliability Engineering (SRE) teams, demanding AI-driven automation that can emulate expert diagnostic reasoning. Existing solutions, from traditional AI methods to general-purpose multi-agent systems, fall short: they either lack deep causal reasoning or are not

Rahul Vaze, Sumiran Mishra

In this paper, we broaden the horizon of online convex optimization (OCO), and consider multi-objective OCO, where there are $K$ distinct loss function sequences, and an algorithm has to choose its action at time $t$, before the $K$ loss functions at time $t$ are revealed. To capture the tradeoff between tracking the $K$ different sequences, we consider the

Vahab Knauf Narouie, Jorge-Humberto Urrea-Quintero, Fehmi Cirak, Henning Wessels

Recently, unsupervised constitutive model discovery has gained attention through frameworks based on the Virtual Fields Method (VFM), most prominently the EUCLID approach. However, the performance of VFM-based approaches, including EUCLID, is affected by measurement noise and data sparsity, which are unavoidable in practice. The statistical finite element me

Ruitao Feng, Bixi Zhang, Sheng Liang, Zheng Yuan

Aligning pretrained audio encoders and Large Language Models (LLMs) offers a promising, parameter-efficient path to building powerful multimodal agents. However, existing methods often require costly full-model finetuning or rely on static adapters that may lack expressive power. Drawing inspiration from the Platonic Representation Hypothesis, we introduce S

Zenghuang Fu, Xiaofeng Han, Mingda Jia, Jin ming Yang

Multi-object tracking (MOT) from unmanned aerial vehicles (UAVs) presents unique challenges due to unpredictable object motion, frequent occlusions, and limited appearance cues inherent to aerial viewpoints. These issues are further exacerbated by abrupt UAV movements, leading to unreliable trajectory estimation and identity switches. Conventional motion mod

David Freire-Obregón, José Salas-Cáceres, Javier Lorenzo-Navarro, Oliverio J. Santana

Facial expression recognition (FER) must remain robust under both cultural variation and perceptually degraded visual conditions, yet most existing evaluations assume homogeneous data and high-quality imagery. We introduce an agent-based, streaming benchmark that reveals how cross-cultural composition and progressive blurring interact to shape face recogniti

Aromal P, Unnati Kashyap, Manoneeta Chakraborty, Sudip Bhattacharyya

We present a detailed analysis of the Type-I (thermonuclear) X-ray bursts and eclipses observed from the neutron star low-mass X-ray binary (LMXB) EXO 0748--676 with AstroSat during the second known outburst of the source following a 16-year-long quiescence period. We detect three thermonuclear X-ray bursts, with two displaying simultaneous coverage in the s

Tatsuhiko Shirai

We investigate a quasi-adiabatic thermal process for preparing finite-temperature ensembles in the thermodynamic limit. The process gradually transforms a thermal ensemble of a noninteracting system into that of an interacting system of interest over a finite operation time, with the temperature controlled by parameters associated with the entropy of the ini

Sahil, Swarup Kumar Giri, Sohail

Characterization of quantum measurements and dynamical processes is typically performed using pure state preparations. However, in realistic experimental settings, the preparation of pure states is often infeasible due to noise and system constraints. In this work, we present a unified framework that enables the direct and complete characterization of an unk

Mauricio Cataldo, Norman Cruz

The paper entitled Unimodular Gravity Traversable Wormholes by Agrawal et al. examined the properties of barotropic wormholes without tidal forces within the framework of Unimodular Gravity. Our analysis demonstrates that their conclusion regarding the possibility of sustaining such wormhole configurations with ordinary matter is not entirely accurate. We es

Wentao Guo, Wenzeng Zhang

This paper presents the Hoecken-D Hand, an underactuated robotic gripper that combines a modified Hoecken linkage with a differential spring mechanism to achieve both linear parallel pinching and a mid-stroke transition to adaptive envelope. The original Hoecken linkage is reconfigured by replacing one member with differential links, preserving straight-line

Robert West, Ashton Anderson, Ece Kamar, Eric Horvitz

As language models continue to rapidly improve, we can expect their actions and reasoning to become difficult or impossible for weaker agents and humans to follow, undermining interpretability and oversight. With an eye on long-term futures, we pursue methods that encourage models to produce solutions that remain intelligible to weaker collaborators. We form

Márton Benedek, Balázs R. Sziklai

Students at all levels of education are increasingly relying on generative artificial intelligence (AI) tools to complete assignments and achieve higher exam scores. However, it remains unclear how this reliance affects their motivation, their genuine understanding of the material, and the extent to which it substitutes for the process of knowledge acquisiti

Ivan A. Bocanegra-Garay, Luis M. Nieto

The supersymmetric structure of a generalized non-Hermitian driven two-level system is demonstrated. A unitary rotation turns the Hamiltonian into a more convenient form. After decoupling a set of differential equations, the supersymmetric structure of the problem can be unequivocally ap- appreciated. Performing a spectral analysis of an auxiliary stationary

Patrícia Gonçalves, Maria Chiara Ricciuti, Gunter Schütz

We prove a generalised second-order Boltzmann-Gibbs principle for conservative interacting particle systems on a lattice whose stationary measures are not of product type and not invariant under particle jumps. The result, which requires neither a spectral gap bound nor an equivalence of ensembles, extends the classical framework to settings with correlated

Di Ben, Sheng-Qi Zhang

We study hidden- and open-strange pentaquark configurations in the hadronic molecular picture with QCD sum rules. Starting from the baryon octet combined with an $s\bar{s}$ pair, we construct 21 interpolating currents with $J=1/2$ and $3/2$. In the analysis, contributions up to dimension 11 are included in the operator product expansion, and both parity-proj

Anirban Mondal, Kwang Jin Lee, Seungmin Lee, Oui Jin Oh

Two dimensional Ruddlesden Popper (2D) RP hybrid perovskites exhibit substantially higher chemical and structural stability than their three dimensional (3D) counterparts, positioning them as promising candidates for next generation optoelectronics. While quasiparticle dynamics in 3D perovskites are well studied, their 2D analogues remain comparatively under

Ruiqi Ye, Mikel Luján

Feature detection is a common yet time-consuming module in Simultaneous Localization and Mapping (SLAM) implementations, which are increasingly deployed on power-constrained platforms, such as drones. Graphics Processing Units (GPUs) have been a popular accelerator for computer vision in general, and feature detection and SLAM in particular. On the other han

Muhammad Amer Khan, Lili Hu, Shubin Chen, Yongchun Xu

Corrosion mechanism of minerals and glass is a critical study domain in geology and materials science, vital for comprehending material durability under various environmental conditions. Despite decades of extensive study, a core aspect of these mechanisms - specifically, the formation of amorphous alteration layers upon exposure to aqueous environments - re

Guorui Zhu, Joel Bierman, Jianfeng Lu, Yingzhou Li

We propose a state-specific orbital optimization scheme for improving the accuracy of excited states of the electronic structure Hamiltonian for the use on near-term quantum computers, which can be combined with any overlap-based excited-state quantum eigensolver. We derived the gradient of the overlap term between different states generated by different orb

Avihay Cohen

Large Language Model (LLM) based agents integrated into web browsers (often called agentic AI browsers) offer powerful automation of web tasks. However, they are vulnerable to indirect prompt injection attacks, where malicious instructions hidden in a webpage deceive the agent into unwanted actions. These attacks can bypass traditional web security boundarie

Martin Licht, Sara Ketabi, Farzad Khalvati

Topic modeling is a useful tool for analyzing large corpora of written documents, particularly academic papers. Despite a wide variety of proposed topic modeling techniques, these techniques do not perform well when applied to medical texts. This can be due to the low number of documents available for some topics in the healthcare domain. In this paper, we p

Trond Hjerpekjøn Haug, Timo Hillmann, Anton Frisk Kockum, Raphaël Van Laer

Modular architectures are a promising approach to scaling quantum computers to fault tolerance. Small, low-noise quantum processors connected through relatively noisy quantum links are capable of fault-tolerant operation as long as the noise can be confined to the interface. Finding protocols that implement the quantum links between modules as efficiently as

Maximilian Weiherer, Antonia von Riedheim, Vanessa Brébant, Bernhard Egger

We present a neural parametric 3D breast shape model and, based on this model, introduce a low-cost and accessible 3D surface reconstruction pipeline capable of recovering accurate breast geometry from a monocular RGB video. In contrast to widely used, commercially available yet prohibitively expensive 3D breast scanning solutions and existing low-cost alter

Mubaris Nadeem, Johannes Zenkert, Christian Weber, Madjid Fathi

This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals.

Alexander Ponticello, Filipo Sharevski, Simon Anell, Katharina Krombholz

Managing passwords securely and conveniently is still an open problem for many users. Existing research has examined users' password management strategies and identified pain points, such as security concerns, leading to insecure practices. We investigate how Blind and Low-Vision (BLV) users tackle this problem and how password managers can assist them. This

Daichi Mukunoki, Katsuhisa Ozaki

To obtain accurate results in numerical computation, high-precision arithmetic is a straightforward approach. However, most processors lack hardware support for floating-point formats beyond double precision (FP64). Double-word arithmetic (Dekker 1971) extends precision by using standard floating-point operations to represent numbers with twice the mantissa

Shuo Xing, Junyuan Hong, Yifan Wang, Runjin Chen

We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language models (LLMs). To unveil junk effects, we designed a novel controlled experiment on real Twitter/X corpora, by constructing junk and reverse-controlled datasets via two orthogonal operationalizations: M1 (engagement degree

Wentao Guo, Yizhou Wang, Wenzeng Zhang

This paper presents a novel underactuated adaptive robotic hand, Hockens-A Hand, which integrates the Hoeckens mechanism, a double-parallelogram linkage, and a specialized four-bar linkage to achieve three adaptive grasping modes: parallel pinching, asymmetric scooping, and enveloping grasping. Hockens-A Hand requires only a single linear actuator, leveragin

Thibault Geoffroy, Gauthier Gerspacher, Lionel Prevost

Incremental learning is a complex process due to potential catastrophic forgetting of old tasks when learning new ones. This is mainly due to transient features that do not fit from task to task. In this paper, we focus on complex emotion recognition. First, we learn basic emotions and then, incrementally, like humans, complex emotions. We show that Action U

Yizhou Guo, Houdun Zeng, Junjie Wei, Hao Zhou

Following its launch on 2024 January 9, the Einstein Probe (EP) telescope has detected hundreds of fast X-ray transients (FXTs), yet their physical origins remain elusive. Understanding their luminosity function and formation rate is crucial for elucidating their nature. Recently, the EP team has provided the latest catalog of EP-detected FXTs. Based on this

Dushyantha A Basnayaka

In this paper, we describe the necessary procedures for accurately simulating digital wireless communication systems operating in the mediumband, aimed at both beginners and experts. In the research literature, digital wireless communication systems are typically simulated in the discrete-time complex baseband domain, where pulse shaping, upconversion, mixin

Peng Liu, Tanweer Sohail, Xiaoyu Jia

The spinor tensor $\epsilon_{AB}$ has a special property that its elements can be formulated into an algebraic expression of the indices. All the totally anti-symmetric tensors in Minkowski space are expressed by $\epsilon_{AB}$. By using the property, we give a simple proof of the total anti-symmetry for the volume spinor tensor.

Zixuan Jia, Lufeng Zhang, Qingzhuo Duan, Zenghui Fan

Inspired by the recent experimental progress in pyrochlore derivative RE$_3$Sb$_3$A$_2$O$_{14}$ (A = Mg, Zn), we investigate the Hubbard model on the kagome lattice with an additional hopping $t'/t$, which enables continuous interpolation between the kagome and triangular lattices by using determinant quantum Monte Carlo simulations. We find that increasing

Ross C. Schofield, Daniel Lim, Nathan R. Gemmell, Edmund Clarke

Here we report the measurement of thermal photon statistics from a semiconductor photon Bose-Einstein condensate operating just above the condensation threshold. We identify a regime where coherent, single mode emission occurs while still demonstrating significant photon bunching. Taking advantage of the photon bunching, along with the continuous-wave operat

Loïs Ecoffet, Veronika Rehn-Sonigo, Jean-François Couchot, Catuscia Palamidessi

Analytical SQL queries are essential for extracting insights from relational databases but concurrently introduce significant privacy risks by potentially exposing sensitive information. To mitigate these risks, numerous query sanitization systems have been developed, employing diverse approaches that create a complex landscape for both researchers and pract

Devansh Mathur, Juliette Becker

The population of hot Jupiters with adjacent planetary companions is small but growing, and inner companions appear to be a nearly ubiquitous outcome within this subset of the exoplanet census. While most hot Jupiters are believed to form via tidal migration, the presence of adjacent companions is not easily explained by this formation mechanism, requiring c

Hayato Arai

We study autoequivalences and stability conditions on the derived category of coherent sheaves on a singular surface $X$ which arises as an open subvariety of a type III Kulikov degeneration of K3 surfaces. The surface $X$ consists of four irreducible components, one of which is $\mathbb{P}^2$, and the others are non-compact rational surfaces. Using a compar

Jishu Adhikary, Raju Maiti

Rainfall forecasting plays a critical role in climate adaptation, agriculture, and water resource management. This study develops long-term forecasts of monthly rainfall across 19 districts of West Bengal using a century-scale dataset spanning 1900-2019. Daily rainfall records are aggregated into monthly series, resulting in 120 years of observations for eac

Sean Li, Raanan Schul

We give the following characterization of rectifiable metric spaces. A metric space with positive lower Hausdorff density is rectifiable if and only if, for any subset $F$ and $f:F\to Y$, a Lipschitz map into a metric space with positive measure image (of the same dimension), there exists a positive measure subset $A\subset F$ so that $f$ is biLipschitz on $

William Flanagan, Mukunda Das, Rajitha Ramanayake, Swanuja Maslekar

As Generative Artificial Intelligence is adopted across the financial services industry, a significant barrier to adoption and usage is measuring model performance. Historical machine learning metrics can oftentimes fail to generalize to GenAI workloads and are often supplemented using Subject Matter Expert (SME) Evaluation. Even in this combination, many pr

Jia-jun Ma, Shilin Yu

Weak unipotence of primitive ideals is a crucial property in the study of unitary representations of reductive groups. We establish a sufficient condition, referred to as mild unipotence, which guarantees weak unipotence and is more accessible in practice. We establish mild unipotence for both the $q$-unipotent ideals defined by McGovern and unipotent ideals

Siddhartha Ganguly, Shubham Gupta, Debasish Chatterjee

We establish an algorithm to learn feedback maps from data for a class of robust model predictive control (MPC) problems. The algorithm accounts for the approximation errors due to the learning directly at the synthesis stage, ensuring recursive feasibility by construction. The optimal control problem consists of a linear noisy dynamical system, a quadratic

Timo Thun, Rory Conlin, Dario Panici, Daniel Böckenhoff

Numerical computation of the ideal Magnetohydrodynamic (MHD) equilibrium magnetic field is at the base of stellarator optimisation and provides the starting point for solving more sophisticated Partial Differential Equations (PDEs) like transport or turbulence models. Conventional approaches solve for a single stationary point of the ideal MHD equations, whi

Mirco Castoldi

Objective: Quantitative real-time PCR is widely used for gene expression analysis, yet inconsistencies in data storage and reporting limit reproducibility. While MIQE guidelines define the minimal information required for publication, they do not specify structured digital storage formats compatible with long-term reanalysis. This work presents qLOOK (qPCR-L

Alice Marraffa, Renate Krause, Valerio Mante, George Haller

Artificial Recurrent Neural Networks (RNNs) are widely used in neuroscience to model the collective activity of neurons during behavioral tasks. The high dimensionality of their parameter and activity spaces, however, often make it challenging to infer and interpret the fundamental features of their dynamics. In this study, we employ recent nonlinear dynamic

Shaul Rosner, Marc Schröder, Laura Vargas Koch

We study a dynamic routing game motivated by traffic flows. The base model for an edge is the Vickrey bottleneck model. That is, edges are equipped with a free flow transit time and a capacity. When the inflow into an edge exceeds its capacity, a queue forms and the following particles experience a waiting time. In this paper, we enhance the model by introdu

Zixu Feng, Qinglin Tang

In this article, we propose a unified framework for preconditioned Riemannian gradient (P-RG) methods to minimize Gross-Pitaevskii (GP) energy functionals with rotation on a Riemannian manifold. This framework enables comprehensive analysis of existing projected Sobolev gradient methods and facilitates the construction of highly efficient P-RG algorithms. Un

Tiancheng Gu, Kaicheng Yang, Kaichen Zhang, Xiang An

Universal multimodal embedding models are foundational to various tasks. Existing approaches typically employ in-batch negative mining by measuring the similarity of query-candidate pairs. However, these methods often struggle to capture subtle semantic differences among candidates and lack diversity in negative samples. Moreover, the embeddings exhibit limi

Andreas C. Makrides, Adam Suski, Elina Spyrou

The transition to a fully decarbonised electricity system depends on integrating new technologies that ensure reliability alongside sustainability. However, missing risk markets hinder investment in reliability-enhancing technologies by exposing investors to revenue uncertainty. This study provides the first quantitative assessment of how missing risk market

Karin Koch, Joachim Landers, Damian Günzing, Hajnalka Nádasi

Ferronematic phases, composed of liquid crystals doped with magnetic nanoparticles, exhibit unique magnetomechanical coupling effects that are of interest for responsive materials. In this study, we investigate the influence of spindle-shaped {\alpha}-Fe_2O_3 nanoparticles functionalized with a mesogen-decorated polymer brush on the phase behavior and field-

Yulian Wu, Rushil Thareja, Praneeth Vepakomma, Francesco Orabona

In this paper, we study the offline and online settings of reinforcement learning from human feedback (RLHF) with KL-regularization -- a widely used objective function in large language model alignment -- under the $\epsilon$ local differential privacy ($\epsilon$-LDP) model on the label of the human preference. In the offline setting, we design an algorithm

David V. Svintradze

We present a differential geometric formulation of the Poincare problem using the calculus of moving surfaces (CMS). In this framework, an n dimensional compact hypersurface evolves under a velocity field that couples motion to the extrinsic curvature tensor while preserving topology through smooth diffeomorphic flow. A variational energy principle identifie