December 2024 arXiv papers — page 141

George Barmpalias, Mingyang Wang, Xiaoyan Zhang

We study the complexity of deterministic and probabilistic inversions of partial computable functions on the reals.

Hou-Wan Long, Hongyang Li, Wei Cai

The rapid growth of memecoins within the Web3 ecosystem, driven by platforms like Pump.fun, has made it easier for anyone to create tokens. However, this democratization has also led to an explosion of low-quality or bot-generated projects, often motivated by short-term financial gain. This overwhelming influx of speculative tokens creates a challenge in dis

Jiahua Xu, Dawei Zhou, Lei Hu, Jianfeng Guo

Motion artifacts present in magnetic resonance imaging (MRI) can seriously interfere with clinical diagnosis. Removing motion artifacts is a straightforward solution and has been extensively studied. However, paired data are still heavily relied on in recent works and the perturbations in k-space (frequency domain) are not well considered, which limits their

Jianzong Wu, Chao Tang, Jingbo Wang, Yanhong Zeng

Story visualization, the task of creating visual narratives from textual descriptions, has seen progress with text-to-image generation models. However, these models often lack effective control over character appearances and interactions, particularly in multi-character scenes. To address these limitations, we propose a new task: \textbf{customized manga gen

Frederik Zumegen, Christoph Studer

We propose a software-defined testbed for Wi-Fi channel-state information (CSI) acquisition. This testbed features distributed software-defined radios (SDRs) and a custom IEEE 802.11a software stack that enables the passive collection of CSI data from commercial off-the-shelf (COTS) devices that connect to an existing Wi-Fi network. Unlike commodity Wi-Fi sn

Zheng Cao, Helyette Geman

This article introduces a Hype-Adjusted Probability Measure in the context of a new Natural Language Processing (NLP) approach for stock return and volatility forecasting. A novel sentiment score equation is proposed to represent the impact of intraday news on forecasting next-period stock return and volatility for selected U.S. semiconductor tickers, a very

Moritz Piening, Matthias Chung

Generative autoencoders learn compact latent representations of data distributions through jointly optimized encoder--decoder pairs. In particular, Wasserstein autoencoders (WAEs) minimize a relaxed optimal transport (OT) objective, where similarity between distributions is measured through a cost-minimizing joint distribution (OT coupling). Beyond distribut

Pablo Zivic, Hernan Vazquez, Jorge Sanchez

Modeling user preferences has been mainly addressed by looking at users' interaction history with the different elements available in the system. Tailoring content to individual preferences based on historical data is the main goal of sequential recommendation. The nature of the problem, as well as the good performance observed across various domains, has mo

Quoc-Bao Nguyen-Le, Thanh-Huy Le-Nguyen

Current video retrieval systems, especially those used in competitions, primarily focus on querying individual keyframes or images rather than encoding an entire clip or video segment. However, queries often describe an action or event over a series of frames, not a specific image. This results in insufficient information when analyzing a single frame, leadi

Sangwon Jo, Hoon Lee, Seok-Hwan Park

To ensure coherent signal processing across distributed Access Points (APs) in Cell-Free Massive Multiple-Input Multiple-Output (CF-mMIMO) systems, a fronthaul connection between the APs and a Central Processor (CP) is imperative. We consider a fronthaul network employing parallel radio stripes. In this system, APs are grouped into multiple segments where AP

Weihao Liu, Igor V. Sokolov, Lulu Zhao, Tamas I. Gombosi

Solar energetic particles (SEPs) can pose hazardous radiation risks to both humans and spacecraft electronics in space. Numerical modeling based on first principles offers valuable insights into the underlying physics of SEPs and provides synthetic observables for SEPs at any time and location in the inner heliosphere. In this work, we present a numerical sc

Alexander Panferov, Grigory Beskin, Sergey Karpov, Olga Maryeva

Quasi-periodic pulsations (QPPs) of Sun and stars are challenging for stellar flare models. The white light stellar QPPs in the periodicity region of tens of second are unexplored yet. On the basis of observations with the 6-m telescope BTA in U-band of flaring dM-stars EV Lac, Wolf 359, Wolf 424, V577 Mon and UV Ceti we found 13 new QPPs. This composes 30%

Xinyue Liu, Jianyuan Wang, Biao Leng, Shuo Zhang

Knowledge Distillation (KD) is a promising approach for unsupervised Anomaly Detection (AD). However, the student network's over-generalization often diminishes the crucial representation differences between teacher and student in anomalous regions, leading to detection failures. To addresses this problem, the widely accepted Reverse Distillation (RD) paradi

Mitchell Chiew, Brent Harrison, Sergii Strelchuk

We consider two approaches to designing fermion-qubit mappings: (1) ternary tree transformations, which use Pauli representations of the Majorana operators that correspond to root-to-leaf paths of a tree graph and (2) linear encodings of the Fock basis, such as the Jordan-Wigner and Bravyi-Kitaev transformations, which store linear binary transformations of

P. Boyvalenkov, P. Dragnev

We prove the universal optimality of four remarkable spherical 11-designs in 48 dimensions either among all antipodal codes, or all spherical 3-designs, whose inner-products avoid the set $T_1=(-1/3,-1/6) \cup (1/6,1/3)$. We also prove the universal optimality of these configurations among all codes whose distance-avoiding set is $T_2=(-1/2,-1/3) \cup (1/3,1

Huan Liu, Ilja Makkonen, Calliope Bazioti, Junlei Zhao

Ultrawide bandgap semiconductor gallium oxide (Ga2O3) and its polymorphs have recently attracted increasing attention across physics, materials science, and electronics communities. In particular, the self-organized formation of the beta/gamma-Ga2O3 double polymorph structures was demonstrated recently [A. Azarov et al., Nat. Commun. 14, 4855 (2023)], paving

Shuai Zhou, Dayong Ye, Tianqing Zhu, Wanlei Zhou

Model inversion attacks pose a significant privacy threat to machine learning models by reconstructing sensitive data from their outputs. While various defenses have been proposed to counteract these attacks, they often come at the cost of the classifier's utility, thus creating a challenging trade-off between privacy protection and model utility. Moreover,

Erwan Célanie, Laurent Delisle, Amine Jaouadi

This study investigates the formation and dynamics of solitons in Bose-Einstein condensates (BECs) within dark traps generated by two crossed Laguerre-Gaussian (LG) beams with varying azimuthal indices $\ell$. As the index $\ell$ increases, the potential transitions from a harmonic trap when $\ell = 1$ to a square-well potential for larger values of $\ell$.

Youchao Zhou, Heyan Huang, Zhijing Wu, Yuhang Liu

Long-form document matching aims to judge the relevance between two documents and has been applied to various scenarios. Most existing works utilize hierarchical or long context models to process documents, which achieve coarse understanding but may ignore details. Some researchers construct a document view with similar sentences about aligned document subto

Mikhail Egorov

The approach of direct integration of the three-dimensional Faddeev equations with respect to the breakup T-matrix in momentum space for three bodies of different masses is presented. The Faddeev equations are written out explicitly without the requirement for symmetry or antisymmetry of two-body t matrices, taking into account the difference in the masses o

N. Glebov, M. Masharin, A. Yulin, A. Mikhin

Optical nonlinearities are crucial for advanced photonic technologies since they allow photons to be managed by photons. Exciton-polaritons resulting from strong light-matter coupling are hybrid in nature: they combine small mass and high coherence of photons with strong nonlinearity enabled by excitons, making them ideal for ultrafast all-optical manipulati

Clément Aubert, Cinzia Di Giusto, Simon Fowler, Violet Ka I Pun

This volume contains the proceedings of ICE'24, the 17th Interaction and Concurrency Experience, which was held on Friday 21th June 2024 at the University of Groningen in Groningen, The Netherlands, as a satellite workshop of DisCoTec 2024. The ICE workshop series features a distinguishing review and selection procedure: PC members are encouraged to interact

Eunsu Kim, Juyoung Suk, Seungone Kim, Niklas Muennighoff

We introduce LLM-as-an-Interviewer, a novel paradigm for evaluating large language models (LLMs). This approach leverages multi-turn interactions where the LLM interviewer actively provides feedback on responses and poses follow-up questions to the evaluated LLM. At the start of the interview, the LLM interviewer dynamically modifies datasets to generate ini

Hengjia Zhang, Xiaoping Xu

Associated varieties are geometric objects appearing in infinite-dimensional representations of semisimple Lie algebras (groups). By applying Fourier transformations to the natural orthogonal oscillator representations of special linear Lie algebras, Luo and the second author (2013) obtained a big family of infinite-dimensional irreducible representations of

Dietmar Gallistl, Ngoc Tien Tran

This work introduces finite element methods for a class of elliptic fully nonlinear partial differential equations. They are based on a minimal residual principle that builds upon the Alexandrov--Bakelman--Pucci estimate. Under rather general structural assumptions on the operator, convergence of $C^1$ conforming and discontinuous Galerkin methods is proven

Adam Kollarčík, Zdeněk Hanzálek

This paper addresses the trajectory planning problem for automated vehicle on-ramp highway merging. To tackle this challenge, we extend our previous work on trajectory planning at unsignalized intersections using Partially Observable Markov Decision Processes (POMDPs). The method utilizes the Adaptive Belief Tree (ABT) algorithm, an approximate sampling-base

Rémi Danain-Bertoncini

We propose in this article the study of the deformations of a Calabi-Yau type foliations $\mathcal{F}$. For three different types of deformations (unfoldings, holomorphic, transversally holomorphic) there exist Kuranishi spaces $K^f,K^h,K^{tr}$ parametrizing the corresponding families of deformations. We show that $K^f$ is smooth, and that we can obtain $K^h

Simon Kristoffersson Lind, Rudolph Triebel, Volker Krüger

Modern robotic perception is highly dependent on neural networks. It is well known that neural network-based perception can be unreliable in real-world deployment, especially in difficult imaging conditions. Out-of-distribution detection is commonly proposed as a solution for ensuring reliability in real-world deployment. Previous work has shown that normali

Julia Kotovich, Manuel Oriol

ChatGPT3 is a chat engine that fulfils the promises of an AI-based chat engine: users can ask a question (prompt) and it answers in a reasonable manner. The coding-related skills of ChatGPT are especially impressive: informal testing shows that it is difficult to find simple questions that ChatGPT3 does not know how to answer properly. Some students are cert

Ke Ding, Hao-Ran Zhang, Bai-Ting Liu, Shuo Yang

We generalize the topological response theory to detect the boundary anomalies of linear subsystem symmetries. This approach allows us to distinguish different subsystem symmetry-protected topological (SSPT) phases and uncover new ones. We focus on the cases where the mixed anomaly exists within the adjacent subsystems. Using numerical simulations, we demons

N. M. Belousov, G. A. Sarkissian, V. P. Spiridonov

We consider different pentagon identities realized by the hyperbolic hypergeometric functions and investigate their degenerations to the level of complex hypergeometric functions. In particular, we show that one of the degenerations yields the complex binomial theorem which coincides with the Fourier transformation of the complex analogue of the Euler beta i

Hai Li, Longyu Wu, Baocheng Zhu

In this paper, we consider an extremal problem associated with the solution to a boundary value problem. Our main focus is on establishing a variational formula for a functional related to the $\mathbf{p}$-harmonic measure, from which a new measure is derived. This further motivates us to study the Minkowski problem for this new measure. As a main result, we

Manon P. Bart, Sita Dawanse, Nicholas J. Savino, Viet Tran

Spatial modes are a promising candidate for encoding information for classical and quantum optical communication due to their potential high information capacity. Unfortunately, compensation of the wavefront upon propagation through the atmosphere is necessary to benefit from advantages spatial modes offer. In this work, we leverage the success of convolutio

Yiqian Yang, Xihua Zhu, Fan Zhang

Adversarial training with Normalizing Flow (NF) models is an emerging research area aimed at improving model robustness through adversarial samples. In this study, we focus on applying adversarial training to NF models for gravitational wave parameter estimation. We propose an adaptive epsilon method for Fast Gradient Sign Method (FGSM) adversarial training,

Riccardo Scotti, Gabriella Bettonte, Antonio Costantini, Sara Marzella

This work presents a hybrid quantum-classical algorithm to perform clustering aggregation, designed for neutral-atoms quantum computers and quantum annealers. Clustering aggregation is a technique that mitigates the weaknesses of clustering algorithms, an important class of data science methods for partitioning datasets, and is widely employed in many real-w

Enzo Zanchini, Francesco Zanchini

The design and the simulation of a borehole-heat-exchanger (BHE) field is usually performed by simplified methods that yield either an overestimation or an underestimation of the thermal response. The methods employing the assumption of a uniform heat rate per unit BHE length overestimate the thermal response, while those employing the assumption of a unifor

Pierluigi Mansueto, Mihai Dragusanu, Anjum Saeed, Monica Malvezzi

Sim-to-real transfer remains a significant challenge in soft robotics due to the unpredictability introduced by common manufacturing processes such as 3D printing and molding. These processes often result in deviations from simulated designs, requiring multiple prototypes before achieving a functional system. In this study, we propose a novel methodology to

Sai Xu, Yanan Du, Gaojie Chen, Rahim Tafazolli

This paper proposes a graph neural network (GNN)-based space multiple-input multiple-output (MIMO) framework, named GSM, for direct-to-cell communications, aiming to achieve distributed coordinated beamforming for low Earth orbit (LEO) satellites. Firstly, a system model for LEO multi-satellite communications is established, where multiple LEO satellites col

Muhammed Shafeeque, Malay K. Nandy

In this paper, we focus upon the behaviour of spacetime of charged black holes described by Eddington-inspired Born-Infeld (EiBI) gravity. With a static and spherically symmetric metric, we solve the ensuing field equations obtained from the EiBI-Maxwell action in the Palatini formalism. Consequently we carry out, for the first time, an in-depth analysis of

A. D. Kammogne, L. C. Fai

The phenomenon of spontaneous emission can lead to the creation of an imaginary coupling and a shift. To explore this, we utilized the renormalized first Nikitin model, revealing an exponential detuning variation with a phase and an imaginary coupling along with the shift. By employing the time-dependent Schr\"odinger equation, we investigated the behavior o

Lennart Schneider, Martin Wistuba, Aaron Klein, Jacek Golebiowski

Optimal prompt selection is crucial for maximizing large language model (LLM) performance on downstream tasks, especially in black-box settings where models are only accessible via APIs. Black-box prompt selection is challenging due to potentially large, combinatorial search spaces, absence of gradient information, and high evaluation cost of prompts on a va

Salvatore Butera

We extend the theory of the radiation pressure to include quadratic fluctuations in the position of a moving mirror. This enables the introduction of a generalized radiation pressure operator that captures higher-order effects in the mirror-field coupling. For mechanical resonators with frequencies comparable to the fundamental cavity frequency, the resultin

Albert Elias-López, Fabio Del Sordo, Daniele Viganò, Clàudia Soriano-Guerrero

Magnetic fields remain one of the least understood aspects of exoplanetary systems. A deeper understanding of planetary dynamos and the evolution of surface magnetic properties throughout a planet's lifetime is a key scientific purpose, with implications for planetary evolution, habitability, and atmospheric dynamics. This study models the evolution of magne

Norihiro Iizuka, Simon Lin, Mitsuhiro Nishida

We investigate the multi-partite entanglement structure of an evaporating black hole and its Hawking radiation by dividing the radiation into finer subsystems. We approximate an evaporating black hole and its radiation with a Haar-random state for this purpose. Using the multi-entropy of these configurations, we define a black hole multi-entropy curve, which

Sibei Chen, Ju Fan, Bin Wu, Nan Tang

Database management system (DBMS) configuration debugging, e.g., diagnosing poorly configured DBMS knobs and generating troubleshooting recommendations, is crucial in optimizing DBMS performance. However, the configuration debugging process is tedious and, sometimes challenging, even for seasoned database administrators (DBAs) with sufficient experience in D

Mattia Coccolo, Miguel A. F. Sanjuán

When two systems are coupled, the driver system can function as an external forcing over the driven or response system. Also, an external forcing can independently perturb the driven system, leading us to examine the interplay between the dynamics induced by the driver system and the external forcing acting on the response system. The cooperation of the two

Alessandro De Stefani, Shreedevi K. Masuti, Maria Evelina Rossi, Jugal K. Verma

We study the behavior of the Hilbert-Kunz multiplicity of powers of an ideal in a local ring. In dimension two, we provide answers to some problems raised by Smirnov, and give a criterion to answer one of his questions in terms of a "Ratliff-Rush version" of the Hilbert-Kunz multiplicity.

Casper van Peijpe, Farhad Ghanipoor, Youri de Loore, Pim Hacking

This paper presents a mathematical framework for modeling the dynamic effects of three fault categories and six fault variants in the ink channels of high-end industrial printers. It also introduces a hybrid approach that combines model-based and data-based methods to detect and isolate these faults effectively. A key challenge in these systems is that the s

Chuan Chen, Peng Luo, Bo Zhao, Yu Feng

Spatial analysis can generate both exogenous and endogenous biases, which will lead to ethics issues. Exogenous biases arise from external factors or environments and are unrelated to internal operating mechanisms, while endogenous biases stem from internal processes or technologies. Although much attention has been given to exogenous biases, endogenous bias

Amin Abyaneh, Mahrokh G. Boroujeni, Hsiu-Chin Lin, Giancarlo Ferrari-Trecate

Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous research relying on stable dynamical systems guarantees convergence to a desired state, it often overlooks transient behavior. We propose a framework for learning policies modeled by con

Ling-Yun Dai, Johann Haidenbauer, Ulf-G. Meißner

We review recent experimental and theoretical results for the electromagnetic form factors of hyperons (Y) in the timelike region, accessible in the reactions $e^+e^-\to \bar YY$. Specifically, we focus on the final states $\bar \Lambda\Lambda$, $\bar\Lambda\Sigma^0$/$\bar \Sigma^0\Lambda$, $\bar \Sigma\Sigma$, $\bar \Xi\Xi$, and $\bar\Omega\Omega$. The $\ba

Babak Jabbar Nezhad

Bishop's constructive mathematics school rejects the Law of Excluded Middle, but instead vastly makes use of weaker versions of the Choice. In this paper we pioneer an example, which shows that this road is not consistent, as our example provides a paradox. Therefore, rejecting the Law of Excluded Middle, and as an alternative using the Countable Axiom of Ch

Kaiqiang Lin, Yijie Mao

Wireless-powered underground sensor networks (WPUSNs), which enable wireless energy transfer to sensors located underground, is a promising approach for establishing sustainable internet of underground things (IoUT). To support urgent information transmission and improve resource utilization within WPUSNs, backscatter communication (BC) is introduced, result

Guillaume de Romémont, Florent Renac, Jorge Nunez, Francisco Chinesta

This paper presents a data-driven finite volume method for solving 1D and 2D hyperbolic partial differential equations. This work builds upon the prior research incorporating a data-driven finite-difference approximation of smooth solutions of scalar conservation laws, where optimal coefficients of neural networks approximating space derivatives are learned

David Cruz-Uribe, Sullivan F. MacDonald, Scott Rodney

We consider the boundedness and exponential integrability of solutions to the Dirichlet problem for the degenerate elliptic equation \[ -v^{-1}\mathrm{Div}(|\sqrt{Q}\nabla u|^{p-2}Q\nabla u)=f|f|^{p-2}- v^{-1}\mathrm{Div}(v|g|^{p-2}g \mathbf{t}), \quad 1<p<\infty, \] assuming that there is a Sobolev inequality of the form \[ \|\varphi\|_{L^N(v,\Omega)}\leq S

Aryan Bhosale, Samrat Mukherjee, Biplab Banerjee, Fabio Cuzzolin

This paper explores the utility of diffusion-based models for anomaly detection, focusing on their efficacy in identifying deviations in both compact and high-resolution datasets. Diffusion-based architectures, including Denoising Diffusion Probabilistic Models (DDPMs) and Diffusion Transformers (DiTs), are evaluated for their performance using reconstructio

D. Cotroneo, F. C. Grasso, R. Natella, V. Orbinato

Vulnerability prediction is valuable in identifying security issues efficiently, even though it requires the source code of the target software system, which is a restrictive hypothesis. This paper presents an experimental study to predict vulnerabilities in binary code without source code or complex representations of the binary, leveraging the pivotal idea

Linlin Sun, Xiaobao Zhu

Let $(M, g)$ be a compact Riemann surface with area $1$. We investigate the Toda system \begin{align} \begin{cases} -\Delta u_1 = 2\rho_1(h_1e^{u_1}-1) - \rho_2(h_2e^{u_2}-1),\\ -\Delta u_2 = 2\rho_2(h_2e^{u_2}-1) - \rho_1(h_1e^{u_1}-1), \end{cases} \end{align} on $(M, g)$ where $\rho_1, \rho_2 \in (0,4\pi]$, and $h_1$ and $h_2$ are two smooth functions on $

Nir Gavish

Infectious diseases often involve multiple strains that interact through the immune response generated after an infection. This study investigates the conditions under which a two-strain epidemic model with partial cross-immunity can lead to self-sustained oscillations, and reveals a new oscillatory regime in these models. Contrary to previous findings, whic

Dhruva Naik, Garima Rajpoot, Sudhir Ranjan Jain

Controlling quantum jumps is crucial for reliable quantum computing. In this work, we demonstrate how the quantum Zeno effect can be applied to a two qubit system interacting with an ancilla which is a component of surface code architecture used to control undesired transitions. Further, we show that by designing the interaction and tuning measurement freque

Jingzhi Li, Zongwei Wu, Eduard Zamfir, Radu Timofte

Accurate 3D objects relighting in diverse unseen environments is crucial for realistic virtual object placement. Due to the albedo-lighting ambiguity, existing methods often fall short in producing faithful relights. Without proper constraints, observed training views can be explained by numerous combinations of lighting and material attributes, lacking phys

Francesco Benetti, Andrea Lapi, Samuele Silveravalle, Stefano Liberati

In the framework of a collisionless dark matter fluid which is non-minimally coupled to gravity, we investigate the existence and properties of static, spherically symmetric solutions of the general relativistic field equations. We show that the non-minimal coupling originates an (anisotropic) pressure able to counteract gravity and to allow the formation of

C. J. A. P. Martins, M. A. F. Melo e Sousa, S. Q. Fernandes, C. M. J. Marques

The redshift drift of objects following the cosmological expansion is a unique model-independent probe of background cosmology, detectable by astrophysical facilities presently under construction. Previous forecasts for such measurements assume flat universes. We explore the impact of relaxing this assumption on the constraining power of the redshift drift,

Juntao He, Yikai Dang, Haoqi Wang, Shaohua Wang

Based on grating diffraction principle, optical fiber transmission principle and optical interference principle, a multi-functional portable optical measuring instrument is constructed in this paper. The optical measurement visualization spectrometer based on CCD photoelectric image sensor is designed and assembled. The "Y" optical signal transmission fiber

Hua Chen, Yun Lu Fan, Xin Liao

We establish sharp quantitative stability estimates near finite sums of ground states. The results depend on the dimension and the order of nonlinearity.

Kjell S. Heinrich, Henning G. Hugdal, Morten Amundsen, Sol H. Jacobsen

We consider the effect of bending-strain in thin films of clean, conventional superconductors (S), and the proximity-induced effect of this strain in SN bilayers with a normal metal (N), and SNS junctions with equal curvatures in each superconductor. We find that the effective spin-orbit coupling due to strain in the superconductor induces both spin-polarize

Juntao He, Yikai Dang, Haoqi Wang, Shaohua Wang

In this paper, a thin film thickness gauge based on the interferometric principle of Y-shaped optical fiber is proposed to achieve accurate measurement of film thickness. In this paper, the optical fiber, the interferometric principle and the film thickness calculation principle are introduced, and the interferometric thickness measurement system based on Y-

Tu Vo, Chan Y. Park

Low-light and blurring issues are prevalent when capturing photos at night, often due to the use of long exposure to address dim environments. Addressing these joint problems can be challenging and error-prone if an end-to-end model is trained without incorporating an appropriate physical model. In this paper, we introduce JUDE, a Deep Joint Unrolling for De

Nicharee Srikijkasemwat, Soumya Snigdha Kundu, Fuping Wu, Bartlomiej W. Papiez

Knee osteoarthritis (OA) is the most common joint disorder and a leading cause of disability. Diagnosing OA severity typically requires expert assessment of X-ray images and is commonly based on the Kellgren-Lawrence grading system, a time-intensive process. This study aimed to develop an automated deep learning model to classify knee OA severity, reducing t

David A. Hague

This paper demonstrates a method that synthesizes narrowband Multiple-Input Multiple-Output (MIMO) beampatterns using the Multi-Tone Sinusoidal Frequency Modulated (MTSFM) waveform model. MIMO arrays transmit unique waveforms on each of their elements which increases the degrees of freedom available to synthesize novel transmit beampatterns. The MIMO beampat

Fiona Murphy, Marina Navas Bachiller, Deirdre M. D'Arcy, Alessio Benavoli

In-vitro dissolution testing is a critical component in the quality control of manufactured drug products. The $\mathrm{f}_2$ statistic is the standard for assessing similarity between two dissolution profiles. However, the $\mathrm{f}_2$ statistic has known limitations: it lacks an uncertainty estimate, is a discrete-time metric, and is a biased measure, ca

Ryo Tazaki, François Ménard, Gaspard Duchêne, Marion Villenave

We present near- and mid-infrared (IR) broadband imaging observations of the edge-on protoplanetary disk around HH 30 with the James Webb Space Telescope/Near Infrared Camera (NIRCam) and the Mid-Infrared Instrument (MIRI). We combine these observations with archival optical/near-IR scattered light images obtained with the Hubble Space Telescope (HST) and a

Niklas Schwanemann, Stefan Weinzierl

We present for Moller scattering planar and non-planar two-loop double-box integrals where three electroweak gauge bosons are exchanged between the fermion lines, among which at least one is a photon. These integrals are relevant for the NNLO electroweak corrections to Moller scattering.

Nicola Henkelmann, Stephan Rhode, Johannes von Keler

Vehicle models have a long history of research and as of today are able to model the involved physics in a reasonable manner. However, each new vehicle has its new characteristics or parameters. The identification of these is the main task of an engineer. To validate whether the correct parameter set has been chosen is a tedious task and often can only be pe

Abdalla Swikir

This paper introduces a compositional framework for constructing finite abstractions of nonlinear interconnected impulsive systems using dissipativity-based conditions. Central to our approach is the concept of "alternating simulation functions," which serve to relate the concrete dynamics of impulsive subsystems to their finite abstractions. Dissipativity c

Koby Bibas

Machine learning models have exhibited exceptional results in various domains. The most prevalent approach for learning is the empirical risk minimizer (ERM), which adapts the model's weights to reduce the loss on a training set and subsequently leverages these weights to predict the label for new test data. Nonetheless, ERM makes the assumption that the tes

Nurettin Turan, Srikar Allaparapu, Donia Ben Amor, Benedikt Böck

This letter proposes a graph neural network (GNN)-based framework for statistical precoder design that leverages model-based insights to compactly represent statistical knowledge, resulting in efficient, lightweight architectures. The framework also supports approximate statistical information in frequency division duplex (FDD) systems obtained through a Gau

Jiaqi Fan, Jianhua Wu, Hongqing Chu, Quanbo Ge

Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding and generation tasks. However, these models occasionally generate hallucinatory texts, resulting in descriptions that seem reasonable but do not correspond to the image. This phenomenon can lead to wrong driving decisions of the autonomous driving syste

Yingying Deng, Xiangyu He, Changwang Mei, Peisong Wang

Though Rectified Flows (ReFlows) with distillation offers a promising way for fast sampling, its fast inversion transforms images back to structured noise for recovery and following editing remains unsolved. This paper introduces FireFlow, a simple yet effective zero-shot approach that inherits the startling capacity of ReFlow-based models (such as FLUX) in

Nicolás Villarroel-Sepúlveda, Pablo S. Moya, Felipe A. Asenjo, Swadesh M. Mahajan

It is shown that in the spacetime dominated by a cosmological constant, in the far region of a Schwarzschild-de Sitter black hole, a seed magnetic field can be generated in an ambient plasma (in a state of no magnetic field) by a general-relativistic battery, which depends on the interaction of spacetime curvature with inhomogeneous plasma thermodynamics. Th

Sebastian Steindl, Ulrich Schäfer, Bernd Ludwig

Large-scale Wizard-Of-Oz dialogue datasets have enabled the training of deep learning-based dialogue systems. While they are successful as benchmark datasets, they lack certain types of utterances, which would make them more realistic. In this work, we investigate the creation of synthetic communication errors in an automatic pipeline. Based on linguistic th

Branislava Lalic, Dinh Viet Cuong, Mina Petric, Vladimir Pavlovic

Vector-borne diseases continue to pose a significant health threat globally with more than 3 billion people at risk each year. Despite some limitations, mechanistic dynamic models are a popular approach to representing biological processes using ordinary differential equations where the parameters describe the different development and survival rates. Recent

Zongbo Liao, Xuanxuan Zhang, Tianxiang Zhang, Zhi Li

LiDAR is widely used in Simultaneous Localization and Mapping (SLAM) and autonomous driving. The LiDAR odometry is of great importance in multi-sensor fusion. However, in some unstructured environments, the point cloud registration cannot constrain the poses of the LiDAR due to its sparse geometric features, which leads to the degeneracy of multi-sensor fusi

Mengjue Wang, Stylianos Kampakis

This paper presents the application of Tokenlab, an agent-based modeling framework designed to analyze price dynamics and speculative behavior within token-based economies. By decomposing complex token systems into discrete agent interactions governed by fundamental behavioral rules, Tokenlab simplifies the simulation of otherwise intricate market scenarios.

Xiaoyang Ning, Qing Xie, Jinyu Xu, Wenbo Jiang

Recently, 3D backdoor attacks have posed a substantial threat to 3D Deep Neural Networks (3D DNNs) designed for 3D point clouds, which are extensively deployed in various security-critical applications. Although the existing 3D backdoor attacks achieved high attack performance, they remain vulnerable to preprocessing-based defenses (e.g., outlier removal and

Ravindra Kumar, Om Prakash

For a graph $G= (V, E)$, a Roman dominating function is a map $f : V \rightarrow \{0, 1, 2\}$ satisfies the property that if $f(v) = 0$, then $v$ must have adjacent to at least one vertex $u$ such that $f(u)= 2$. The weight of a Roman dominating function $f$ is the value $f(V)= \Sigma_{u \in V} f(u)$, and the minimum weight of a Roman dominating function on

Vladislav Li, Ilias Siniosoglou, Thomai Karamitsou, Anastasios Lytos

Autonomous Vehicles (AVs) use natural images and videos as input to understand the real world by overlaying and inferring digital elements, facilitating proactive detection in an effort to assure safety. A crucial aspect of this process is real-time, accurate object recognition through automatic scene analysis. While traditional methods primarily concentrate

Apostolos A. Tegos, Yue Xiao, Sotiris A. Tegos, George K. Karagiannidis

One of the main goals of the upcoming sixth-generation (6G) wireless networks is the ability to support higher network density, while ensuring a high quality of service for each user. In this paper, we introduce distributed uplink rate-splitting multiple access (DU-RSMA), define its basic principles, and provide insights into its advantages. Specifically, a

Hongshu Guo, Zeyuan Ma, Jiacheng Chen, Yining Ma

Recent advances in Meta-learning for Black-Box Optimization (MetaBBO) have shown the potential of using neural networks to dynamically configure evolutionary algorithms (EAs), enhancing their performance and adaptability across various BBO instances. However, they are often tailored to a specific EA, which limits their generalizability and necessitates retra

Amaury Micheli, Scott Robertson

We synthesize results of previous works to give a coherent and self-consistent account of parametric resonance in a modulated quasi-1D Bose gas in the presence of a dissipative mechanism. The resonant behaviour is shown to be largely in line with the predictions of a phenomenological model published in 2014, while the associated dissipation rate is consisten

Gérard M T Watts

We present two explicit expressions for generic singular vectors of type $(r,s)$ of the Virasoro algebra. These results follow from the paper of Bauer et al which presented recursive methods to construct the vectors. The expressions presented here generalise the results of Benoit-Saint Aubin for the type $(1,s)$ singular vectors in two different ways: the fi

Roberto Rivelino

DNA has been proposed as a chemical platform for computing and data storage, paving the way for building DNA-based computers. Recently, DNA has been hypothesized as an ideal quantum computer with the base pairs working as Josephson junctions. There are still major challenges to be overcome in these directions, but they do not prevent deviceful perspectives o

Federico Chiariotti, Andrea Munari, Leonardo Badia, Petar Popovski

Goal-oriented communication entails the timely transmission of updates related to a specific goal defined by the application. In a distributed setup with multiple sensors, each individual sensor knows its own observation and can determine its freshness, as measured by Age of Incorrect Information (AoII). This local knowledge is suited for distributed medium

Magnus Goffeng, Bram Mesland, Mehmet Haluk Sengun

We prove that the well-known explicit construction of the local theta correspondence by Li has a simple interpretation in terms of group C*-algebras. In particular, we deduce that in two standard cases where Li's method work, local theta correspondence arises from a continuous functor. Moreover, using results from a companion paper, we treat global theta cor

Hana Formánková Levá, Gabriela Holubová, Petr Nečesal

We study the admissible values of the wave speed $c$ for which the beam equation with jumping nonlinearity possesses a travelling wave solution. In contrast to previously studied problems modelling suspension bridges, the presence of the term with negative part of the solution in the equation results in restrictions of $c$. In this paper, we provide the maxi

Yuchen Sun, Qianqian Xu, Zitai Wang, Zhiyong Yang

Multi-label Out-Of-Distribution (OOD) detection aims to discriminate the OOD samples from the multi-label In-Distribution (ID) ones. Compared with its multiclass counterpart, it is crucial to model the joint information among classes. To this end, JointEnergy, which is a representative multi-label OOD inference criterion, summarizes the logits of all the cla

Daniel Herrera Correa, Cristhiam Lopez-Arcos, Alexander Quintero Velez

By employing the perturbiner method we study the tree- and one-loop-level amplitudes in (anti)self-dual Yang-Mills, focusing on color-kinematics duality and double copy features; they arise naturally even in the fully off-shell case. In particular, we calculate the respective the Kawai-Lewellen-Tye relations for tree-level Berends-Giele currents and color-ki

Lorena Leon, Jonathan Mamou, Denis Kouamé, Adrian Basarab

Quantitative acoustic microscopy (QAM) is a cutting-edge imaging modality that leverages very high-frequency ultrasound to characterize the acoustic and mechanical properties of biological tissues at microscopic resolutions. Radio-frequency echo signals are digitized and processed to yield two-dimensional maps. This paper introduces a weighted Hankel-based s

Fansu Wei, Chi-Kin Lai, Yuying Chen, Zhengxi Zhang

The excited bands in optical lattices manifest an important tool for studying quantum simulation and many-body physics, making it crucial to measure high-band scattering dynamics under strong interactions. This work investigates both experimentally and theoretically the collisional scattering of $^{6}\rm Li_2$ molecular Bose-Einstein condensate in the $D$ ba

Morten Overgaard

Weighting with the inverse probability of censoring is an approach to deal with censoring in regression analyses where the outcome may be missing due to right-censoring. In this paper, three separate approaches involving this idea in a setting where the Kaplan--Meier estimator is used for estimating the censoring probability are compared. In more detail, the