October 2024 arXiv papers — page 15

Rodrigo Humberto Aguilera-del-Toro, Mikel Arruabarrena, Aritz Leonardo, Martin Rodriguez-Vega

The manganese pnictide CaMn$_2$Bi$_2$, with Mn atoms arranged in a puckered honeycomb structure, exhibits narrow-gap antiferromagnetism, and it is currently a promising candidate for the study of complex electronic and magnetic phenomena, such as magnetotransport effects and potential spin spirals under high pressure. In this paper, we perform a detailed res

Tristan Robert

In this work, we pursue our investigations on the Cauchy problem for a class of dispersive PDEs where a rough time coefficient is present in front of the dispersion. We show that if the PDE satisfies a strong non-resonance condition (Theorem 1.6), eventually up to a completely resonant term (Theorem 1.9), then the modulated PDE is well-posed at any regularit

Bo Zhang, Mariana de Souza, Daniel M. Mulvihill, Davy Dalmas

Many properties of soft contact interfaces are controlled by the contact area (e.g. friction, contact stiffness and surface charge generation). The contact area increases with the contact age at rest. In contrast, it usually reduces under unidirectional shear loading. Although the physical origin of such a reduction is still debated, it always happens in an

L. Romanello, A. Teboul, F. Wiesemuller, P. H. Nguyen

Robotic systems show significant promise for water environmental sensing applications such as water quality monitoring, pollution mapping and biodiversity data collection. Conventional deployment methods often disrupt fragile ecosystems, preventing depiction of the undisturbed environmental condition. In response to this challenge, we propose a novel framewo

Thomas B. Mieling, Mario Hudelist

Single-mode fibers are used in fiber-optic gyroscopes to measure the Sagnac effect and are planned to be used in forthcoming experiments on the gravitationally induced phase shift in single photons. However, current theoretical models of such experiments are limited to ray-optics approximations or, if based on wave optics, to a restricted class of fiber alig

José M. Conde-Alonso, Filippo De Mari, Matteo Monti, Elena Rizzo

We prove endpoint and sparse-like bounds for Bergman projectors on nonhomogeneous, radial trees $X$ that model manifolds with possibly unbounded geometry. The natural Bergman measures on $X$ may fail to be doubling, and even locally doubling, with respect to the right metric in our setting. Weighted consequences of our sparse domination results are also cons

Arthur Pignet, Chiara Regniez, John Klein

Despite the increasing demand for safer machine learning practices, the use of Uncertainty Quantification (UQ) methods in production remains limited. This limitation is exacerbated by the challenge of validating UQ methods in absence of UQ ground truth. In classification tasks, when only a usual set of test data is at hand, several authors suggested differen

Alberto Del Pia, Aida Khajavirad

In this paper, we study the problem of minimizing a polynomial function with literals over all binary points, often referred to as pseudo-Boolean optimization. We investigate the fundamental limits of computation for this problem by providing new necessary conditions and sufficient conditions for tractability. On the one hand, we obtain the first intractabil

Ming-Hua Chang, Steffen Backes, Donghui Lu, Nicolas Gauthier

The attractive interaction in conventional BCS superconductors is provided by a bosonic mode. However, the pairing glue of most unconventional superconductors is unknown. The effect of electron-boson coupling is therefore extensively studied in these materials. A key signature are dispersion kinks that can be observed in the spectral function as abrupt chang

Katja Kossira, Jürgen Seiler, André Kaup

This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural, and environmental processes. Due to fabrication differences, noise, or device altering, varying pixel sensitivities occ

Bryan Chan, Xinyi Chen, András György, Dale Schuurmans

It has recently been demonstrated empirically that in-context learning emerges in transformers when certain distributional properties are present in the training data, but this ability can also diminish upon further training. We provide a new theoretical understanding of these phenomena by identifying simplified distributional properties that give rise to th

Le Huang, Hengzhi Lan, Zijun Sun, Chuan Shi

As LLMs exhibit a high degree of human-like capability, increasing attention has been paid to role-playing research areas in which responses generated by LLMs are expected to mimic human replies. This has promoted the exploration of role-playing agents in various applications, such as chatbots that can engage in natural conversations with users and virtual a

Anil Singh, Banarsi Lal

We have established various criteria for the topological transitivity of families of continuous (holomorphic) functions. Furthermore, by leveraging the properties of expanding families of meromorphic functions, we offer an alternative proof of Montel's three point theorem.

Qianxu Wang, Congyue Deng, Tyler Ga Wei Lum, Yuanpei Chen

One-shot transfer of dexterous grasps to novel scenes with object and context variations has been a challenging problem. While distilled feature fields from large vision models have enabled semantic correspondences across 3D scenes, their features are point-based and restricted to object surfaces, limiting their capability of modeling complex semantic featur

Tristan Robert

In this work, we study the Cauchy problem for a class of dispersive PDEs where a rough time coefficient is present in front of the dispersion. Under minimal assumptions on the occupation measure of this coefficient, we show that for the large class of semilinear dispersive PDEs whose well-posedness theory relies on linear estimates of Strichartz or local smo

Lucian Nita, Eric C. Kerrigan

We propose joining a flexible mesh design with an integrated residual transcription in order to improve the accuracy of numerical solutions to optimal control problems. This approach is particularly useful when state or input trajectories are non-smooth, but it may also be beneficial when dynamics constraints are stiff. Additionally, we implement an initial

Chunhua Qi, David J. Wilner

Observations of CO isotopologue emission from protoplanetary disks at millimeter wavelengths are a powerful tool for probing the CO snowline, an important marker for disk chemistry, and also for estimating total disk gas mass, a key quantity for planet formation. We use simple models to demonstrate that the vertical thickness of an isothermal layer around th

David Guo, Matthew Tointon

We show that if all the finite coset spaces of a polycyclic group have diameter bounded uniformly below by a polynomial in their size then the group is virtually nilpotent. We obtain the same conclusion for a finitely generated residually torsion-free nilpotent group under the weaker assumption that the finite quotient groups have diameter bounded uniformly

David Guo

Let $G = K \rtimes \langle t \rangle $ be a finitely generated group where $K$ is abelian and $\langle t\rangle$ is the infinite cyclic group. Let $ R $ be a finite symmetric subset of $K$ such that $S = \{ (r,1),(0,t^{\pm 1}) \mid r \in R \}$ is a generating set of $G$. We prove that the spherical conjugacy ratio, and hence the conjugacy ratio, of $G$ with

Luca Romanello, Tian Lan, Mirko Kovac, Sophie F. Armanini

Forests offer essential resources and services to humanity, yet preserving and restoring them presents challenges, particularly due to the limited availability of actionable data, especially in hard-to-reach areas like forest canopies. Accessibility continues to pose a challenge for biologists collecting data in forest environments, often requiring them to i

Luca Romanello, Leonard Hohaus, David-Marian Schmitt, Mirko Kovac

This research introduces a novel hydrofoil-based propulsion framework for unmanned aquatic robots, inspired by the undulating locomotion observed in select aquatic species. The proposed system incorporates a camber-modulating mechanism to enhance hydrofoil propulsive force generation and eventually efficiency. Through dynamic simulations, we validate the eff

Samuele Peri, Alessio Russo, Gabor Fodor, Pablo Soldati

Link adaptation (LA) is an essential function in modern wireless communication systems that dynamically adjusts the transmission rate of a communication link to match time- and frequency-varying radio link conditions. However, factors such as user mobility, fast fading, imperfect channel quality information, and aging of measurements make the modeling of LA

Chubin Huang, Abhishek Rakshit, Gianluca Janka, Zaher Salman

The coupling between structural, electronic and magnetic degrees of freedom across the metal-insulator transition in V2O3 makes it hard to determine the main driving mechanism behind the transition. Specifically, the role of magnetism has been debated and its interplay with the other transitions has not been established. To address this issue, we use a combi

Nima Akbarzadeh, Yossiri Adulyasak, Erick Delage

In restless bandits, a central agent is tasked with optimally distributing limited resources across several bandits (arms), with each arm being a Markov decision process. In this work, we generalize the traditional restless bandits problem with a risk-neutral objective by incorporating risk-awareness, which is particularly important in various real-world app

Aleksey N. Bolgar, Daria A. Kalacheva, Viktor B. Lubsanov, Aleksei Yu. Dmitriev

Air-bridges play a critical role in the performance of microwave circuits integrated with superconducting quantum bits, and their mechanical stability is predominant for reliable operation. This study is devoted to the technological issues that lead to air-bridge instability. We propose an optimized bridge geometry designed to enhance mechanical resilience.

Devon Stockall

Under appropriate conditions, if one picks a commutative algebra A with action of group G in braided monoidal category C, the category of A modules in C obtains a natural crossed G-braided structure. In the case of general commutative algebra object A in braided monoidal category C, one might ask what weakened notion of braiding one obtains on the category o

David Ginzburg, David Soudry

We determine the poles of the Eisenstein series on a general linear group, induced from two Speh representations, $\Delta(\tau,m_1)|\cdot|^s\times\Delta(\tau,m_2)|\cdot|^{-s}$, $Re(s)\geq 0$, where $\tau$ is an irreducible, unitary, cuspidal, automorphic representation of $GL_n({\bf A})$. The poles are simple and occur at $s=\frac{m_1+m_2}{4}-\frac{i}{2}$, $

Quentin Raillard-Cazanove, Thibaut Knibiehly, Robin Girard

The decarbonisation of the energy system is crucial for achieving climate goals and is inherently linked to the decarbonisation of industry. Despite this, few studies explore the simultaneous impacts of decarbonising both sectors. This paper aims to examine how industrial decarbonisation in Europe affects the energy system and vice versa. To address this, an

Giovanna Feraco, Wissem Boubaker, Petra Rudolf, Antonija Grubišić-Čabo

Bilayer graphene twisted at the angle of about 1.1{\deg} better known as magic angle, exhibits ultra-flat moir\'e superlattice bands that are a source of highly-tunable, exotic quantum phenomena. Such phenomena, like superconductivity, correlated Mott-like insulating states and orbital ferromagnetism are driven by strong-correlation physics that defies class

Robert Fulsche, Oliver Fürst

We show how the Gelfand spectrum of certain commutative operator algebras can be studied based on the theorem of Stone and von Neumann. The method presented is a natural addition to the tools of quantum spectral synthesis, which were recently used to characterize certain commutative Toeplitz algebras on the Fock space. Our method applies to this setting and

Yuli Liu, Min Liu, Christian Walder, Lexing Xie

Next Set Recommendation (NSRec), encompassing related tasks such as next basket recommendation and temporal sets prediction, stands as a trending research topic. Although numerous attempts have been made on this topic, there are certain drawbacks: (i) Existing studies are still confined to utilizing objective functions commonly found in Next Item Recommendat

Qinqing Zheng, Mikael Henaff, Amy Zhang, Aditya Grover

Automatically synthesizing dense rewards from natural language descriptions is a promising paradigm in reinforcement learning (RL), with applications to sparse reward problems, open-ended exploration, and hierarchical skill design. Recent works have made promising steps by exploiting the prior knowledge of large language models (LLMs). However, these approac

Alexandre Delplanque

For r > 1, we show, using the Ledrappier-Young entropy characterization of SRB measures for non-invertible maps, that if a C^r map f of the interval or the circle has its Lyapunov exponent greater than 1/r log ||f ' || $\infty$ on a set E of positive Lebesgue measure, then it admits hyperbolic ergodic invariant measures that are absolutely continuous with re

Mircea Marin, Laurenţiu Leuştean

The Working Formal Methods Symposium (FROM) is a series of workshops that aim to bring together researchers and practitioners who work on formal methods by contributing new theoretical results, methods, techniques, and frameworks, and/or by creating or using software tools that apply theoretical contributions.

Fabien Malbet, Gary A. Mamon, Lucas Labadie, Alessandro Sozzetti

Astrometry is one of the oldest branches of astronomy which measures the position, the proper motion and parallax of celestial objects. Following the Hipparcos and Gaia missions that have measured several billions of them using global astrometry, we propose to increase astrometry precision on pointed objects using differential astrometry in a large field in

Conor Smith, Quinn T. Campbell, Tameem Albash

Parameterized artificial neural networks (ANNs) can be very expressive ansatzes for variational algorithms, reaching state-of-the-art energies on many quantum many-body Hamiltonians. Nevertheless, the training of the ANN can be slow and stymied by the presence of local minima in the parameter landscape. One approach to mitigate this issue is to use parallel

Max W. Knoop, Rahul Deshpande, Ferry F. J. Schrijer, Bas W. van Oudheusden

This study investigates the spatial evolution of a zero pressure gradient turbulent boundary layer (TBL) imposed by a square-wave (SqW) of steady spanwise wall-forcing, which varies along the streamwise direction ($x$). The SqW wall-forcing is imposed experimentally via a series of streamwise periodic belts running in opposite spanwise directions, following

Louis-Pierre Chaintron, Giovanni Conforti

We consider a system of diffusion processes interacting through their empirical distribution. Assuming that the empirical average of a given observable can be observed at any time, we derive regularity and quantitative stability results for the optimal solutions in the associated version of the Gibbs conditioning principle. The proofs rely on the analysis of

Cosima A. Ermert, Manuj Yadav, Jonathan Ehret, Chinthusa Mohanathasan

Virtual reality (VR) environments are frequently used in auditory and cognitive research to imitate real-life scenarios, presumably enhancing state-of-the-art approaches with traditional computer screens. However, the effects of different display technologies on audiovisual processing remain underexplored. This study investigated how VR displayed with an hea

Sambit Kumar Pusty, Rudra Majhi, Dinesh Kumar Singha, Monojit Ghosh

In this paper, we studied the impact of the off-diagonal SNSI parameters in the future long-baseline neutrino oscillation experiments DUNE and P2SO. In our analysis, we found that the sensitivities of these experiments altered in a very non-trivial way due to the presence of these parameters. Depending on the values of these parameters, they can either compl

Loïc Gassmann, Ioan Manolescu

By the FKG inequality for FK-percolation, the probability of the alternating two-arm event is smaller than the product of the probabilities of having a primal arm and a dual arm, respectively. In this paper, we improve this inequality by a polynomial factor for critical planar FK-percolation in the continuous phase transition regime ($1 \leq q \leq 4$). In p

V. Cabedo, G. Pareras, J. Allitt, A. Rimola

Current models of chemical evolution during star and planetary formation rely on the presence of dust grains to act as a third body. However, they generally ignore the reactivity of the dust grains themselves. Dust grains present in the protoplanetary phase will evolve as the solar system forms and, after protoplanets have appeared, they will be constantly d

John Southworth

MU Cas is a detached eclipsing binary containing two B5 V stars in an orbit of period 9.653 d and eccentricity 0.192, which has been observed in seven sectors using the Transiting Exoplanet Survey Satellite (TESS). We use these new light curves together with published spectroscopic results to measure the physical properties of the component stars, finding ma

John Southworth

IQ Per is a totally-eclipsing binary system containing a B8 V star and an A6 V star in an orbit of period 1.744 d with eccentricity and apsidal motion. We use new light curves from the Transiting Exoplanet Survey Satellite (TESS) and published spectroscopy from Lacy & Frueh (1985) to measure the physical properties of the component stars, finding masses of 3

Ada Stelzer, Alexander Yong

The Robinson-Schensted-Knuth correspondence (RSK) is a bijection between nonnegative integer matrices and pairs of Young tableaux. We study it as a linear operator on the coordinate ring of matrices, proving results about its diagonalizability, eigenvalues, trace, and determinant. Our criterion for diagonalizability involves the $ADE$ classification of Dynki

Ryuhaerang Choi, Soumyajit Chatterjee, Dimitris Spathis, Sung-Ju Lee

Developing new machine learning applications often requires the collection of new datasets. However, existing datasets may already contain relevant information to train models for new purposes. We propose SoundCollage: a framework to discover new classes within audio datasets by incorporating (1) an audio pre-processing pipeline to decompose different sounds

Connor Clayton, Xiaodi Wu, Bobby Bhattacharjee

We introduce QuARC, Quantum Adaptive Routing using Clusters, a novel clustering-based entanglement routing protocol that leverages redundant, multi-path routing through multi-particle projective quantum measurements to enable high-throughput, low-overhead, starvation-free entanglement distribution. At its core, QuARC periodically reconfigures the underlying

Peng Cheng, Jindong Pan, Haichen Xu, Si-Jiang Yang

Exploring the universal structure of the gravitational path integral beyond semi-classical saddles and uncovering a compelling statistical interpretation of black hole thermodynamics have long been significant challenges. We investigate the statistical interpretation of the Kerr-AdS black hole thermodynamics through an ensemble-averaged theory. By extending

Javier Nistal, Marco Pasini, Stefan Lattner

Building upon Diff-A-Riff, a latent diffusion model for musical instrument accompaniment generation, we present a series of improvements targeting quality, diversity, inference speed, and text-driven control. First, we upgrade the underlying autoencoder to a stereo-capable model with superior fidelity and replace the latent U-Net with a Diffusion Transformer

Jialiang Zhang, Haoran Liu, Danshi Li, Xinqiang Yu

Grasping in cluttered scenes remains highly challenging for dexterous hands due to the scarcity of data. To address this problem, we present a large-scale synthetic benchmark, encompassing 1319 objects, 8270 scenes, and 427 million grasps. Beyond benchmarking, we also propose a novel two-stage grasping method that learns efficiently from data by using a diff

Matthias Reitzner, Anna Strotmann

For a Borel set $A$ and a stationary Poisson point process $\eta_t$ in $\mathbb R^d$ of intensity $t>0$, the Poisson-Delaunay approximation $ A_{\eta_t}$ of $A$ is the union of all Delaunay cells generated by $\eta_t$ with center in $A$. It is shown that $\lambda_d(A_{\eta_t})$ is an unbiased estimator for $\lambda_d(A)$, variance bounds and a quantitative c

Hugo Spring-Ragain

This article examines how emerging economies use countercyclical monetary policies to manage economic crises and fluctuations in dominant currencies, such as the US dollar and the euro. Global economic cycles are marked by phases of expansion and recession, often exacerbated by major financial crises. These crises, such as those of 1997, 2008 and the disrupt

Christian Fröhlich, Robert C. Williamson

What does it mean to say that, for example, the probability for rain tomorrow is between 20% and 30%? The theory for the evaluation of precise probabilistic forecasts is well-developed and is grounded in the key concepts of proper scoring rules and calibration. For the case of imprecise probabilistic forecasts (sets of probabilities), such theory is still la

Zehan Qi, Rongwu Xu, Zhijiang Guo, Cunxiang Wang

Retrieval-augmented generation (RAG) is a promising approach to address the limitations of fixed knowledge in large language models (LLMs). However, current benchmarks for evaluating RAG systems suffer from two key deficiencies: (1) they fail to adequately measure LLMs' capability in handling long-context retrieval due to a lack of datasets that reflect the

Tianfu Wang, Long Yang, Chao Wang, Chuan Qin

Virtual Network Embedding (VNE) is a fundamental resource allocation challenge that is associated with hard and multifaceted constraints in network function virtualization (NFV). Existing works for VNE struggle to handle such complex constraints, leading to compromised system performance and stability. In this paper, we propose a \textbf{CON}straint-\textbf{

Ilia Ponomarenko, Grigory Ryabov

Following Wielandt, a finite group $G$ is called a $B$-group (Burnside group) if every primitive group containing a regular subgroup isomorphic to $G$ is doubly transitive. Using a method of Schur rings, Wielandt proved that every abelian group of composite order which has at least one cyclic Sylow subgroup is a $B$-group. Since then, other infinite families

Jonas Bode, Bastian Pätzold, Raphael Memmesheimer, Sven Behnke

Recent advances in LLM have been instrumental in autonomous robot control and human-robot interaction by leveraging their vast general knowledge and capabilities to understand and reason across a wide range of tasks and scenarios. Previous works have investigated various prompt engineering techniques for improving the performance of LLM to accomplish tasks,

Deperias Kerre, Anne Laurent, Kenneth Maussang, Dickson Owuor

A well structured collection of the various Quantum Cascade Laser (QCL) design and working properties data provides a platform to analyze and understand the relationships between these properties. By analyzing these relationships, we can gain insights into how different design features impact laser performance properties such as the working temperature. Most

Jingkun Ma, Runzhe Zhan, Yang Li, Di Sun

A hallmark of advanced artificial intelligence is the capacity to progress from passive visual perception to the strategic modification of visual information to facilitate complex reasoning. This advanced capability, however, remains critically underdeveloped in current Large Multi-modal Models (LMMs). The deficiency is often masked by evaluation metrics tha

Chenhui Lv, Jack H. Koolen

Let $\Gamma$ be a distance-regular graph with classical parameters $(D, b, \alpha, \beta)$ satisfying $b\geq 2$ and $D\geq 3$. Let $r=1+b+b^2+\cdots+b^{D-1}$. In 1999, K. Metsch showed that there exists a positive constant $C(\alpha,b)$ only depending on $\alpha$ and $b$, such that if $\beta \geq C(\alpha, b)r^2$, then either $\Gamma$ is a Grassmann graph or

Jason Levesley, Bing Li, David Simmons, Sanju Velani

Let $X = [0,1]$, and let $T:X\to X$ be an expanding piecewise linear map sending each interval of linearity to $[0,1]$. For $\psi:\mathbb N\to\mathbb R_{\geq 0}$, $x\in X$, and $N\in\mathbb N$ we consider the recurrence counting function \[ R(x,N;T,\psi) := \#\{1\leq n\leq N: d(T^n x, x) < \psi(n)\}. \] We show that for any $\varepsilon > 0$ we have \[ R(x,N

Kirk Bansak, Soonbong Lee, Vahideh Manshadi, Rad Niazadeh

Motivated by our collaboration with a major refugee resettlement agency in the U.S., we study a dynamic matching problem where each new arrival (a refugee case) must be matched immediately and irrevocably to one of the static resources (a location with a fixed annual quota). In addition to consuming the static resource, each case requires post-allocation ser

Zhenyi Hou, Xu Zhao, Kejie Ye, Xinyu Sheng

Vocal education in the music field is difficult to quantify due to the individual differences in singers' voices and the different quantitative criteria of singing techniques. Deep learning has great potential to be applied in music education due to its efficiency to handle complex data and perform quantitative analysis. However, accurate evaluations with li

Tom Gustafsson

We summarise three applications of the obstacle problem to membrane contact, elastoplastic torsion and cavitation modelling, and show how the resulting models can be solved using mixed finite elements. It is challenging to construct fixed computational meshes for any inequality-constrained problem because the coincidence set has an unknown shape. Consequentl

Yuqi Wang, Wei-Hai Fang, Zhendong Li

Many-body perturbation theory (MBPT) based on Green's functions and Feynman diagrams provides a fundamental theoretical framework for various \emph{ab initio} computational approaches in molecular and materials science, including the random phase approximation (RPA) and $GW$ approximation. Unfortunately, this perturbation expansion often fails in systems wit

Gabriel Wallin, Marie Wiberg

In test equating, ensuring score comparability across different test forms is crucial but particularly challenging when test groups are non-equivalent and no anchor test is available. Local test equating aims to satisfy Lord's equity requirement by conditioning equating transformations on individual-level information, typically using anchor test scores as pr

Sahasra Kokkula, Ankit Vatsa, Savaridassan P

The advent of edge computing is set to revolutionize cloud computing in various sectors, including Agriculture, Health, and more. AWS Greengrass Core Device plays a pivotal role in this transformative process by bridging connections between IoT devices by improving data sharing between them, unlocking new possibilities in Smart Home, Agriculture, Health, Veh

Joon-Hwi Kim, Jung-Wook Kim, Sungsoo Kim, Sangmin Lee

In a classical scattering problem, the classical eikonal is defined as the generator of the canonical transformation that maps in-states to out-states. It can be regarded as the classical limit of the log of the quantum S-matrix. In a classical analog of the Born approximation in quantum mechanics, the classical eikonal admits an expansion in oriented tree g

Pravakar Paul, Manjil P. Saikia

In this paper, we give inductive sum formulas to calculate the number of diagonally symmetric, and diagonally \& anti-diagonally symmetric domino tilings of Aztec Diamonds. As a byproduct, we also find such a formula for the unrestricted case as well. Our proofs rely on a new technique for counting the number of perfect matchings of graphs, proposed by the a

Qiong Wu, Jiahou Chu, Pingyi Fan, Kezhi Wang

This paper investigates distributed computing and cooperative control of connected and automated vehicles (CAVs) in ramp merging scenario under transportation cyber-physical system. Firstly, a centralized cooperative trajectory planning problem is formulated subject to the safely constraints and traffic performance in ramp merging scenario, where the traject

Jelena Wohlwend, Oliver Wipf, David Kiwic, Siro Käch

Plasmons can drive chemical reactions by directly exciting intramolecular transitions. However, strong coupling of plasmons to single molecules remains a challenge as ultra-small mode volumes are required. In the presented work, we propose Cu-Pd plasmonic network metamaterials as a scalable platform for plasmon-assisted catalysis. Due to the absence of trans

Glen Berman, Ned Cooper, Wesley Hanwen Deng, Ben Hutchinson

To evaluate the societal impacts of GenAI requires a model of how social harms emerge from interactions between GenAI, people, and societal structures. Yet a model is rarely explicitly defined in societal impact evaluations, or in the taxonomies of societal impacts that support them. In this provocation, we argue that societal impacts should be conceptualise

Guancen Lin, Cong Shen, Aijing Lin

Time series analysis has gained significant attention due to its critical applications in diverse fields such as healthcare, finance, and sensor networks. The complexity and non-stationarity of time series make it challenging to capture the interaction patterns across different timestamps. Current approaches struggle to model higher-order interactions within

Zichen Wen, Tianyi Wu, Yazhou Ren, Yawen Ling

Multi-view clustering is an important machine learning task for multi-media data, encompassing various domains such as images, videos, and texts. Moreover, with the growing abundance of graph data, the significance of multi-view graph clustering (MVGC) has become evident. Most existing methods focus on graph neural networks (GNNs) to extract information from

Haim Barad, Jascha Achterberg, Tien Pei Chou, Jean Yu

In this paper, we focus on Dynamic Execution techniques that optimize the computation flow based on input. This aims to identify simpler problems that can be solved using fewer resources, similar to human cognition. The techniques discussed include early exit from deep networks, speculative sampling for language models, and adaptive steps for diffusion model

Alaa Awad Abdellatif, Ali Elmancy, Amr Mohamed, Ahmed Massoud

This paper introduces a comprehensive framework for Post-Disaster Search and Rescue (PDSR), aiming to optimize search and rescue operations leveraging Unmanned Aerial Vehicles (UAVs). The primary goal is to improve the precision and availability of sensing capabilities, particularly in various catastrophic scenarios. Central to this concept is the rapid depl

Zhiding Liu, Jiqian Yang, Qingyang Mao, Yuze Zhao

Multivariate time series forecasting plays a crucial role in various real-world applications. Significant efforts have been made to integrate advanced network architectures and training strategies that enhance the capture of temporal dependencies, thereby improving forecasting accuracy. On the other hand, mainstream approaches typically utilize a single unif

Kaiqin Yang, Yixiang Dai, Guijin Wang, Siang Chen

6-DoF grasp detection is critically important for the advancement of intelligent embodied systems, as it provides feasible robot poses for object grasping. Various methods have been proposed to detect 6-DoF grasps through the extraction of 3D geometric features from RGBD or point cloud data. However, most of these approaches encounter challenges during real

Yuxin Zhang, Dandan Zheng, Biao Gong, Shiwen Wang

Lighting plays a pivotal role in ensuring the naturalness and aesthetic quality of video generation. However, the impact of lighting is deeply coupled with other factors of videos, e.g., objects and scenes. Thus, it remains challenging to disentangle and model coherent lighting conditions independently, limiting the flexibility to control lighting in video g

Jake S. Rhodes, Adam G. Rustad

Data from individual observations can originate from various sources or modalities but are often intrinsically linked. Multimodal data integration can enrich information content compared to single-source data. Manifold alignment is a form of data integration that seeks a shared, underlying low-dimensional representation of multiple data sources that emphasiz

Shikha Bordia

In this work, we present two systems -- Named Entity Resolution (NER) and Natural Language Inference (NLI) -- for detecting legal violations within unstructured textual data and for associating these violations with potentially affected individuals, respectively. Both these systems are lightweight DeBERTa based encoders that outperform the LLM baselines. The

Yutaka Ohira

We solve the cosmic-ray diffusion around a Galactic black hole binary (microquasars) by considering the finite size of the escape region and the continuous cosmic-ray injection. We find that the energy spectrum of escaping cosmic rays in the gamma-ray emission region is described by a broken power law spectrum with one or two spectral breaks even though the

Stefan Rohshap, Marc K. Ritter, Hiroshi Shinaoka, Jan von Delft

We present the first application of quantics tensor trains (QTTs) and tensor cross interpolation (TCI) to the solution of a full set of self-consistent equations for multivariate functions, the so-called parquet equations. We show that the steps needed to evaluate the equations (Bethe--Salpeter equations, parquet equation and Schwinger--Dyson equation) can b

Giuseppe Di Sciascio

In high energy Gamma-Ray Astronomy with shower arrays the most discriminating signature of the photon-induced showers against the background of hadron-induced cosmic-ray is the content of muons in the observed events. In the electromagnetic $\gamma$-showers the muon production is mainly due to the photo-production of pions followed by the decay $\pi\to\mu\nu

International Clock, Oscillator Networking, Collaboration, :

Optical clocks have improved their frequency stability and estimated accuracy by more than two orders of magnitude over the best caesium microwave clocks that realise the SI second. Accordingly, an optical redefinition of the second has been widely discussed, prompting a need for the consistency of optical clocks to be verified worldwide. While satellite fre

Alberto Carlo Maria Mancino, Salvatore Bufi, Angela Di Fazio, Antonio Ferrara

Recommender systems have demonstrated significant impact across diverse domains, yet ensuring the reproducibility of experimental findings remains a persistent challenge. A primary obstacle lies in the fragmented and often opaque data management strategies employed during the preprocessing stage, where decisions about dataset selection, filtering, and splitt

Sebastian Ochs, Ivan Habernal

How capable are diffusion models of generating synthetics texts? Recent research shows their strengths, with performance reaching that of auto-regressive LLMs. But are they also good in generating synthetic data if the training was under differential privacy? Here the evidence is missing, yet the promises from private image generation look strong. In this pa

Ahmed Yousfi, Arnaud Demortière, Guillaume Boussinot

An appropriate description of the lithiation/delithiation dynamics in bi-phasic primary cathode particles of Li-ion batteries requires an accurate treatment of the conditions holding at the interface between the particle and the surrounding liquid electrolyte. We propose a phase field model based on the Allen-Cahn approach within which the particle-electroly

Deborshi Das

We consider a generalization of the so-called elephant random walk by introducing multiple elephants moving along the integer line, $\mathbb{Z}$. When taking a new step, each elephant considers not only its own previous steps but also the past steps of other elephants. The dynamics of "who follows whom" are governed by a directed graph, where each vertex rep

Raymond G. Carlberg, Rodrigo Ibata, Nicolas F. Martin, Else Starkenburg

The C-19 star stream has the abundance characteristics of an unusually metal poor globular cluster but kinematically is uncharacteristically hot and wide for a cluster stream, having a line of sight velocity dispersion of 7 +/- 2 km/s and a 1-sigma width of 240 pc. We show that the tidal dissolution of an old, lower mass, globular cluster in a CDM galactic h

Mathias Richerzhagen, Matthias Seidel, Leander Mehrgan, Derek Ives

A new detector controller, NGCII, is in development for the first-generation instruments of the ELT as well as new instruments for the VLT. Building on experience with previous ESO detector controllers, a modular system based on the MicroTCA.4 industrial standard, is designed to control a variety of infrared and visible light scientific and wavefront sensor

Lamine Diop, Marc Plantevit

Discovering valuable insights from data through meaningful associations is a crucial task. However, it becomes challenging when trying to identify representative patterns in quantitative databases, especially with large datasets, as enumeration-based strategies struggle due to the vast search space involved. To tackle this challenge, output space sampling me

Mennatullah Siam

There have been works discussing the adoption of a human rights framework for responsible AI, emphasizing various rights such as the right to contribute to scientific advancements. Yet, to the best of our knowledge, this is the first attempt to take this framework with special focus on computer vision and documenting human rights violations in its community.

Andrea Burgess, Danny Dyer, Kerry Ojakian, Lusheng Wang

Deduction is a recently introduced graph searching process in which searchers clear the vertex set of a graph with one move each, with each searcher's movement determined by which of its neighbors are protected by other searchers. In this paper, we show that the minimum number of searchers required to clear the graph is the same in deduction as in constraine

Belle, Belle II Collaborations, :, I. Adachi

We perform a model-independent measurement of the $D^0$-$\overline{D}{}^0$ mixing parameters using samples of $e^+e^-$-collision data collected by the Belle and Belle II experiments that have integrated luminosities of $951\ \text{fb}^{-1}$ and $408\ \text{fb}^{-1}$, respectively. Approximately $2.05\times10^6$ neutral $D$ mesons are reconstructed in the $D^

Huan-Chih Wang, Ja-Ling Wu

After entering the era of big data, more and more companies build services with machine learning techniques. However, it is costly for companies to collect data and extract helpful handcraft features on their own. Although it is a way to combine with other companies' data for boosting the model's performance, this approach may be prohibited by laws. In other

Shangquan Sun, Wenqi Ren, Zikun Liu, Hyunhee Park

Image restoration has experienced significant advancements due to the development of deep learning. Nevertheless, it encounters challenges related to ill-posed problems, resulting in deviations between single model predictions and ground-truths. Ensemble learning, as a powerful machine learning technique, aims to address these deviations by combining the pre

Vittorio Aita, Diane J. Roth, Anastasiia Zaleska, Alexey V. Krasavin

Structured light plays an important role in metrology, optical trapping and manipulation, communications, quantum technologies, nonlinear optics and provides a rich playground for addressing new optical phenomena. Here we demonstrate a novel approach for manipulating vector vortex beams carrying longitudinal field components using metamaterials with extreme

Miguel A. Herrada

Traditional methods for solving physical equations in curved spaces, especially in fluid mechanics and general relativity, rely heavily on the use of Christoffel symbols. These symbols provide the necessary corrections to account for curvature in differential geometries but lead to significant computational complexity, particularly in numerical simulations.

Jie Yang, Hang Que, Tao Du, Le Liang

Future wireless networks are poised to transform into integrated sensing and communication (ISAC) networks, unlocking groundbreaking services such as digital twinning. To harness the full potential of ISAC networks, it is essential to experimentally validate their sensing capabilities and the role of sensing in boosting communication. However, current protot